From 441267f6ad9f628d9a30db34da5274f4e13721b5 Mon Sep 17 00:00:00 2001 From: r-trimbour <77151348+r-trimbour@users.noreply.github.com> Date: Mon, 22 Apr 2024 16:37:44 +0000 Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20cantinil?= =?UTF-8?q?ab/HuMMuS@609eece8ad4b60df488ba125dd9216ef008c2e6d=20?= =?UTF-8?q?=F0=9F=9A=80?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- articles/chen_vignette.html | 34 ++++++++++++------------ pkgdown.yml | 2 +- reference/compute_atac_peak_network.html | 2 +- reference/compute_gene_network.html | 2 +- reference/compute_tf_network.html | 4 +-- search.json | 2 +- 6 files changed, 23 insertions(+), 23 deletions(-) diff --git a/articles/chen_vignette.html b/articles/chen_vignette.html index b2d9c4b..9b168b3 100644 --- a/articles/chen_vignette.html +++ b/articles/chen_vignette.html @@ -458,12 +458,12 @@

3.2. Retrieve target genes
 head(ATF2_genes)
##   layer                   path_layer        score   tf     gene
-## 1   RNA multiplex/RNA/RNA_GENIE3.tsv 5.312726e-05 ATF2    CDC5L
-## 2   RNA multiplex/RNA/RNA_GENIE3.tsv 4.575481e-05 ATF2     ATF3
-## 3   RNA multiplex/RNA/RNA_GENIE3.tsv 4.486195e-05 ATF2    ATP5I
-## 4   RNA multiplex/RNA/RNA_GENIE3.tsv 4.485264e-05 ATF2 CCNB1IP1
+## 1   RNA multiplex/RNA/RNA_GENIE3.tsv 5.291440e-05 ATF2    CDC5L
+## 2   RNA multiplex/RNA/RNA_GENIE3.tsv 4.570328e-05 ATF2     ATF3
+## 3   RNA multiplex/RNA/RNA_GENIE3.tsv 4.486208e-05 ATF2    ATP5I
+## 4   RNA multiplex/RNA/RNA_GENIE3.tsv 4.485191e-05 ATF2 CCNB1IP1
 ## 5   RNA multiplex/RNA/RNA_GENIE3.tsv 4.482241e-05 ATF2   DGCR14
-## 6   RNA multiplex/RNA/RNA_GENIE3.tsv 4.176625e-05 ATF2    ATAT1
+## 6 RNA multiplex/RNA/RNA_GENIE3.tsv 4.176609e-05 ATF2 ATAT1 
 target_genes <- define_target_genes(
   hummus,
@@ -492,12 +492,12 @@ 
3.2. Retrieve target genes
 head(target_genes)
##   layer                   path_layer        score   tf     gene
-## 1   RNA multiplex/RNA/RNA_GENIE3.tsv 0.0002318538 CUX1   CHRNB1
-## 2   RNA multiplex/RNA/RNA_GENIE3.tsv 0.0002298631 CUX1    CDC5L
-## 3   RNA multiplex/RNA/RNA_GENIE3.tsv 0.0002217500 CUX1    ALG11
-## 4   RNA multiplex/RNA/RNA_GENIE3.tsv 0.0002211191 CUX1    CDCA5
-## 5   RNA multiplex/RNA/RNA_GENIE3.tsv 0.0002201935 CUX1    AGBL5
-## 6   RNA multiplex/RNA/RNA_GENIE3.tsv 0.0001498122 BPTF CDC42SE1
+## 1 RNA multiplex/RNA/RNA_GENIE3.tsv 0.0002318541 CUX1 CHRNB1 +## 2 RNA multiplex/RNA/RNA_GENIE3.tsv 0.0002299783 CUX1 CDC5L +## 3 RNA multiplex/RNA/RNA_GENIE3.tsv 0.0002217501 CUX1 ALG11 +## 4 RNA multiplex/RNA/RNA_GENIE3.tsv 0.0002211187 CUX1 CDCA5 +## 5 RNA multiplex/RNA/RNA_GENIE3.tsv 0.0002201921 CUX1 AGBL5 +## 6 RNA multiplex/RNA/RNA_GENIE3.tsv 0.0001498125 BPTF CDC42SE1

3.3. Define GRN @@ -547,12 +547,12 @@

3.4. Retrieve enhancers
 head(enhancers)

##   layer                              path_layer        score gene
-## 1 peaks multiplex/peaks/peak_network_cicero.tsv 0.0008960582 ATF2
-## 2 peaks multiplex/peaks/peak_network_cicero.tsv 0.0007440111 ATF2
-## 3 peaks multiplex/peaks/peak_network_cicero.tsv 0.0006710919 ATF2
-## 4 peaks multiplex/peaks/peak_network_cicero.tsv 0.0004391423 ATF2
-## 5 peaks multiplex/peaks/peak_network_cicero.tsv 0.0004031270 ATF2
-## 6 peaks multiplex/peaks/peak_network_cicero.tsv 0.0003824837 ATF2
+## 1 peaks multiplex/peaks/peak_network_cicero.tsv 0.0008951819 ATF2
+## 2 peaks multiplex/peaks/peak_network_cicero.tsv 0.0007383304 ATF2
+## 3 peaks multiplex/peaks/peak_network_cicero.tsv 0.0006763254 ATF2
+## 4 peaks multiplex/peaks/peak_network_cicero.tsv 0.0004115710 ATF2
+## 5 peaks multiplex/peaks/peak_network_cicero.tsv 0.0003972408 ATF2
+## 6 peaks multiplex/peaks/peak_network_cicero.tsv 0.0003850920 ATF2
 ##                       peak
 ## 1   chr6-44387360-44388305
 ## 2 chr3-107522766-107524070
diff --git a/pkgdown.yml b/pkgdown.yml
index f1ef80c..9ab7607 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -4,7 +4,7 @@ pkgdown_sha: ~
 articles:
   add_networks: add_networks.html
   chen_vignette: chen_vignette.html
-last_built: 2024-04-22T09:49Z
+last_built: 2024-04-22T16:33Z
 urls:
   reference: https://cantinilab.github.io/HuMMuS/reference
   article: https://cantinilab.github.io/HuMMuS/articles
diff --git a/reference/compute_atac_peak_network.html b/reference/compute_atac_peak_network.html
index c12506d..1ca60ad 100644
--- a/reference/compute_atac_peak_network.html
+++ b/reference/compute_atac_peak_network.html
@@ -98,7 +98,7 @@ 
Usage
     

     
Arguments

     
hummus

-
(hummus_object) - Hummus object

+
(Hummus_Object) - Hummus object

 
 
 
atac_assay

diff --git a/reference/compute_gene_network.html b/reference/compute_gene_network.html
index 9a44832..3ea5f8f 100644
--- a/reference/compute_gene_network.html
+++ b/reference/compute_gene_network.html
@@ -94,7 +94,7 @@ 
Usage
     

     
Arguments

     
hummus

-
(hummus_object) - Hummus object

+
(Hummus_Object) - Hummus object

 
 
 
gene_assay

diff --git a/reference/compute_tf_network.html b/reference/compute_tf_network.html
index 06075b5..4b319d2 100644
--- a/reference/compute_tf_network.html
+++ b/reference/compute_tf_network.html
@@ -88,7 +88,7 @@ 
Usage
     

     
Arguments

     
hummus

-
(hummus_object) - Hummus object

+
(Hummus_Object) - Hummus object

 
 
 
organism

@@ -148,7 +148,7 @@ 
ArgumentsValue

     
 
-
(hummus_object) - Return hummus object with the new network added.

+
(Hummus_Object) - Return hummus object with the new network added.

     

 
     

diff --git a/search.json b/search.json
index a2fb5cb..7995684 100644
--- a/search.json
+++ b/search.json
@@ -1 +1 @@
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General Public Licenses designed make sure freedom distribute copies free software (charge wish), receive source code can get want , can change software use pieces new free programs, know can things. Developers use General Public Licenses protect rights two steps: (1) assert copyright software, (2) offer License gives legal permission copy, distribute /modify software. secondary benefit defending users’ freedom improvements made alternate versions program, receive widespread use, become available developers incorporate. Many developers free software heartened encouraged resulting cooperation. However, case software used network servers, result may fail come . GNU General Public License permits making modified version letting public access server without ever releasing source code public. GNU Affero General Public License designed specifically ensure , cases, modified source code becomes available community. requires operator network server provide source code modified version running users server. Therefore, public use modified version, publicly accessible server, gives public access source code modified version. older license, called Affero General Public License published Affero, designed accomplish similar goals. different license, version Affero GPL, Affero released new version Affero GPL permits relicensing license. precise terms conditions copying, distribution modification follow.","code":""},{"path":[]},{"path":"https://cantinilab.github.io/HuMMuS/LICENSE.html","id":"id_0-definitions","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"0. 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Also add information contact electronic paper mail. software can interact users remotely computer network, also make sure provides way users get source. example, program web application, interface display “Source” link leads users archive code. many ways offer source, different solutions better different programs; see section 13 specific requirements. also get employer (work programmer) school, , sign “copyright disclaimer” program, necessary. information , apply follow GNU AGPL, see https://www.gnu.org/licenses/.","code":"     Copyright (C)         This program is free software: you can redistribute it and/or modify     it under the terms of the GNU Affero General Public License as     published by the Free Software Foundation, either version 3 of the     License, or (at your option) any later version.      This program is distributed in the hope that it will be useful,     but WITHOUT ANY WARRANTY; without even the implied warranty of     MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the     GNU Affero General Public License for more details.      You should have received a copy of the GNU Affero General Public License     along with this program.  If not, see ."},{"path":[]},{"path":[]},{"path":[]},{"path":"https://cantinilab.github.io/HuMMuS/articles/add_networks.html","id":"add-a-new-bipartite","dir":"Articles","previous_headings":"General plan","what":"3. Add a new bipartite","title":"Add external networks to HuMMuS object","text":"","code":"library(reticulate) # install python dependency py_install(\"hummuspy\", envname = \"r-reticulate\", method=\"auto\") ## Using virtual environment 'r-reticulate' ... ## + /home/runner/.virtualenvs/r-reticulate/bin/python -m pip install --upgrade --no-user hummuspy library(HuMMuS) ##"},{"path":"https://cantinilab.github.io/HuMMuS/articles/add_networks.html","id":"initialisation-of-hummus-object","dir":"Articles","previous_headings":"","what":"1. Initialisation of HuMMuS object","title":"Add external networks to HuMMuS object","text":"HuMMuS R objects instances developed top seurat objects. means ’s created seurat object contained assays can accessed way. Additionally, contains motifs_db object, providing tf motifs informations, multilayer objects, completed going tutorial. mostly include : - list multiplex networks (one per modality) - list bipartites (one per connection layers)","code":"# Create an hummus object from seurat object # Load the Chen dataset, which is a Seurat object containing scRNA-seq and scATAC-seq data data(\"chen_dataset_subset\") chen_dataset_subset ## An object of class Seurat  ## 12000 features across 385 samples within 2 assays  ## Active assay: RNA (2000 features, 0 variable features) ##  2 layers present: counts, data ##  1 other assay present: peaks hummus <- Initiate_Hummus_Object(chen_dataset_subset)   # wrapper of Signac::GetGRangesFromEnsDb, adapting output to UCSC format genome_annotations <- get_genome_annotations(   ensdb_annotations = EnsDb.Hsapiens.v86::EnsDb.Hsapiens.v86) # Add annotations to peak assay Signac::Annotation(hummus@assays$peaks) <- genome_annotations rm(genome_annotations)  # Load TF motifs from JASPAR2020 and chromVARmotifs in hummus object hummus@motifs_db <- get_tf2motifs() # by default human motifs"},{"path":[]},{"path":"https://cantinilab.github.io/HuMMuS/articles/add_networks.html","id":"add-a-new-multiplex-through-a-network","dir":"Articles","previous_headings":"2. Add networks","what":"2.1 Add a new multiplex through a network","title":"Add external networks to HuMMuS object","text":"","code":"# The networks should be imported as 3 columns data.frame: (source, target, weight) rna_network_path = \"chen_multilayer/multiplex/RNA/RNA_GENIE3.tsv\" rna_network <- read.table(rna_network_path, sep = \"\\t\", header = FALSE) head(rna_network) ##       V1      V2        V3 ## 1  BACH1  COL4A6 0.7388727 ## 2  DDIT3 CCDC173 0.7060954 ## 3  DDIT3  CCT6P1 0.6697768 ## 4  ATF6B  DNASE1 0.6598122 ## 5 ARID3B   ACER3 0.6499825 ## 6   ATF4  ATP8A1 0.6465523 hummus <- add_network(     hummus, rna_network,     multiplex_name = \"RNA\",     network_name = \"GENIE3\",     verbose = 1) ##  Creating new multiplex :  RNA"},{"path":"https://cantinilab.github.io/HuMMuS/articles/add_networks.html","id":"add-a-network-to-an-existing-multiplex","dir":"Articles","previous_headings":"2. Add networks","what":"2.2 Add a network to an existing multiplex","title":"Add external networks to HuMMuS object","text":"","code":"hummus <- add_network(     hummus, rna_network,     multiplex_name = \"RNA\",     network_name = \"GENIE3_other\")"},{"path":"https://cantinilab.github.io/HuMMuS/articles/add_networks.html","id":"add-external-bipartites","dir":"Articles","previous_headings":"2. Add networks","what":"3 Add external bipartites","title":"Add external networks to HuMMuS object","text":"Bipartites can 2 3 columns data.frame, depending weighted . Bipartites computed HuMMuS added directly object : Display HuMMuS object","code":"## Add TF peaks bipartite atac_rna_path = \"chen_multilayer/bipartite/atac_rna.tsv\" atac_rna <- read.table(atac_rna_path, sep = \"\\t\", header = FALSE) head(atac_rna) ##       V1                        V2 ## 1   CMC1    chr3-28241304-28242015 ## 2 ANGEL2  chr1-213015141-213016006 ## 3  CNNM2 chr10-103053902-103054565 ## 4  DNM1L   chr12-32678989-32680007 ## 5   DHX9  chr1-182838974-182840143 ## 6 B3GAT2    chr6-70955759-70956501 hummus@multilayer@bipartites[[\"atac_rna\"]] <- new(\"bipartite\",                            \"network\" = atac_rna,                            \"multiplex_left\" = \"RNA\",                            \"multiplex_right\" = \"peaks\") hummus ## Hummus object containing a multilayer object : ## Multilayer network containing  1  bipartite networks and  1  multiplex networks. ##   ## - Multiplex names:  RNA  ## - Bipartite names:  atac_rna  ##  ##  ## And a Seurat object : ##  ## 12000 features across samples within 2 assays  ## Active assay: RNA ( features, 0 variable features) ##  1 other assay present: peaks hummus@multilayer@multiplex ## $RNA ## Multiplex of  2  networks with 2000 features. ##  Networks names:  GENIE3, GENIE3_other"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"useful-links","dir":"Articles","previous_headings":"","what":"Useful links:","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"Paper: https://www.biorxiv.org/content/10.1101/2023.06.09.543828v1 Github repo: https://github.com/cantinilab/HuMMuS Documentation: https://cantinilab.github.io/HuMMuS/","code":""},{"path":[]},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"useful-ressources","dir":"Articles","previous_headings":"General description of the pipeline","what":"Useful ressources","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"Preprint detailing method: https://www.biorxiv.org/content/10.1101/2023.06.09.543828v1 Github repo detailing installation: https://github.com/cantinilab/HuMMuS Documentation vignette: https://cantinilab.github.io/HuMMuS","code":""},{"path":[]},{"path":[]},{"path":[]},{"path":[]},{"path":[]},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"setting-up-the-environment","dir":"Articles","previous_headings":"General description of the pipeline","what":"0. Setting up the environment","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"","code":"library(reticulate) # install python dependency py_install(\"hummuspy\", envname = \"r-reticulate\", method=\"auto\") ## Using virtual environment 'r-reticulate' ... ## + /home/runner/.virtualenvs/r-reticulate/bin/python -m pip install --upgrade --no-user hummuspy library(HuMMuS) ##"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"download-the-single-cell-data","dir":"Articles","previous_headings":"General description of the pipeline","what":"Download the single-cell data","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"data used tutorial can downloaded ","code":""},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"initialisation-of-hummus-object","dir":"Articles","previous_headings":"General description of the pipeline","what":"1. Initialisation of HuMMuS object","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"HuMMuS R objects instances developed top seurat objects. means ’s created seurat object contained assays can accessed way. Additionally, contains motifs_db object, providing tf motifs informations, multilayer objects, completed going tutorial. mostly include : list multiplex networks (one per modality) list bipartites (one per connection layers)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"transform-data-into-a-hummus-object","dir":"Articles","previous_headings":"General description of the pipeline > 1. Initialisation of HuMMuS object","what":"1.1. Transform data into a hummus object","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"","code":"# Load the Chen dataset, which is a Seurat object containing scRNA-seq and scATAC-seq data data(\"chen_dataset_subset\") chen_dataset_subset ## An object of class Seurat  ## 12000 features across 385 samples within 2 assays  ## Active assay: RNA (2000 features, 0 variable features) ##  2 layers present: counts, data ##  1 other assay present: peaks # Create an hummus object from seurat object hummus <- Initiate_Hummus_Object(chen_dataset_subset)"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"add-genome-and-motif-annotations-to-hummus-object","dir":"Articles","previous_headings":"General description of the pipeline > 1. Initialisation of HuMMuS object","what":"1.2. Add genome and motif annotations to hummus object","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"Fetch genome annotations online (necessitate internet connection). can also request “EnsDB” object adapted data (e.g. EnsDb.Hsapiens.v86::EnsDb.Hsapiens.v86 human genome annotations) use genome annotations format. Add genome annotations hummus/seurat object Get TF motifs JASPAR2020 chromVARmotifs databsases motifs_db object. default, human motifs used. can specify species want use species argument (e.g. species = “mouse” mouse). motifs_db objects contain 3 slots : * motifs = \"PWMatrixList\" * tf2motifs = \"data.frame\" * tfs = \"NULL\" PWMatrixList named vector motif matrices, whil tf2motifs correspondance table TFs motifs. tfs named vector TFs. can also use motifs_db object, long contains slots.","code":"# get human genome annotation from EndDb data # wrapper of Signac::GetGRangesFromEnsDb, adapting output to UCSC format genome_annotations <- get_genome_annotations(   ensdb_annotations = EnsDb.Hsapiens.v86::EnsDb.Hsapiens.v86)  # can also be downloaded, saved as an RDS objects for example Signac::Annotation(hummus@assays$peaks) <- genome_annotations rm(genome_annotations) # Load TF motifs from JASPAR2020 and chromVARmotifs in hummus object hummus@motifs_db <- get_tf2motifs() # by default human motifs"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"construction-of-the-multilayer-1","dir":"Articles","previous_headings":"General description of the pipeline","what":"2. Construction of the multilayer","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"can compute different layers bipartites indicated . example multilayer completed can also imported : data(chen_subset_hummus). object corresponds multilayer chen_dataset_subset completed. can go part 3, replacing hummus chen_subset_hummus step. Finally, can compute different layers , add afterwards. allows use faster methods compute networks (e.g. Arboreto gene network, ATACNet peak network, etc.).","code":""},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"compute-3-layers-and-2-bipartites","dir":"Articles","previous_headings":"General description of the pipeline > 2. Construction of the multilayer","what":"Compute 3 layers and 2 bipartites","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"!! Long step !! can also go directly part 3 “discovery tour”. :)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"tf---peaks-bipartite-reconstruction","dir":"Articles","previous_headings":"General description of the pipeline > 2. Construction of the multilayer","what":"2.1. TF - peaks bipartite reconstruction","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"TF - peaks bipartite computed using motifs_db object peak assay. can specify assay use filter TFs (e.g. “RNA” want use TFs expressed dataset). NULL, TFs motifs used. BSGenome object used identify location motifs intersect peak can also specify name bipartite added hummus object. default, named “tf_peak”.","code":"hummus <- bipartite_tfs2peaks(               hummus_object = hummus,               tf_expr_assay = \"RNA\", # use to filter TF on only expressed TFs,                                      # if NULL, all TFs with motifs are used               peak_assay = \"peaks\",               tf_multiplex_name = \"TF\",               genome = BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38,               )"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"genes---peaks-bipartite-reconstruction","dir":"Articles","previous_headings":"General description of the pipeline > 2. Construction of the multilayer","what":"2.2. Genes - peaks bipartite reconstruction","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"Peaks - genes bipartite computed","code":"hummus <- bipartite_peaks2genes(                       hummus_object = hummus,                       gene_assay = \"RNA\",                       peak_assay = \"peaks\",                       store_network = FALSE,                       )"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"compute-layer-networks-and-add-it-to-hummus-object","dir":"Articles","previous_headings":"General description of the pipeline > 2. Construction of the multilayer > 2.2. Genes - peaks bipartite reconstruction","what":"Compute layer networks and add it to hummus object","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"one three layers computed individually.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"compute-the-tf-network-from-omnipath-database","dir":"Articles","previous_headings":"General description of the pipeline > 2. Construction of the multilayer","what":"2.3. Compute the TF network from OmniPath database","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"currently use OmniPath R package fetch TF interactions. can first specify want use TFs expressed dataset (RNA assay hummus object). gene_assay NULL, TFs motifs used.  can specify interactions want keep ‘source_target’ argument (“” | “”). “”, interactions 2 TFs present dataset kept. “”, interactions involving least one TF present dataset kept. Finally, can specify name multiplex name network added hummus object. added network undirected unweighted since PPI OmniPath database directional return weight .","code":"hummus <- compute_tf_network(hummus,                             gene_assay = \"RNA\", # default = None ;                                                 # If a assay is provided,                                                 # only the TFs that are present                                                 # will be considered                             verbose = 1,                             #source_target = \"OR\",                             multiplex_name = \"TF\",                             tf_network_name = \"TF_network\")"},{"path":[]},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"this-step-can-be-very-slow-if-you-have-thousands-of-cells","dir":"Articles","previous_headings":"General description of the pipeline > 2. Construction of the multilayer","what":"!! This step can be very slow if you have thousands of cells !!","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"Current recommendation big dataset compute network GRNBoost2 thorugh arboreto add hummus object afterwards. Different methods can used compute gene network. now, GENIE3 implemented HuMMuS. can specify assay use compute network (gene_assay). can specify number cores use compute network. can also specify want save network locally (store_network = TRUE) (store_network = FALSE). choose save network, need specify output file name (output_file). returned network considered undirected weighted. GENIE3 returns directed network, symmetrize random walk restart exploration genes proximity.","code":"hummus <- compute_gene_network(               hummus,               gene_assay = \"RNA\",               method = \"GENIE3\",               verbose = 1,               number_cores = 5, # GENIE3 method can be ran                                 # parallelised on multiple cores               store_network = FALSE, # by default : FALSE, but                                      # each network can be saved                                       # when computed with hummus               output_file = \"gene_network.tsv\")"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"compute-the-peak-network-from-scatac-seq-w-cicero","dir":"Articles","previous_headings":"General description of the pipeline > 2. Construction of the multilayer","what":"2.5. Compute the peak network from scATAC-seq w/ Cicero","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"Different methods can used compute peak network. now, Cicero implemented HuMMuS. can specify assay use compute network (peak_assay). can also specify number cores use compute network. can also specify want save network locally (store_network = TRUE) (store_network = FALSE). choose save network, need specify output file name (output_file). returned network considered undirected weighted, since cis-regulatory interaction Cicero outputs directional.","code":"hummus <- compute_atac_peak_network(hummus,               atac_assay = \"peaks\",               verbose = 1,               genome = BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38,               store_network = FALSE)"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"analyse-of-the-multilayer-and-definition-of-grn","dir":"Articles","previous_headings":"General description of the pipeline","what":"3. Analyse of the multilayer and definition of GRN","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"","code":"data(chen_subset_hummus)  hummus <- chen_subset_hummus"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"save-the-mulilayer-in-a-classic-hierarchical-structure","dir":"Articles","previous_headings":"General description of the pipeline > 3. Analyse of the multilayer and definition of GRN","what":"3.1. Save the mulilayer in a classic hierarchical structure","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"package used random walk restart exploration (multixrank) requires currently save network files disk. simplify organisation file, possible save everything necessary function save_multilayer(). create folder (specified folder_name) containing files necessary run multixrank algorithm. folder contain following subfolders : * bipartite : containing bipartites files * multiplex : containing multiplex sub-subfolders * multiplex_1 (e.g. TF|peak|RNA) : containing network file layer multiplex * seed : contain seed files (necessary compute HuMMuS outputs later) * config : contain config files (necessary compute HuMMuS outputs later)","code":"save_multilayer(hummus = hummus,                 folder_name = \"chen_multilayer\") ## Warning in dir.create(folder_name): 'chen_multilayer' already exists ## Warning in dir.create(paste0(folder_name, \"/\", multiplex_folder)): ## 'chen_multilayer/multiplex' already exists ## Warning in dir.create(paste0(folder_name, \"/\", bipartite_folder)): ## 'chen_multilayer/bipartite' already exists ## Multiplex of  1  networks with 32 features. ##  Networks names:  TF_network[1] \"TF TF_network\" ## Warning in dir.create(paste0(folder_name, \"/\", multiplex_folder, \"/\", ## multiplex_name)): 'chen_multilayer/multiplex/RNA' already exists ## Multiplex of  1  networks with 2000 features. ##  Networks names:  RNA_GENIE3[1] \"RNA RNA_GENIE3\" ## Multiplex of  1  networks with 4639 features. ##  Networks names:  peak_network_cicero[1] \"peaks peak_network_cicero\""},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"retrieve-target-genes","dir":"Articles","previous_headings":"General description of the pipeline > 3. Analyse of the multilayer and definition of GRN","what":"3.2. Retrieve target genes","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"HuMMuS, inference GRN target gene TFs different outputs. Indeed, GRN computed making TFs compete regulate genes (random walk restart starting genes going TFs), target genes computed making genes compete regulated TFs (random walk restart starting TFs going genes). target genes output, can specify list TFs (tf_list) use seed (NULL default, TFs used seed). links seed TFs genes computed. can also specify list genes use. score genes present network gene_list returned.","code":"ATF2_genes <- define_target_genes(   hummus,   tf_list = list(\"ATF2\"),   multilayer_f = \"chen_multilayer\",   njobs = 1   ) ## multiplexes_list :  {'TF': {'TF_network': '00'}, 'RNA': {'RNA_GENIE3': '01'}, 'peaks': {'peak_network_cicero': '01'}} ## bipartites_list :  {'tf_peak.tsv': {'multiplex_right': 'TF', 'multiplex_left': 'peaks'}, 'atac_rna.tsv': {'multiplex_right': 'peaks', 'multiplex_left': 'RNA'}} ## folder_multiplexes :  multiplex ## folder_bipartites :  bipartite ## gene_list :  None ## tf_list :  ['ATF2'] ## peak_list :  None ## config_filename :  target_genes_config.yml ## config_folder :  config ## tf_multiplex :  TF ## peak_multiplex :  peaks ## rna_multiplex :  RNA ## update_config :  True ## save :  False ## return_df :  True ## output_f :  None ## njobs :  1 ## {'TF': {'TF_network': '00'}, 'RNA': {'RNA_GENIE3': '01'}, 'peaks': {'peak_network_cicero': '01'}} ## bipartites_type has been provided throguh a list, make sure the order matches the one of the 'bipartites' dictionary' keys. head(ATF2_genes) ##   layer                   path_layer        score   tf     gene ## 1   RNA multiplex/RNA/RNA_GENIE3.tsv 5.312726e-05 ATF2    CDC5L ## 2   RNA multiplex/RNA/RNA_GENIE3.tsv 4.575481e-05 ATF2     ATF3 ## 3   RNA multiplex/RNA/RNA_GENIE3.tsv 4.486195e-05 ATF2    ATP5I ## 4   RNA multiplex/RNA/RNA_GENIE3.tsv 4.485264e-05 ATF2 CCNB1IP1 ## 5   RNA multiplex/RNA/RNA_GENIE3.tsv 4.482241e-05 ATF2   DGCR14 ## 6   RNA multiplex/RNA/RNA_GENIE3.tsv 4.176625e-05 ATF2    ATAT1 target_genes <- define_target_genes(   hummus,   multilayer_f = \"chen_multilayer\",   njobs = 1   ) ## multiplexes_list :  {'TF': {'TF_network': '00'}, 'RNA': {'RNA_GENIE3': '01'}, 'peaks': {'peak_network_cicero': '01'}} ## bipartites_list :  {'tf_peak.tsv': {'multiplex_right': 'TF', 'multiplex_left': 'peaks'}, 'atac_rna.tsv': {'multiplex_right': 'peaks', 'multiplex_left': 'RNA'}} ## folder_multiplexes :  multiplex ## folder_bipartites :  bipartite ## gene_list :  None ## tf_list :  None ## peak_list :  None ## config_filename :  target_genes_config.yml ## config_folder :  config ## tf_multiplex :  TF ## peak_multiplex :  peaks ## rna_multiplex :  RNA ## update_config :  True ## save :  False ## return_df :  True ## output_f :  None ## njobs :  1 ## {'TF': {'TF_network': '00'}, 'RNA': {'RNA_GENIE3': '01'}, 'peaks': {'peak_network_cicero': '01'}} ## bipartites_type has been provided throguh a list, make sure the order matches the one of the 'bipartites' dictionary' keys. head(target_genes) ##   layer                   path_layer        score   tf     gene ## 1   RNA multiplex/RNA/RNA_GENIE3.tsv 0.0002318538 CUX1   CHRNB1 ## 2   RNA multiplex/RNA/RNA_GENIE3.tsv 0.0002298631 CUX1    CDC5L ## 3   RNA multiplex/RNA/RNA_GENIE3.tsv 0.0002217500 CUX1    ALG11 ## 4   RNA multiplex/RNA/RNA_GENIE3.tsv 0.0002211191 CUX1    CDCA5 ## 5   RNA multiplex/RNA/RNA_GENIE3.tsv 0.0002201935 CUX1    AGBL5 ## 6   RNA multiplex/RNA/RNA_GENIE3.tsv 0.0001498122 BPTF CDC42SE1"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"define-grn","dir":"Articles","previous_headings":"General description of the pipeline > 3. Analyse of the multilayer and definition of GRN","what":"3.3. Define GRN","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"GRN defined using multixrank algorithm. requires hummuspy python package installed (pip install hummuspy). can parallelised using njobs argument. can also specify list genes list TFs use.","code":"grn <- define_grn(   hummus,   multilayer_f = \"chen_multilayer\",   njobs = 1   ) head(grn)"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"retrieve-enhancers","dir":"Articles","previous_headings":"General description of the pipeline > 3. Analyse of the multilayer and definition of GRN","what":"3.4. Retrieve enhancers","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"can also specify list peaks use.","code":"enhancers <- define_enhancers(   hummus,   gene_list = list(\"ATF2\"),   multilayer_f = \"chen_multilayer\",   njobs = 1   ) ## multiplexes_list :  {'TF': {'TF_network': '00'}, 'RNA': {'RNA_GENIE3': '01'}, 'peaks': {'peak_network_cicero': '01'}} ## bipartites_list :  {'tf_peak.tsv': {'multiplex_right': 'TF', 'multiplex_left': 'peaks'}, 'atac_rna.tsv': {'multiplex_right': 'peaks', 'multiplex_left': 'RNA'}} ## folder_multiplexes :  multiplex ## folder_bipartites :  bipartite ## gene_list :  ['ATF2'] ## tf_list :  None ## peak_list :  None ## config_filename :  enhancers_config.yml ## config_folder :  config ## tf_multiplex :  TF ## peak_multiplex :  peaks ## rna_multiplex :  RNA ## update_config :  True ## save :  False ## return_df :  True ## output_f :  None ## njobs :  1 ## {'TF': {'TF_network': '00'}, 'RNA': {'RNA_GENIE3': '01'}, 'peaks': {'peak_network_cicero': '01'}} ## bipartites_type has been provided throguh a list, make sure the order matches the one of the 'bipartites' dictionary' keys. head(enhancers) ##   layer                              path_layer        score gene ## 1 peaks multiplex/peaks/peak_network_cicero.tsv 0.0008960582 ATF2 ## 2 peaks multiplex/peaks/peak_network_cicero.tsv 0.0007440111 ATF2 ## 3 peaks multiplex/peaks/peak_network_cicero.tsv 0.0006710919 ATF2 ## 4 peaks multiplex/peaks/peak_network_cicero.tsv 0.0004391423 ATF2 ## 5 peaks multiplex/peaks/peak_network_cicero.tsv 0.0004031270 ATF2 ## 6 peaks multiplex/peaks/peak_network_cicero.tsv 0.0003824837 ATF2 ##                       peak ## 1   chr6-44387360-44388305 ## 2 chr3-107522766-107524070 ## 3 chr7-102125135-102125606 ## 4   chr7-73738654-73739271 ## 5  chr10-73874242-73875104 ## 6  chr16-67561885-67563510"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"retrieve-binding-regions","dir":"Articles","previous_headings":"General description of the pipeline > 3. Analyse of the multilayer and definition of GRN","what":"3.5. Retrieve binding regions","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"binding regions output, can specify list TFs (tf_list) use seed (NULL default, TFs used seed). links seed TFs peaks computed. can also specify list peaks use. score peaks present network peak_list returned.","code":"binding_regions <- define_binding_regions(   hummus,   multilayer_f = \"chen_multilayer\",   njobs = 1   ) ## multiplexes_list :  {'TF': {'TF_network': '00'}, 'RNA': {'RNA_GENIE3': '01'}, 'peaks': {'peak_network_cicero': '01'}} ## bipartites_list :  {'tf_peak.tsv': {'multiplex_right': 'TF', 'multiplex_left': 'peaks'}, 'atac_rna.tsv': {'multiplex_right': 'peaks', 'multiplex_left': 'RNA'}} ## folder_multiplexes :  multiplex ## folder_bipartites :  bipartite ## gene_list :  None ## tf_list :  None ## peak_list :  None ## config_filename :  binding_regions_config.yml ## config_folder :  config ## tf_multiplex :  TF ## peak_multiplex :  peaks ## rna_multiplex :  RNA ## update_config :  True ## save :  False ## return_df :  True ## output_f :  None ## njobs :  1 ## {'TF': {'TF_network': '00'}, 'RNA': {'RNA_GENIE3': '01'}, 'peaks': {'peak_network_cicero': '01'}} ## bipartites_type has been provided throguh a list, make sure the order matches the one of the 'bipartites' dictionary' keys. head(binding_regions) ##   layer                              path_layer       score   tf ## 1 peaks multiplex/peaks/peak_network_cicero.tsv 0.001680402 CUX1 ## 2 peaks multiplex/peaks/peak_network_cicero.tsv 0.001675393 CUX1 ## 3 peaks multiplex/peaks/peak_network_cicero.tsv 0.001674121 CUX1 ## 4 peaks multiplex/peaks/peak_network_cicero.tsv 0.001559648 CUX1 ## 5 peaks multiplex/peaks/peak_network_cicero.tsv 0.001502478 CUX1 ## 6 peaks multiplex/peaks/peak_network_cicero.tsv 0.001502093 CUX1 ##                       peak ## 1   chr1-65002512-65003322 ## 2   chrX-48971714-48972653 ## 3   chr1-65419692-65420979 ## 4   chrX-48918888-48919598 ## 5   chr8-24955892-24956818 ## 6 chr2-201642365-201643651"},{"path":"https://cantinilab.github.io/HuMMuS/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Rémi Trimbour. Author, maintainer.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Trimbour R (2024). HuMMuS: Heterogeneous Multilayer Network Multi-Omics Single-Cell Data. R package version 0.0.2, https://cantinilab.github.io/HuMMuS/.","code":"@Manual{,   title = {HuMMuS: Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data},   author = {Rémi Trimbour},   year = {2024},   note = {R package version 0.0.2},   url = {https://cantinilab.github.io/HuMMuS/}, }"},{"path":[]},{"path":"https://cantinilab.github.io/HuMMuS/index.html","id":"heterogeneous-multilayer-network-for-multi-omics-single-cell-data","dir":"","previous_headings":"","what":"Heterogeneous Multilayer network for Multi-omics Single-cell data","title":"Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data","text":"HuMMuS exploits multi-omics single-cell measurements infer numerous regulatory mechanisms. Inter-omics (e.g. peak-gene, TF-peak) intra-omics interactions (e.g. peak-peak, gene-gene, TF-TF) considered capture regulatory interactions macromolecule cooperations.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/index.html","id":"overview","dir":"","previous_headings":"","what":"Overview","title":"Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data","text":"current outputs available HuMMuS gene regulatory networks (GRNs) enhancers TF - DNA binding regions TF - target genes.","code":""},{"path":[]},{"path":"https://cantinilab.github.io/HuMMuS/index.html","id":"scrna--scatac","dir":"","previous_headings":"Overview","what":"scRNA + scATAC","title":"Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data","text":"Like current state---art methods infer GRN, propose minimal version HuMMuS based scRNA-seq + scATAC-seq data (paired unpaired).","code":""},{"path":"https://cantinilab.github.io/HuMMuS/index.html","id":"use-of-additional-modalities","dir":"","previous_headings":"Overview","what":"Use of additional modalities","title":"Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data","text":"HuMMuS developed extendable additional biological modality interest. possible add additional network already existing modality (e.g. prior-knowledge network data-driven network genes), new modality (e.g. adding epigenetic proteomic networks). now, personalisation requires use directly hummuspy (python package) functions end pipeline write configuration files manually. simplified soon !","code":""},{"path":"https://cantinilab.github.io/HuMMuS/index.html","id":"tutorialsvignettes","dir":"","previous_headings":"","what":"Tutorials/Vignettes","title":"Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data","text":"Infer gene regulatory network outputs unpaired/paired scRNA+scATAC data shows application HuMMuS Chen dataset, used benchmark HuMMuS publication.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data","text":"HuMMuS now ready R requires python dependencies (hummuspy).","code":""},{"path":"https://cantinilab.github.io/HuMMuS/index.html","id":"hummus-python-dependency","dir":"","previous_headings":"Installation","what":"HuMMuS python dependency","title":"Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data","text":"Python package hummuspy preferably installed using pip (terminal conda environment e.g) Alternatively, can also install directly R using reticulate package:","code":"conda create -n hummuspy_env python conda activate hummuspy_env pip install hummuspy library(reticulate) py_install(\"hummuspy\", envname = \"r-reticulate\", method=\"auto\")"},{"path":"https://cantinilab.github.io/HuMMuS/index.html","id":"hummus-r-package","dir":"","previous_headings":"Installation","what":"HuMMuS R package","title":"Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data","text":"Core R package can installed directly R: running HuMMuS, ’re using multiple conda environment need make sure reticulate points toward one hummuspy installed. can precise beginning code : details setup reticulate connection, see: https://rstudio.github.io/reticulate","code":"devtools::install_github(\"cantinilab/HuMMuS\") library(reticulate) # Using a specific conda environment envname = \"hummuspy_env\" # or \"r-reticulate\" for e.g. use_condaenv(envname, required = TRUE)"},{"path":"https://cantinilab.github.io/HuMMuS/index.html","id":"scatac-processing","dir":"","previous_headings":"Installation","what":"scATAC processing","title":"Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data","text":"compute directly scATAC data HuMMuS, currently propose use Cicero. requires version running Monocle3. need install Monocle3, Cicero: encounter troubles Monocle3 installation, ubuntu can try run: sudo apt-get install libgdal-dev libgeos-dev libproj-dev. can also go github page help. previous version Monocle (1 2) still R session can cause troubles. encounter even restarting R session,, try remove.packages(\"monocle\") reinstall Monocle3 Cicero","code":"devtools::install_github(\"cole-trapnell-lab/monocle3\") devtools::install_github(\"cole-trapnell-lab/cicero-release\", ref = \"monocle3\")"},{"path":"https://cantinilab.github.io/HuMMuS/index.html","id":"data-accessibility","dir":"","previous_headings":"","what":"Data accessibility","title":"Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data","text":"reproduce HuMMuS results presented manuscript, preprocessed data accessible  quick tests, Chen dataset preprocessed accessible directly package Seurat object: load(chen_dataset), along subset version load(chen_dataset_subset).","code":""},{"path":"https://cantinilab.github.io/HuMMuS/index.html","id":"cite-us","dir":"","previous_headings":"","what":"Cite us","title":"Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data","text":"Trimbour R., Deutschmann . M., Cantini L. Molecular mechanisms reconstruction single-cell multi-omics data HuMMuS. Bioinformatics (2024), btae143. doi: https://doi.org/10.1093/bioinformatics/btae143","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/DefaultAssay.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Default assays of Hummus_Object (based on Seurat) — DefaultAssay","title":"Get Default assays of Hummus_Object (based on Seurat) — DefaultAssay","text":"Get set default assay","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/DefaultAssay.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Default assays of Hummus_Object (based on Seurat) — DefaultAssay","text":"","code":"# S3 method for Hummus_Object DefaultAssay(object, ...)  DefaultAssay(object, ...)  DefaultAssay(object, ...) <- value"},{"path":"https://cantinilab.github.io/HuMMuS/reference/DefaultAssay.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Default assays of Hummus_Object (based on Seurat) — DefaultAssay","text":"object object value Name assay set default","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/DefaultAssay.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Default assays of Hummus_Object (based on Seurat) — DefaultAssay","text":"DefaultAssay: name default assay DefaultAssay<-: object default assay updated","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/DefaultAssay.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Default assays of Hummus_Object (based on Seurat) — DefaultAssay","text":"","code":"# Get current default assay DefaultAssay(object = pbmc_small) #> Error in eval(expr, envir, enclos): object 'pbmc_small' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/Hummus_Object-class.html","id":null,"dir":"Reference","previous_headings":"","what":"The Hummus_Object class — Hummus_Object-class","title":"The Hummus_Object class — Hummus_Object-class","text":"Hummus_Object object extended Seurat object storage analysis heterogeneous multilayer network","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/Hummus_Object-class.html","id":"slots","dir":"Reference","previous_headings":"","what":"Slots","title":"The Hummus_Object class — Hummus_Object-class","text":"multilayer (multilayer) - Multilayer object motifs_db (motifs_db) - Motifs database assay (list) - List assays","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/Initiate_Hummus_Object.html","id":null,"dir":"Reference","previous_headings":"","what":"Initiate a hummus object — Initiate_Hummus_Object","title":"Initiate a hummus object — Initiate_Hummus_Object","text":"Initiate hummus object","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/Initiate_Hummus_Object.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Initiate a hummus object — Initiate_Hummus_Object","text":"","code":"Initiate_Hummus_Object(   seurat_assays,   active.assay = NULL,   multilayer = NULL,   motifs_db = NULL )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/Initiate_Hummus_Object.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Initiate a hummus object — Initiate_Hummus_Object","text":"seurat_assays Seurat object list Seurat assays active.assay name active assay. Default: NULL multilayer multilayer object. Default: NULL motifs_db motifs_db object. Default: NULL","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/Initiate_Hummus_Object.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Initiate a hummus object — Initiate_Hummus_Object","text":"hummus object","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/Initiate_Hummus_Object.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Initiate a hummus object — Initiate_Hummus_Object","text":"","code":"seurat_object <- Seurat::CreateSeuratObject(counts = matrix(rnorm(1000), nrow = 100, ncol = 10)) #> Error in loadNamespace(x): there is no package called ‘Seurat’          hummus <- InitiateHummus_Object(seurat_object) #> Error in InitiateHummus_Object(seurat_object): could not find function \"InitiateHummus_Object\"          hummus #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/VariableFeatures.html","id":null,"dir":"Reference","previous_headings":"","what":"Variable features of assays in Hummus_Object (based on Seurat) — VariableFeatures","title":"Variable features of assays in Hummus_Object (based on Seurat) — VariableFeatures","text":"Variable features assays Hummus_Object (based Seurat)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/VariableFeatures.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Variable features of assays in Hummus_Object (based on Seurat) — VariableFeatures","text":"","code":"# S3 method for Hummus_Object VariableFeatures(   object,   method = NULL,   assay = NULL,   nfeatures = NULL,   layer = NA,   simplify = TRUE,   selection.method = lifecycle::deprecated(),   ... )  VariableFeatures(object, method = NULL, ...)  VariableFeatures(object, ...) <- value"},{"path":"https://cantinilab.github.io/HuMMuS/reference/VariableFeatures.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Variable features of assays in Hummus_Object (based on Seurat) — VariableFeatures","text":"value character vector variable features","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/VariableFeatures.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Variable features of assays in Hummus_Object (based on Seurat) — VariableFeatures","text":"VariableFeatures: vector variable features","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/add_network.html","id":null,"dir":"Reference","previous_headings":"","what":"Add a network to a multiplex, a multilayer or an hummus object — add_network","title":"Add a network to a multiplex, a multilayer or an hummus object — add_network","text":"Add network multiplex, multilayer hummus object","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/add_network.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add a network to a multiplex, a multilayer or an hummus object — add_network","text":"","code":"add_network(   object,   network,   network_name,   multiplex_name = NULL,   directed = FALSE,   weighted = FALSE,   verbose = 1 )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/add_network.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add a network to a multiplex, a multilayer or an hummus object — add_network","text":"object multiplex, multilayer hummus object network network (edge list) network_name name network multiplex_name name multiplex. Default: NULL object multiplex already directed Logical indicating network directed. Default: FALSE weighted Logical indicating network weighted. Default: FALSE verbose (integer) - Display function messages. Set 0 message displayed, >= 1 details.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/add_network.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add a network to a multiplex, a multilayer or an hummus object — add_network","text":"multiplex, multilayer hummus object added network","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/add_network.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add a network to a multiplex, a multilayer or an hummus object — add_network","text":"","code":"hummus <- add_network(                            object = hummus,                            network = atac_peak_network,                            network_name = network_name,                            multiplex_name = multiplex_name,                            weighted = TRUE,                            directed = FALSE) #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/aggregate_matrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Aggregate matrix over groups — aggregate_matrix","title":"Aggregate matrix over groups — aggregate_matrix","text":"Aggregate matrix groups","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/aggregate_matrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Aggregate matrix over groups — aggregate_matrix","text":"","code":"aggregate_matrix(x, groups = NULL, fun = \"mean\")"},{"path":"https://cantinilab.github.io/HuMMuS/reference/aggregate_matrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Aggregate matrix over groups — aggregate_matrix","text":"groups character vector groups aggregate . fun summary function applied group.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/aggregate_matrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Aggregate matrix over groups — aggregate_matrix","text":"summary matrix.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite-class.html","id":null,"dir":"Reference","previous_headings":"","what":"Bipartite class — bipartite-class","title":"Bipartite class — bipartite-class","text":"Bipartite object stores bipartite network (edge list) names left right features' multiplexes.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite-class.html","id":"slots","dir":"Reference","previous_headings":"","what":"Slots","title":"Bipartite class — bipartite-class","text":"network (data.frame) - Bipartite network (edge list) multiplex_left (character) - Left features' multiplex multiplex_right (character) - Right features' multiplex","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite-class.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Bipartite class — bipartite-class","text":"","code":"bipartite <- bipartite(                           network = bipartite_network,                          multiplex_left = \"RNA\",                         multiplex_right = \"peaks\") #> Error in bipartite(network = bipartite_network, multiplex_left = \"RNA\",     multiplex_right = \"peaks\"): could not find function \"bipartite\""},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite_peaks2genes.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute links between DNA regions and genenames — bipartite_peaks2genes","title":"Compute links between DNA regions and genenames — bipartite_peaks2genes","text":"Compute add bipartite DNA regions genenames hummus object. Links computed based distance peaks gene's TSS location gene.range annotations. Call find_peaks_near_genes function, can use different methods.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite_peaks2genes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute links between DNA regions and genenames — bipartite_peaks2genes","text":"","code":"bipartite_peaks2genes(   hummus_object,   gene_assay = \"RNA\",   peak_assay = \"peaks\",   gene_multiplex_name = NULL,   peak_multiplex_name = NULL,   peak_to_gene_method = \"Signac\",   upstream = 500,   downstream = 500,   only_tss = TRUE,   store_network = FALSE,   output_file = NULL,   bipartite_name = \"atac_rna\" )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite_peaks2genes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute links between DNA regions and genenames — bipartite_peaks2genes","text":"hummus_object (hummus_object) - Hummus object. gene_assay (character) - Name assay containing gene expression data. Default: \"RNA\". peak_assay (character) - Name assay containing DNA regions (ATAC peaks). Default: \"peaks\". gene_multiplex_name (character) - Name multiplex containing genes. NULL, name gene assay used. peak_multiplex_name (character) - Name multiplex containing DNA regions (ATAC peaks). NULL, name peak assay used. peak_to_gene_method (character) - Method use compute links peaks genes. Default: \"Signac\". 'Signac' - Use Signac::Extend extend genes. 'GREAT' - implemented yet. upstream (int) - Upstream distance TSS consider potential promoter. downstream (int) - Downstream distance TSS consider potential promoter. only_tss (logical) - TRUE, TSS considered. store_network (bool) - Save bipartite directly (TRUE, default) return without saving disk (FALSE). output_file (character) - Name output_file (store_bipartite == TRUE). Default: NULL. bipartite_name (character) - Name bipartite. Default: \"atac_rna\". verbose (integer) Display function messages. Set 0 message displayed, >= 1 details. Default: 1.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite_peaks2genes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute links between DNA regions and genenames — bipartite_peaks2genes","text":"hummus_object (hummus_object) - Hummus object w/ atac-rna bipartite added multilayer slot","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite_peaks2genes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute links between DNA regions and genenames — bipartite_peaks2genes","text":"","code":"hummus <- bipartite_peaks2genes(                        hummus_object = hummus,                        gene_assay = \"RNA\",                        peak_assay = \"peaks\",                        gene_multiplex_name = \"RNA\",                        peak_multiplex_name = \"peaks\",                        peak_to_gene_method = \"Signac\",                        upstream = 500,                        downstream = 500,                        only_tss = TRUE,                        store_network = FALSE,                        bipartite_name = \"atac_rna\") #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite_tfs2peaks.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute links between TFs and DNA regions (ATAC peaks) — bipartite_tfs2peaks","title":"Compute links between TFs and DNA regions (ATAC peaks) — bipartite_tfs2peaks","text":"Compute add bipartite TFs DNA regions hummus object. Links computed based binding motifs TFs locations reference genome. Currently based Signac AddMotifs function (--> motifmachR, based MOODs algorithm).","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite_tfs2peaks.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute links between TFs and DNA regions (ATAC peaks) — bipartite_tfs2peaks","text":"","code":"bipartite_tfs2peaks(   hummus_object,   tf_expr_assay = \"RNA\",   peak_assay = \"peaks\",   tf_multiplex_name = NULL,   peak_multiplex_name = NULL,   genome,   store_network = FALSE,   output_file = NULL,   verbose = 1,   bipartite_name = \"tf_peak\" )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite_tfs2peaks.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute links between TFs and DNA regions (ATAC peaks) — bipartite_tfs2peaks","text":"hummus_object (hummus_object) - Hummus object. tf_expr_assay (character) - Name assay containing TF expression data. NULL, TFs motif used. Default: \"RNA\". peak_assay (character) - Name assay containing DNA regions (ATAC peaks). Default: \"peaks\". tf_multiplex_name (character) - Name multiplex containing TFs. NULL, name TF assay used. peak_multiplex_name (character) - Name multiplex containing DNA regions (ATAC peaks). NULL, name peak assay used. genome (BSgenome object) - Reference genome. store_network (bool) - Save bipartite directly (TRUE, default) return without saving disk (FALSE). output_file (character) - Name output_file (store_bipartite == TRUE). Default: NULL. verbose (integer) Display function messages. Set 0 message displayed, >= 1 details. Default: 1. bipartite_name (character) - Name bipartite. Default: \"tf_peak\".","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite_tfs2peaks.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute links between TFs and DNA regions (ATAC peaks) — bipartite_tfs2peaks","text":"hummus_object (hummus_object) - Hummus object TF-peak bipartite added multilayer slot","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite_tfs2peaks.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute links between TFs and DNA regions (ATAC peaks) — bipartite_tfs2peaks","text":"","code":"hummus <- bipartite_tfs2peaks(                      hummus_object = hummus,                      tf_expr_assay = \"RNA\",                      peak_assay = \"peaks\",                      tf_multiplex_name = \"TF\",                      peak_multiplex_name = \"peaks\",           genome = BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38,                      store_network = FALSE,                      verbose = 1,                      bipartite_name = \"tf_peak\") #> Computing TF-peak bipartite #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_atac_peak_network.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute peak network from scATAC-seq data — compute_atac_peak_network","title":"Compute peak network from scATAC-seq data — compute_atac_peak_network","text":"function create network atac data (theory data wtih peaks coordinates features). Different method implemented point (e.g. RENIN), now Cicero still reference method available","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_atac_peak_network.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute peak network from scATAC-seq data — compute_atac_peak_network","text":"","code":"compute_atac_peak_network(   hummus,   atac_assay = \"peaks\",   genome = BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38,   method = \"cicero\",   multiplex_name = NULL,   network_name = NULL,   store_network = FALSE,   output_file = NULL,   threshold = 0,   number_cells_per_clusters = 50,   sample_num = 100,   seed = 2025,   verbose = 1,   window = 5e+05,   reduction_method = \"UMAP\" )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_atac_peak_network.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute peak network from scATAC-seq data — compute_atac_peak_network","text":"hummus (hummus_object) - Hummus object atac_assay (character) - Name assay containing atac peaks data. genome (BSgenome) - Genome used compute distance peaks. method (character) - Method used infer network edges. 'cicero' - Use cicero infer regulatory networks. 'method' - . multiplex_name (character) - Name multiplex add network . Default 'peaks'. network_name (character) - Name network multiplex add network . Default 'peak_network'. store_network (bool) - Save network directly (TRUE, default) return without saving disk (FALSE). output_file (character) - Name output_file (store_network == TRUE). threshold (interger, default 0) - Minimal threshold select tf-gene edges. number_cells_per_clusters (integer) - Number cells grouped territory define pseudocells sample_num (integer | Cicero) - Number pseudocells sample territory. Default 100. seed (integer | Cicero) - Seed used sample pseudocells. Default 2025 verbose (integer) - Display function messages. Set 0 message displayed, >= 1 details. window (integer) - Size window consider potential cis-regulatory cooperations peaks. Default 500K base pairs. reduction_method (character | Cicero) - Method used reduce dimensionality data identify territories. Default 'UMAP'.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_atac_peak_network.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute peak network from scATAC-seq data — compute_atac_peak_network","text":"(data.frame) - Return list network interactions peaks","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_atac_peak_network.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Compute peak network from scATAC-seq data — compute_atac_peak_network","text":"Method descriptions : Cicero Use patial corelation peaks given window (e.g. : less distant 500K base pairs)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_atac_peak_network.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute peak network from scATAC-seq data — compute_atac_peak_network","text":"","code":"hummus <- compute_atac_peak_network(hummus) #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_gene_network.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute gene netwok from scRNA-seq data — compute_gene_network","title":"Compute gene netwok from scRNA-seq data — compute_gene_network","text":"function create network rna data (theory data wtih genes features). Different method implemented point (suggestion welcomed ! :) ), now Genie3 still reference method available","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_gene_network.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute gene netwok from scRNA-seq data — compute_gene_network","text":"","code":"compute_gene_network(   hummus,   gene_assay = \"RNA\",   tfs = NULL,   method = \"GENIE3\",   multiplex_name = NULL,   network_name = NULL,   store_network = FALSE,   output_file = NULL,   threshold = 0,   number_cores = 1,   verbose = 1 )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_gene_network.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute gene netwok from scRNA-seq data — compute_gene_network","text":"hummus (hummus_object) - Hummus object gene_assay (character) - Name assay containing gene expression data. tfs vector(character) - List tfs considered. NULL, TFs motifs hummus object used. method (character) - Method used infer network edges. 'Genie3' - Use tree random forest infer regulatory networks. 'method' - . multiplex_name (character) - Name multiplex add network . Default 'RNA'. network_name (character) - Name network multiplex add network . Default 'RNA_network'. store_network (bool) - Save network directly (TRUE, default) return without saving disk (FALSE). output_file (character) - Name output_file (store_network == TRUE). threshold (interger, default 0) - Minimal threshold select tf-gene edges. number_cores (interger, default 1) - Number thread used parallelizable methods. verbose (integer) - Display function messages. Set 0 message displayed, >= 1 details.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_gene_network.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute gene netwok from scRNA-seq data — compute_gene_network","text":"(data.frame) - Return list network interactions genes","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_gene_network.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Compute gene netwok from scRNA-seq data — compute_gene_network","text":"Method descriptions : Genie3 Use tree random forest infer regulatory networks : https://bioconductor.org/packages/release/bioc/html/GENIE3.html","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_gene_network.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute gene netwok from scRNA-seq data — compute_gene_network","text":"","code":"hummus <- compute_gene_network(                                hummus,                                gene_assay = \"RNA\",                                method = \"GENIE3\",                                verbose = 1,                                number_cores = 8,                                store_network = FALSE) #> Computing gene network with  GENIE3  ... #> \tNo TFs list provided, fetching from hummus object... #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_tf_network.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute TF network and add it to hummus object — compute_tf_network","title":"Compute TF network and add it to hummus object — compute_tf_network","text":"Compute protein-protein interaction layer Omnipath request represent tf cooperativity. network top-layer HuMMuS multilayer.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_tf_network.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute TF network and add it to hummus object — compute_tf_network","text":"","code":"compute_tf_network(   hummus,   organism = 9606,   tfs = NA,   gene_assay = NULL,   method = NULL,   store_network = FALSE,   output_file = NULL,   source_target = \"AND\",   multiplex_name = \"TF\",   tf_network_name = \"TF_network\",   verbose = 1 )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_tf_network.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute TF network and add it to hummus object — compute_tf_network","text":"hummus (hummus_object) - Hummus object organism (integer)  - Specie identifier Omnipath fetch specific interactions tfs vector(character) - List tfs consider. NA, tfs extracted hummus object get_tfs function. gene_assay (character) - Name assay get tfs tfs provided. NULL, TFs motifs hummus object used. method (character) - Method used infer network edges. 'Omnipath' - Use Omnipath infer tf-tf networks. 'NULL' - fake connected network computed. 'method' - . store_network (bool) - Save network directly (TRUE, default) return without saving disk (FALSE). output_file (character) - Name output_file (store_network == TRUE). source_target (''|'') - Fetch interactions involving two considered tfs ('', default), one considered tfs element ('') multiplex_name (character) - Name multiplex add network . Default 'TF'. tf_network_name (character) - Name network multiplex add network . Default 'TF_network'. verbose (integer) - Display function messages. Set 0 message displayed, >= 1 details.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_tf_network.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute TF network and add it to hummus object — compute_tf_network","text":"(hummus_object) - Return hummus object new network added.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_tf_network.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute TF network and add it to hummus object — compute_tf_network","text":"","code":"hummus <- compute_tf_network(hummus,                                        gene_assay = \"RNA\",                                        verbose = 1) #> Creating a fake TF network with all TFs connected to a fake node. #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/dMcast.html","id":null,"dir":"Reference","previous_headings":"","what":"Copy of the dMcast function from the Matrix.utils package, since this is off CRAN and does not seem to be maintained anymore internally — dMcast","title":"Copy of the dMcast function from the Matrix.utils package, since this is off CRAN and does not seem to be maintained anymore internally — dMcast","text":"Copy dMcast function Matrix.utils package, since CRAN seem maintained anymore internally","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/dMcast.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Copy of the dMcast function from the Matrix.utils package, since this is off CRAN and does not seem to be maintained anymore internally — dMcast","text":"","code":"dMcast(   data,   formula,   fun.aggregate = \"sum\",   value.var = NULL,   as.factors = FALSE,   factor.nas = TRUE,   drop.unused.levels = TRUE )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_binding_regions.html","id":null,"dir":"Reference","previous_headings":"","what":"Define binding_regions from hummus object — define_binding_regions","title":"Define binding_regions from hummus object — define_binding_regions","text":"Calling define_output function output_type = 'binding_regions'","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_binding_regions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Define binding_regions from hummus object — define_binding_regions","text":"","code":"define_binding_regions(   hummus_object,   multiplex_names = NULL,   bipartites_names = NULL,   config_name = \"binding_regions_config.yml\",   config_folder = \"config\",   tf_multiplex = \"TF\",   atac_multiplex = \"peaks\",   rna_multiplex = \"RNA\",   multilayer_f = \"multilayer\",   gene_list = NULL,   tf_list = NULL,   save = FALSE,   output_f = NULL,   return_df = TRUE,   suffix_bipartites = \".tsv\",   njobs = 1 )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_binding_regions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Define binding_regions from hummus object — define_binding_regions","text":"hummus_object hummus object multiplex_names vector multiplex names considered. must subset names multiplexes hummus object. bipartites_names vector bipartites names considered. must subset names bipartites hummus object. config_name name config file created hummuspy config_folder folder config file created tf_multiplex name multiplex containing TFs atac_multiplex name multiplex containing ATAC-seq peaks rna_multiplex name multiplex containing RNA-seq genes multilayer_f folder multilayer stored gene_list vector genes considered final binding regions (filtering done genes inferring binding_regions) tf_list vector TFs considered binding_regions (filtering done TFs inferring binding_regions) save boolean indicating binding_regions saved output_f name file binding_regions can saved (save == TRUE) return_df boolean indicating binding_regions returned dataframe suffix_bipartites suffix add bipartites names (indicate exact file location) njobs number jobs used computation binding_regions","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_binding_regions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Define binding_regions from hummus object — define_binding_regions","text":"dataframe containing binding_regions (return_df == TRUE)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_binding_regions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Define binding_regions from hummus object — define_binding_regions","text":"","code":"binding_regions <- define_binding_regions(hummus_object = hummus,                             multilayer_f = multilayer_folder,                             njobs = 5) #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_enhancers.html","id":null,"dir":"Reference","previous_headings":"","what":"Define enhancers from hummus object — define_enhancers","title":"Define enhancers from hummus object — define_enhancers","text":"Calling define_output function output_type = 'enhancers'","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_enhancers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Define enhancers from hummus object — define_enhancers","text":"","code":"define_enhancers(   hummus_object,   multiplex_names = NULL,   bipartites_names = NULL,   config_name = \"enhancers_config.yml\",   config_folder = \"config\",   tf_multiplex = \"TF\",   atac_multiplex = \"peaks\",   rna_multiplex = \"RNA\",   multilayer_f = \"multilayer\",   gene_list = NULL,   tf_list = NULL,   save = FALSE,   output_f = NULL,   return_df = TRUE,   suffix_bipartites = \".tsv\",   njobs = 1 )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_enhancers.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Define enhancers from hummus object — define_enhancers","text":"hummus_object hummus object multiplex_names vector multiplex names considered. must subset names multiplexes hummus object. bipartites_names vector bipartites names considered. must subset names bipartites hummus object. config_name name config file created hummuspy config_folder folder config file created tf_multiplex name multiplex containing TFs atac_multiplex name multiplex containing ATAC-seq peaks rna_multiplex name multiplex containing RNA-seq genes multilayer_f folder multilayer stored gene_list vector genes considered final enhancers (filtering done genes inferring enhancers) tf_list vector TFs considered final enhancers (filtering done TFs inferring enhancers) save boolean indicating enhancers saved output_f name file enhancers saved (save == TRUE) return_df boolean indicating enhancers returned dataframe suffix_bipartites suffix add bipartites names (indicate exact file location) njobs number jobs used compute enhancers","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_enhancers.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Define enhancers from hummus object — define_enhancers","text":"dataframe containing enhancers (return_df == TRUE)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_enhancers.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Define enhancers from hummus object — define_enhancers","text":"","code":"enhancers <- define_enhancers(hummus_object = hummus,                             multilayer_f = multilayer_folder,                             njobs = 5) #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_general_config.html","id":null,"dir":"Reference","previous_headings":"","what":"Define general config file for hummuspy — define_general_config","title":"Define general config file for hummuspy — define_general_config","text":"Define general config file hummuspy","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_general_config.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Define general config file for hummuspy — define_general_config","text":"","code":"define_general_config(   hummus_object,   multiplex_names = NULL,   bipartites_names = NULL,   folder_multiplexes = \"multiplex\",   folder_bipartites = \"bipartites\",   seed_path = \"seed/seeds.txt\",   suffix = \".tsv\",   self_loops = FALSE,   restart_proba = 0.7,   save_configfile = FALSE,   config_name = \"config.yml\",   config_folder = \"config\",   multilayer_f = \"multilayer\",   suffix_bipartites = \".tsv\" )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_general_config.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Define general config file for hummuspy — define_general_config","text":"hummus_object hummus object multiplex_names vector multiplex names considered. must subset names multiplexes hummus object, NULL multiplexes considered. bipartites_names vector bipartites names considered. must subset names bipartites hummus object, NULL bipartites considered. folder_multiplexes folder multiplexes stored folder_bipartites folder bipartites stored seed_path path seed file self_loops boolean indicating self loops considered. restart_proba restart probability random walk (default = 0.7) save_configfile boolean indicating config file saved config_name name config file created hummuspy config_folder folder config file created (inside multilayer_f) multilayer_f folder multilayer stored suffix_bipartites suffix add bipartites names (indicate exact file name)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_general_config.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Define general config file for hummuspy — define_general_config","text":"config file hummuspy","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_grn.html","id":null,"dir":"Reference","previous_headings":"","what":"Define GRN from hummus object — define_grn","title":"Define GRN from hummus object — define_grn","text":"Calling define_output function output_type = 'GRN'","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_grn.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Define GRN from hummus object — define_grn","text":"","code":"define_grn(   hummus_object,   multiplex_names = NULL,   bipartites_names = NULL,   config_name = \"grn_config.yml\",   config_folder = \"config\",   tf_multiplex = \"TF\",   atac_multiplex = \"peaks\",   rna_multiplex = \"RNA\",   multilayer_f = \"multilayer\",   gene_list = NULL,   tf_list = NULL,   save = FALSE,   output_f = NULL,   return_df = TRUE,   suffix_bipartites = \".tsv\",   njobs = 1 )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_grn.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Define GRN from hummus object — define_grn","text":"hummus_object hummus object multiplex_names vector multiplex names considered. must subset names multiplexes hummus object. bipartites_names vector bipartites names considered. must subset names bipartites hummus object. config_name name config file created hummuspy config_folder folder config file created tf_multiplex name multiplex containing TFs atac_multiplex name multiplex containing ATAC-seq peaks rna_multiplex name multiplex containing RNA-seq genes multilayer_f folder multilayer stored gene_list vector genes considered final GRN (filtering done genes inferring GRN) tf_list vector TFs considered final GRN (filtering done TFs inferring GRN) save boolean indicating GRN saved output_f name file GRN saved (save == TRUE) return_df boolean indicating GRN returned dataframe suffix_bipartites suffix add bipartites names (indicate exact file location) njobs number jobs used computation GRN","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_grn.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Define GRN from hummus object — define_grn","text":"dataframe containing GRN (return_df == TRUE)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_grn.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Define GRN from hummus object — define_grn","text":"","code":"grn <- define_grn(hummus_object = hummus,                             multilayer_f = multilayer_folder,                             njobs = 5) #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_output.html","id":null,"dir":"Reference","previous_headings":"","what":"Define output from hummus object — define_output","title":"Define output from hummus object — define_output","text":"Define output hummus object","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_output.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Define output from hummus object — define_output","text":"","code":"define_output(   output_type,   hummus_object,   multiplex_names = NULL,   bipartites_names = NULL,   config_name = \"config.yml\",   config_folder = \"config\",   tf_multiplex = \"TF\",   atac_multiplex = \"peaks\",   rna_multiplex = \"RNA\",   multilayer_f = \"multilayer\",   gene_list = NULL,   tf_list = NULL,   save = FALSE,   output_f = NULL,   return_df = TRUE,   suffix_bipartites = \".tsv\",   njobs = 1 )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_output.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Define output from hummus object — define_output","text":"output_type type output defined hummus_object hummus object multiplex_names vector multiplex names considered. must subset names multiplexes hummus object. bipartites_names vector bipartites names considered. must subset names bipartites hummus object. config_name name config file created hummuspy config_folder folder config file created tf_multiplex name multiplex containing TFs atac_multiplex name multiplex containing ATAC-seq peaks rna_multiplex name multiplex containing RNA-seq genes multilayer_f folder multilayer stored gene_list vector genes considered target_genes (filtering done genes inferring target_genes) tf_list vector TFs considered final target_genes (filtering done TFs inferring target_genes) save boolean indicating target_genes saved output_f name file target_genes saved (save == TRUE) return_df boolean indicating target_genes returned dataframe suffix_bipartites suffix add bipartites names (indicate exact file location) njobs number jobs used compute target_genes","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_output.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Define output from hummus object — define_output","text":"dataframe containing target_genes (return_df == TRUE)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_output.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Define output from hummus object — define_output","text":"","code":"target_genes <- define_output('grn', hummus_object = hummus) #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_target_genes.html","id":null,"dir":"Reference","previous_headings":"","what":"Define target genes from hummus object — define_target_genes","title":"Define target genes from hummus object — define_target_genes","text":"Calling define_output function output_type = 'target_genes'","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_target_genes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Define target genes from hummus object — define_target_genes","text":"","code":"define_target_genes(   hummus_object,   multiplex_names = NULL,   bipartites_names = NULL,   config_name = \"target_genes_config.yml\",   config_folder = \"config\",   tf_multiplex = \"TF\",   atac_multiplex = \"peaks\",   rna_multiplex = \"RNA\",   multilayer_f = \"multilayer\",   gene_list = NULL,   tf_list = NULL,   save = FALSE,   output_f = NULL,   return_df = TRUE,   suffix_bipartites = \".tsv\",   njobs = 1 )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_target_genes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Define target genes from hummus object — define_target_genes","text":"hummus_object hummus object multiplex_names vector multiplex names considered. must subset names multiplexes hummus object. bipartites_names vector bipartites names considered. must subset names bipartites hummus object. config_name name config file created hummuspy config_folder folder config file created tf_multiplex name multiplex containing TFs atac_multiplex name multiplex containing ATAC-seq peaks rna_multiplex name multiplex containing RNA-seq genes multilayer_f folder multilayer stored gene_list vector genes considered target_genes (filtering done genes inferring target_genes) tf_list vector TFs considered final target_genes (filtering done TFs inferring target_genes) save boolean indicating target_genes saved output_f name file target_genes saved (save == TRUE) return_df boolean indicating target_genes returned dataframe suffix_bipartites suffix add bipartites names (indicate exact file location) njobs number jobs used compute target_genes","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_target_genes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Define target genes from hummus object — define_target_genes","text":"dataframe containing target_genes (return_df == TRUE)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_target_genes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Define target genes from hummus object — define_target_genes","text":"","code":"target_genes <- define_target_genes(hummus_object = hummus,                             multilayer_f = multilayer_folder,                             njobs = 5) #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/fast_aggregate.html","id":null,"dir":"Reference","previous_headings":"","what":"Copy of the aggregate.Matrix function from the Matrix.utils package, since this is off CRAN and does not seem to be maintained anymore internally — fast_aggregate","title":"Copy of the aggregate.Matrix function from the Matrix.utils package, since this is off CRAN and does not seem to be maintained anymore internally — fast_aggregate","text":"Copy aggregate.Matrix function Matrix.utils package, since CRAN seem maintained anymore internally","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/fast_aggregate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Copy of the aggregate.Matrix function from the Matrix.utils package, since this is off CRAN and does not seem to be maintained anymore internally — fast_aggregate","text":"","code":"fast_aggregate(x, groupings = NULL, form = NULL, fun = \"sum\", ...)"},{"path":"https://cantinilab.github.io/HuMMuS/reference/find_peaks_near_genes.html","id":null,"dir":"Reference","previous_headings":"","what":"Associate peaks to genes based on distance to TSS (or gene body) — find_peaks_near_genes","title":"Associate peaks to genes based on distance to TSS (or gene body) — find_peaks_near_genes","text":"Associate peaks genes based distance TSS (gene body)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/find_peaks_near_genes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Associate peaks to genes based on distance to TSS (or gene body) — find_peaks_near_genes","text":"","code":"find_peaks_near_genes(   peaks,   genes,   sep = c(\"-\", \"-\"),   method = c(\"Signac\", \"GREAT\"),   upstream = 1e+05,   downstream = 0,   extend = 1e+06,   only_tss = FALSE,   verbose = TRUE )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/find_peaks_near_genes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Associate peaks to genes based on distance to TSS (or gene body) — find_peaks_near_genes","text":"peaks vector(character) - List peaks. genes vector(character) - List genes. sep vector(character) - Separator chromosome, start end position. Default: c('-', '-'). method (character) - Method use. Default: \"Signac\". 'Signac' - Use Signac::Extend extend genes. 'GREAT' - implemented yet. upstream (int) - Upstream distance TSS consider potential promoter. downstream (int) - Downstream distance TSS consider potential promoter. extend (int) - Integer defining distance upstream downstream basal regulatory region. Used method 'GREAT'. only_tss (logical) - TRUE, TSS considered. verbose (logical) - TRUE, print progress messages.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/find_peaks_near_genes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Associate peaks to genes based on distance to TSS (or gene body) — find_peaks_near_genes","text":"(matrix) - Matrix peaks x genes 1 peak near gene.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/find_peaks_near_genes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Associate peaks to genes based on distance to TSS (or gene body) — find_peaks_near_genes","text":"","code":"TODO #> Error in eval(expr, envir, enclos): object 'TODO' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/format_bipartites_names.html","id":null,"dir":"Reference","previous_headings":"","what":"Format bipartites names for python hummuspy package config functions — format_bipartites_names","title":"Format bipartites names for python hummuspy package config functions — format_bipartites_names","text":"Format bipartites names python hummuspy package config functions","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/format_bipartites_names.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format bipartites names for python hummuspy package config functions — format_bipartites_names","text":"","code":"format_bipartites_names(   hummus_object,   bipartites_names = NULL,   suffix_bipartites = \".tsv\" )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/format_bipartites_names.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format bipartites names for python hummuspy package config functions — format_bipartites_names","text":"hummus_object hummus object bipartites_names vector bipartites names considered. must subset names bipartites hummus object. suffix_bipartites suffix add bipartites location","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/format_bipartites_names.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format bipartites names for python hummuspy package config functions — format_bipartites_names","text":"list bipartites names formatted hummuspy config funtions element list list containing right left layer connected bipartite","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/format_bipartites_names.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format bipartites names for python hummuspy package config functions — format_bipartites_names","text":"","code":"bipartites_dictionary <- format_bipartites_names(                                       hummus_object = hummus,                                       bipartites_names = c(\"atac_rna\",                                                            \"tf_peaks\")) #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/format_multiplex_names.html","id":null,"dir":"Reference","previous_headings":"","what":"Format multiplex names for python hummuspy package config functions — format_multiplex_names","title":"Format multiplex names for python hummuspy package config functions — format_multiplex_names","text":"Format multiplex names python hummuspy package config functions","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/format_multiplex_names.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format multiplex names for python hummuspy package config functions — format_multiplex_names","text":"","code":"format_multiplex_names(hummus_object, multiplex_names = NULL)"},{"path":"https://cantinilab.github.io/HuMMuS/reference/format_multiplex_names.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format multiplex names for python hummuspy package config functions — format_multiplex_names","text":"hummus_object hummus object multiplex_names vector multiplex names considered. must subset names multiplexes hummus object.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/format_multiplex_names.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format multiplex names for python hummuspy package config functions — format_multiplex_names","text":"list multiplexes names formatted hummuspy config funtions element list list network types (directed/weighted) name networks named hummus object","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/format_multiplex_names.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format multiplex names for python hummuspy package config functions — format_multiplex_names","text":"","code":"multiplexes_dictionary <- format_multiplex_names(                                        hummus_object = hummus,                                        multiplex_names = c(\"TF\", \"peaks\")) #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_genome_annotations.html","id":null,"dir":"Reference","previous_headings":"","what":"Fetch online genome annotations from Ensembldb database — get_genome_annotations","title":"Fetch online genome annotations from Ensembldb database — get_genome_annotations","text":"Fetch online genome annotations Ensembldb database","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_genome_annotations.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fetch online genome annotations from Ensembldb database — get_genome_annotations","text":"","code":"get_genome_annotations(   ensdb_annotations = EnsDb.Hsapiens.v86::EnsDb.Hsapiens.v86 )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_genome_annotations.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fetch online genome annotations from Ensembldb database — get_genome_annotations","text":"EnsDb_annotations (EndsDb object) - Ensembldb database (default: EnsDb.Hsapiens.v86::EnsDb.Hsapiens.v86","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_genome_annotations.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fetch online genome annotations from Ensembldb database — get_genome_annotations","text":"gene_range (GRanges object) - Genome annotations","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_genome_annotations.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fetch online genome annotations from Ensembldb database — get_genome_annotations","text":"","code":"gene_range = get_genome_annotations(EnsDb.Hsapiens.v86::EnsDb.Hsapiens.v86) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.)"},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_tf2motifs.html","id":null,"dir":"Reference","previous_headings":"","what":"Fetch online TF motifs from JASPAR2020 and chromVARmotifs — get_tf2motifs","title":"Fetch online TF motifs from JASPAR2020 and chromVARmotifs — get_tf2motifs","text":"Fetch online TF motifs JASPAR2020 chromVARmotifs","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_tf2motifs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fetch online TF motifs from JASPAR2020 and chromVARmotifs — get_tf2motifs","text":"","code":"get_tf2motifs(species = \"human\")"},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_tf2motifs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fetch online TF motifs from JASPAR2020 and chromVARmotifs — get_tf2motifs","text":"species (character) - Species name (default: \"human\")","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_tf2motifs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fetch online TF motifs from JASPAR2020 and chromVARmotifs — get_tf2motifs","text":"motifs_db (motifs_db object) - TF2motifs + motifs PWMs","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_tf2motifs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fetch online TF motifs from JASPAR2020 and chromVARmotifs — get_tf2motifs","text":"","code":"motifs_db = get_tf2motifs(species = \"human\")"},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_tfs.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract TF names from scRNA data and tf2motifs — get_tfs","title":"Extract TF names from scRNA data and tf2motifs — get_tfs","text":"Extract TF names scRNA data tf2motifs","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_tfs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract TF names from scRNA data and tf2motifs — get_tfs","text":"","code":"get_tfs(   hummus,   assay = NULL,   store_tfs = TRUE,   output_file = NULL,   verbose = 0 )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_tfs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract TF names from scRNA data and tf2motifs — get_tfs","text":"output_file (character) - Path output file. verbose (integer) - Verbosity level. Default: 1. species (character) - Species name. Default: \"human\". genes (vector(character)) - List expressed genes. tf2motifs (data.frame) - TF motifs names mapping. Columns: motif, tf.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_tfs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract TF names from scRNA data and tf2motifs — get_tfs","text":"TFs (vector(character)) - List TFs expressed motifs.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/motifs_db-class.html","id":null,"dir":"Reference","previous_headings":"","what":"Motifs database class — motifs_db-class","title":"Motifs database class — motifs_db-class","text":"MotifsDatabase object stores motifs(PFM matrices) tf2motifs (TF motifs names mapping) data.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/motifs_db-class.html","id":"slots","dir":"Reference","previous_headings":"","what":"Slots","title":"Motifs database class — motifs_db-class","text":"motifs (TFBSTools::PWMatrixList) - PFM matrices. tf2motifs (data.frame) - TF motif names mapping. Columns: motif, tf.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/multilayer-class.html","id":null,"dir":"Reference","previous_headings":"","what":"Multilayer class — multilayer-class","title":"Multilayer class — multilayer-class","text":"Multilayer object stores list bipartite networks list multiplex networks. can also stores config list create yaml file, used parametrize random walk restart explore multilayer.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/multilayer-class.html","id":"slots","dir":"Reference","previous_headings":"","what":"Slots","title":"Multilayer class — multilayer-class","text":"bipartites (list) - List bipartite networks multiplex (list) - List multiplex networks config (list) - List parameters parametrize random walk restart explore multilayer","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/multiplex-class.html","id":null,"dir":"Reference","previous_headings":"","what":"Multiplex class — multiplex-class","title":"Multiplex class — multiplex-class","text":"Multiplex object stores list networks, list features list logicals indicating network directed weighted.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/multiplex-class.html","id":"slots","dir":"Reference","previous_headings":"","what":"Slots","title":"Multiplex class — multiplex-class","text":"networks (list) - List networks. features (vector) - Vector features. directed (list) - List logical indicating networks directed. weighted (list) - List logical indicating networks weighted.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/peaks_in_regulatory_elements.html","id":null,"dir":"Reference","previous_headings":"","what":"Filter peaks to those overlapping specific (regulatory) elements — peaks_in_regulatory_elements","title":"Filter peaks to those overlapping specific (regulatory) elements — peaks_in_regulatory_elements","text":"Function reduce list \"Peaks\" ones overlapping list \"RegEl\", e.g. regulatory elements, evolutionary conserved regions","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/peaks_in_regulatory_elements.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Filter peaks to those overlapping specific (regulatory) elements — peaks_in_regulatory_elements","text":"","code":"peaks_in_regulatory_elements(   Peaks,   RegEl,   sep_Peak1 = \"-\",   sep_Peak2 = \"-\",   sep_RegEl1 = \"-\",   sep_RegEl2 = \"-\" )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/peaks_in_regulatory_elements.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Filter peaks to those overlapping specific (regulatory) elements — peaks_in_regulatory_elements","text":"Peaks (character) vector genomic coordinates peaks RegEl (character) vector genomic coordinates regulatory elements sep_Peak1 (character) separator chromosome start position peak sep_Peak2 (character) separator start position end position peak sep_RegEl1 (character) separator chromosome start position regulatory element sep_RegEl2 (character) separator start position end position regulatory element","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/peaks_in_regulatory_elements.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Filter peaks to those overlapping specific (regulatory) elements — peaks_in_regulatory_elements","text":"(character) vector genomic coordinates peaks overlapping","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/peaks_in_regulatory_elements.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Filter peaks to those overlapping specific (regulatory) elements — peaks_in_regulatory_elements","text":"","code":"peaks_in_regulatory_elements(peaks, RegEl) #> Error in eval(expr, envir, enclos): object 'peaks' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/run_cicero_wrapper.html","id":null,"dir":"Reference","previous_headings":"","what":"Cicero wrapper function for the compute_atac_peak_network function — run_cicero_wrapper","title":"Cicero wrapper function for the compute_atac_peak_network function — run_cicero_wrapper","text":"function wrapper compute_atac_peak_network function layers.R. computes peak network scATAC-seq data using Cicero. returns data frame peak network. data frame also contains coaccess score edge. coaccess score probability two peaks accessible cell. coaccess score computed Cicero. Edges filtered based coaccess score. edges coaccess score > threshold kept.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/run_cicero_wrapper.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Cicero wrapper function for the compute_atac_peak_network function — run_cicero_wrapper","text":"","code":"run_cicero_wrapper(   hummus,   atac_assay,   genome,   window,   number_cells_per_clusters,   sample_num,   seed,   verbose,   threshold,   reduction_method = \"UMAP\" )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/run_cicero_wrapper.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Cicero wrapper function for the compute_atac_peak_network function — run_cicero_wrapper","text":"hummus hummus object atac_assay name assay containing scATAC-seq data genome genome object window window size used Cicero compute coaccess score number_cells_per_clusters number cells per cluster used Cicero compute coaccess score sample_num number samples used Cicero compute coaccess score seed seed used Cicero compute coaccess score verbose verbosity level threshold threshold used filter edges based coaccess score reduction_method method used monocle3 reduce dimension scATAC-seq data defining pseudocells. default UMAP.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/run_cicero_wrapper.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Cicero wrapper function for the compute_atac_peak_network function — run_cicero_wrapper","text":"data frame containing peak network","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/run_tf_null_wrapper.html","id":null,"dir":"Reference","previous_headings":"","what":"tf_null wrapper function for the tf_network function — run_tf_null_wrapper","title":"tf_null wrapper function for the tf_network function — run_tf_null_wrapper","text":"function wrapper tf_network function","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/run_tf_null_wrapper.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"tf_null wrapper function for the tf_network function — run_tf_null_wrapper","text":"","code":"run_tf_null_wrapper(   hummus = hummus,   organism = organism,   tfs = tfs,   gene_assay = gene_assay,   verbose = 1 )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/run_tf_null_wrapper.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"tf_null wrapper function for the tf_network function — run_tf_null_wrapper","text":"hummus hummus object","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/save_multilayer.html","id":null,"dir":"Reference","previous_headings":"","what":"Save multilayer object files in a hierarchical structure on disk — save_multilayer","title":"Save multilayer object files in a hierarchical structure on disk — save_multilayer","text":"Save multilayer files Hummus_Object hierarchical structure disk, inside folder specified folder_name","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/save_multilayer.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Save multilayer object files in a hierarchical structure on disk — save_multilayer","text":"","code":"save_multilayer(hummus, folder_name, verbose = TRUE, suffix = \".tsv\")"},{"path":"https://cantinilab.github.io/HuMMuS/reference/save_multilayer.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Save multilayer object files in a hierarchical structure on disk — save_multilayer","text":"hummus hummus object folder_name name folder save multilayer verbose (integer) - Display function messages. Set 0 message displayed, >= 1 details. suffix suffix files save. Default: \".tsv\"","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/save_multilayer.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Save multilayer object files in a hierarchical structure on disk — save_multilayer","text":"Nothing, create folder containing multilayer object files","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/save_multilayer.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Save multilayer object files in a hierarchical structure on disk — save_multilayer","text":"","code":"folder_name = \"multilayer\" save_multilayer(hummus = hummus, folder_name = \"multilayer\") #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/store_network.html","id":null,"dir":"Reference","previous_headings":"","what":"Wrapper function to save a network or not — store_network","title":"Wrapper function to save a network or not — store_network","text":"Wrapper function save network file according store_network parameter. store_network TRUE, network saved output_file.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/store_network.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Wrapper function to save a network or not — store_network","text":"","code":"store_network(network, store_network, output_file, verbose = 1)"},{"path":"https://cantinilab.github.io/HuMMuS/reference/store_network.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Wrapper function to save a network or not — store_network","text":"network network (edge list) store_network Logical indicating network saved output_file name file save network verbose (integer) - Display function messages. Set 0 message displayed, >= 1 details.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/store_network.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Wrapper function to save a network or not — store_network","text":"Nothing, save network file store_network TRUE","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/store_network.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Wrapper function to save a network or not — store_network","text":"","code":"network <- read.table(\"network.tsv\", header = TRUE, sep = \"\\t\") #> Warning: cannot open file 'network.tsv': No such file or directory #> Error in file(file, \"rt\"): cannot open the connection           store_network(network = network,               store_network = TRUE,               output_file = \"network.tsv\",               verbose = 1) #> \tStoring network in file :  network.tsv  #> Error in eval(expr, envir, enclos): object 'network' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/sub-subset-Hummus_Object.html","id":null,"dir":"Reference","previous_headings":"","what":"Access assays in Hummus_Object (based on Seurat) — [[<-,Hummus_Object","title":"Access assays in Hummus_Object (based on Seurat) — [[<-,Hummus_Object","text":"Access assays Hummus_Object (based Seurat)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/sub-subset-Hummus_Object.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access assays in Hummus_Object (based on Seurat) — [[<-,Hummus_Object","text":"","code":"# S3 method for Hummus_Object [[(x, i = missing_arg(), ..., drop = FALSE, na.rm = FALSE)"}]
+[{"path":"https://cantinilab.github.io/HuMMuS/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"GNU Affero General Public License","title":"GNU Affero General Public License","text":"Version 3, 19 November 2007 Copyright (C) 2007 Free Software Foundation, Inc.  Everyone permitted copy distribute verbatim copies license document, changing allowed.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/LICENSE.html","id":"preamble","dir":"","previous_headings":"","what":"Preamble","title":"GNU Affero General Public License","text":"GNU Affero General Public License free, copyleft license software kinds works, specifically designed ensure cooperation community case network server software. licenses software practical works designed take away freedom share change works. contrast, General Public Licenses intended guarantee freedom share change versions program–make sure remains free software users. speak free software, referring freedom, price. 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Definitions.","title":"GNU Affero General Public License","text":"“License” refers version 3 GNU Affero General Public License. “Copyright” also means copyright-like laws apply kinds works, semiconductor masks. “Program” refers copyrightable work licensed License. licensee addressed “”. “Licensees” “recipients” may individuals organizations. “modify” work means copy adapt part work fashion requiring copyright permission, making exact copy. resulting work called “modified version” earlier work work “based ” earlier work. “covered work” means either unmodified Program work based Program. “propagate” work means anything , without permission, make directly secondarily liable infringement applicable copyright law, except executing computer modifying private copy. Propagation includes copying, distribution (without modification), making available public, countries activities well. “convey” work means kind propagation enables parties make receive copies. 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Source Code.","title":"GNU Affero General Public License","text":"“source code” work means preferred form work making modifications . “Object code” means non-source form work. “Standard Interface” means interface either official standard defined recognized standards body, , case interfaces specified particular programming language, one widely used among developers working language. “System Libraries” executable work include anything, work whole, () included normal form packaging Major Component, part Major Component, (b) serves enable use work Major Component, implement Standard Interface implementation available public source code form. “Major Component”, context, means major essential component (kernel, window system, ) specific operating system () executable work runs, compiler used produce work, object code interpreter used run . “Corresponding Source” work object code form means source code needed generate, install, (executable work) run object code modify work, including scripts control activities. 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Protecting Users’ Legal Rights From Anti-Circumvention Law.","title":"GNU Affero General Public License","text":"covered work shall deemed part effective technological measure applicable law fulfilling obligations article 11 WIPO copyright treaty adopted 20 December 1996, similar laws prohibiting restricting circumvention measures. convey covered work, waive legal power forbid circumvention technological measures extent circumvention effected exercising rights License respect covered work, disclaim intention limit operation modification work means enforcing, work’s users, third parties’ legal rights forbid circumvention technological measures.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/LICENSE.html","id":"id_4-conveying-verbatim-copies","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"4. 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Conveying Modified Source Versions.","title":"GNU Affero General Public License","text":"may convey work based Program, modifications produce Program, form source code terms section 4, provided also meet conditions: work must carry prominent notices stating modified , giving relevant date. work must carry prominent notices stating released License conditions added section 7. requirement modifies requirement section 4 “keep intact notices”. must license entire work, whole, License anyone comes possession copy. License therefore apply, along applicable section 7 additional terms, whole work, parts, regardless packaged. 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Termination.","title":"GNU Affero General Public License","text":"may propagate modify covered work except expressly provided License. attempt otherwise propagate modify void, automatically terminate rights License (including patent licenses granted third paragraph section 11). However, cease violation License, license particular copyright holder reinstated () provisionally, unless copyright holder explicitly finally terminates license, (b) permanently, copyright holder fails notify violation reasonable means prior 60 days cessation. Moreover, license particular copyright holder reinstated permanently copyright holder notifies violation reasonable means, first time received notice violation License (work) copyright holder, cure violation prior 30 days receipt notice. 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Remote Network Interaction; Use with the GNU General Public License.","title":"GNU Affero General Public License","text":"Notwithstanding provision License, modify Program, modified version must prominently offer users interacting remotely computer network (version supports interaction) opportunity receive Corresponding Source version providing access Corresponding Source network server charge, standard customary means facilitating copying software. Corresponding Source shall include Corresponding Source work covered version 3 GNU General Public License incorporated pursuant following paragraph. Notwithstanding provision License, permission link combine covered work work licensed version 3 GNU General Public License single combined work, convey resulting work. terms License continue apply part covered work, work combined remain governed version 3 GNU General Public License.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/LICENSE.html","id":"id_14-revised-versions-of-this-license","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"14. Revised Versions of this License.","title":"GNU Affero General Public License","text":"Free Software Foundation may publish revised /new versions GNU Affero General Public License time time. new versions similar spirit present version, may differ detail address new problems concerns. version given distinguishing version number. Program specifies certain numbered version GNU Affero General Public License “later version” applies , option following terms conditions either numbered version later version published Free Software Foundation. Program specify version number GNU Affero General Public License, may choose version ever published Free Software Foundation. Program specifies proxy can decide future versions GNU Affero General Public License can used, proxy’s public statement acceptance version permanently authorizes choose version Program. Later license versions may give additional different permissions. However, additional obligations imposed author copyright holder result choosing follow later version.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/LICENSE.html","id":"id_15-disclaimer-of-warranty","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"15. Disclaimer of Warranty.","title":"GNU Affero General Public License","text":"WARRANTY PROGRAM, EXTENT PERMITTED APPLICABLE LAW. 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Interpretation of Sections 15 and 16.","title":"GNU Affero General Public License","text":"disclaimer warranty limitation liability provided given local legal effect according terms, reviewing courts shall apply local law closely approximates absolute waiver civil liability connection Program, unless warranty assumption liability accompanies copy Program return fee. END TERMS CONDITIONS","code":""},{"path":"https://cantinilab.github.io/HuMMuS/LICENSE.html","id":"how-to-apply-these-terms-to-your-new-programs","dir":"","previous_headings":"","what":"How to Apply These Terms to Your New Programs","title":"GNU Affero General Public License","text":"develop new program, want greatest possible use public, best way achieve make free software everyone can redistribute change terms. , attach following notices program. safest attach start source file effectively state exclusion warranty; file least “copyright” line pointer full notice found. Also add information contact electronic paper mail. software can interact users remotely computer network, also make sure provides way users get source. example, program web application, interface display “Source” link leads users archive code. many ways offer source, different solutions better different programs; see section 13 specific requirements. also get employer (work programmer) school, , sign “copyright disclaimer” program, necessary. information , apply follow GNU AGPL, see https://www.gnu.org/licenses/.","code":"     Copyright (C)         This program is free software: you can redistribute it and/or modify     it under the terms of the GNU Affero General Public License as     published by the Free Software Foundation, either version 3 of the     License, or (at your option) any later version.      This program is distributed in the hope that it will be useful,     but WITHOUT ANY WARRANTY; without even the implied warranty of     MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the     GNU Affero General Public License for more details.      You should have received a copy of the GNU Affero General Public License     along with this program.  If not, see ."},{"path":[]},{"path":[]},{"path":[]},{"path":"https://cantinilab.github.io/HuMMuS/articles/add_networks.html","id":"add-a-new-bipartite","dir":"Articles","previous_headings":"General plan","what":"3. Add a new bipartite","title":"Add external networks to HuMMuS object","text":"","code":"library(reticulate) # install python dependency py_install(\"hummuspy\", envname = \"r-reticulate\", method=\"auto\") ## Using virtual environment 'r-reticulate' ... ## + /home/runner/.virtualenvs/r-reticulate/bin/python -m pip install --upgrade --no-user hummuspy library(HuMMuS) ##"},{"path":"https://cantinilab.github.io/HuMMuS/articles/add_networks.html","id":"initialisation-of-hummus-object","dir":"Articles","previous_headings":"","what":"1. Initialisation of HuMMuS object","title":"Add external networks to HuMMuS object","text":"HuMMuS R objects instances developed top seurat objects. means ’s created seurat object contained assays can accessed way. Additionally, contains motifs_db object, providing tf motifs informations, multilayer objects, completed going tutorial. mostly include : - list multiplex networks (one per modality) - list bipartites (one per connection layers)","code":"# Create an hummus object from seurat object # Load the Chen dataset, which is a Seurat object containing scRNA-seq and scATAC-seq data data(\"chen_dataset_subset\") chen_dataset_subset ## An object of class Seurat  ## 12000 features across 385 samples within 2 assays  ## Active assay: RNA (2000 features, 0 variable features) ##  2 layers present: counts, data ##  1 other assay present: peaks hummus <- Initiate_Hummus_Object(chen_dataset_subset)   # wrapper of Signac::GetGRangesFromEnsDb, adapting output to UCSC format genome_annotations <- get_genome_annotations(   ensdb_annotations = EnsDb.Hsapiens.v86::EnsDb.Hsapiens.v86) # Add annotations to peak assay Signac::Annotation(hummus@assays$peaks) <- genome_annotations rm(genome_annotations)  # Load TF motifs from JASPAR2020 and chromVARmotifs in hummus object hummus@motifs_db <- get_tf2motifs() # by default human motifs"},{"path":[]},{"path":"https://cantinilab.github.io/HuMMuS/articles/add_networks.html","id":"add-a-new-multiplex-through-a-network","dir":"Articles","previous_headings":"2. Add networks","what":"2.1 Add a new multiplex through a network","title":"Add external networks to HuMMuS object","text":"","code":"# The networks should be imported as 3 columns data.frame: (source, target, weight) rna_network_path = \"chen_multilayer/multiplex/RNA/RNA_GENIE3.tsv\" rna_network <- read.table(rna_network_path, sep = \"\\t\", header = FALSE) head(rna_network) ##       V1      V2        V3 ## 1  BACH1  COL4A6 0.7388727 ## 2  DDIT3 CCDC173 0.7060954 ## 3  DDIT3  CCT6P1 0.6697768 ## 4  ATF6B  DNASE1 0.6598122 ## 5 ARID3B   ACER3 0.6499825 ## 6   ATF4  ATP8A1 0.6465523 hummus <- add_network(     hummus, rna_network,     multiplex_name = \"RNA\",     network_name = \"GENIE3\",     verbose = 1) ##  Creating new multiplex :  RNA"},{"path":"https://cantinilab.github.io/HuMMuS/articles/add_networks.html","id":"add-a-network-to-an-existing-multiplex","dir":"Articles","previous_headings":"2. Add networks","what":"2.2 Add a network to an existing multiplex","title":"Add external networks to HuMMuS object","text":"","code":"hummus <- add_network(     hummus, rna_network,     multiplex_name = \"RNA\",     network_name = \"GENIE3_other\")"},{"path":"https://cantinilab.github.io/HuMMuS/articles/add_networks.html","id":"add-external-bipartites","dir":"Articles","previous_headings":"2. Add networks","what":"3 Add external bipartites","title":"Add external networks to HuMMuS object","text":"Bipartites can 2 3 columns data.frame, depending weighted . Bipartites computed HuMMuS added directly object : Display HuMMuS object","code":"## Add TF peaks bipartite atac_rna_path = \"chen_multilayer/bipartite/atac_rna.tsv\" atac_rna <- read.table(atac_rna_path, sep = \"\\t\", header = FALSE) head(atac_rna) ##       V1                        V2 ## 1   CMC1    chr3-28241304-28242015 ## 2 ANGEL2  chr1-213015141-213016006 ## 3  CNNM2 chr10-103053902-103054565 ## 4  DNM1L   chr12-32678989-32680007 ## 5   DHX9  chr1-182838974-182840143 ## 6 B3GAT2    chr6-70955759-70956501 hummus@multilayer@bipartites[[\"atac_rna\"]] <- new(\"bipartite\",                            \"network\" = atac_rna,                            \"multiplex_left\" = \"RNA\",                            \"multiplex_right\" = \"peaks\") hummus ## Hummus object containing a multilayer object : ## Multilayer network containing  1  bipartite networks and  1  multiplex networks. ##   ## - Multiplex names:  RNA  ## - Bipartite names:  atac_rna  ##  ##  ## And a Seurat object : ##  ## 12000 features across samples within 2 assays  ## Active assay: RNA ( features, 0 variable features) ##  1 other assay present: peaks hummus@multilayer@multiplex ## $RNA ## Multiplex of  2  networks with 2000 features. ##  Networks names:  GENIE3, GENIE3_other"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"useful-links","dir":"Articles","previous_headings":"","what":"Useful links:","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"Paper: https://www.biorxiv.org/content/10.1101/2023.06.09.543828v1 Github repo: https://github.com/cantinilab/HuMMuS Documentation: https://cantinilab.github.io/HuMMuS/","code":""},{"path":[]},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"useful-ressources","dir":"Articles","previous_headings":"General description of the pipeline","what":"Useful ressources","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"Preprint detailing method: https://www.biorxiv.org/content/10.1101/2023.06.09.543828v1 Github repo detailing installation: https://github.com/cantinilab/HuMMuS Documentation vignette: https://cantinilab.github.io/HuMMuS","code":""},{"path":[]},{"path":[]},{"path":[]},{"path":[]},{"path":[]},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"setting-up-the-environment","dir":"Articles","previous_headings":"General description of the pipeline","what":"0. Setting up the environment","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"","code":"library(reticulate) # install python dependency py_install(\"hummuspy\", envname = \"r-reticulate\", method=\"auto\") ## Using virtual environment 'r-reticulate' ... ## + /home/runner/.virtualenvs/r-reticulate/bin/python -m pip install --upgrade --no-user hummuspy library(HuMMuS) ##"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"download-the-single-cell-data","dir":"Articles","previous_headings":"General description of the pipeline","what":"Download the single-cell data","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"data used tutorial can downloaded ","code":""},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"initialisation-of-hummus-object","dir":"Articles","previous_headings":"General description of the pipeline","what":"1. Initialisation of HuMMuS object","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"HuMMuS R objects instances developed top seurat objects. means ’s created seurat object contained assays can accessed way. Additionally, contains motifs_db object, providing tf motifs informations, multilayer objects, completed going tutorial. mostly include : list multiplex networks (one per modality) list bipartites (one per connection layers)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"transform-data-into-a-hummus-object","dir":"Articles","previous_headings":"General description of the pipeline > 1. Initialisation of HuMMuS object","what":"1.1. Transform data into a hummus object","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"","code":"# Load the Chen dataset, which is a Seurat object containing scRNA-seq and scATAC-seq data data(\"chen_dataset_subset\") chen_dataset_subset ## An object of class Seurat  ## 12000 features across 385 samples within 2 assays  ## Active assay: RNA (2000 features, 0 variable features) ##  2 layers present: counts, data ##  1 other assay present: peaks # Create an hummus object from seurat object hummus <- Initiate_Hummus_Object(chen_dataset_subset)"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"add-genome-and-motif-annotations-to-hummus-object","dir":"Articles","previous_headings":"General description of the pipeline > 1. Initialisation of HuMMuS object","what":"1.2. Add genome and motif annotations to hummus object","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"Fetch genome annotations online (necessitate internet connection). can also request “EnsDB” object adapted data (e.g. EnsDb.Hsapiens.v86::EnsDb.Hsapiens.v86 human genome annotations) use genome annotations format. Add genome annotations hummus/seurat object Get TF motifs JASPAR2020 chromVARmotifs databsases motifs_db object. default, human motifs used. can specify species want use species argument (e.g. species = “mouse” mouse). motifs_db objects contain 3 slots : * motifs = \"PWMatrixList\" * tf2motifs = \"data.frame\" * tfs = \"NULL\" PWMatrixList named vector motif matrices, whil tf2motifs correspondance table TFs motifs. tfs named vector TFs. can also use motifs_db object, long contains slots.","code":"# get human genome annotation from EndDb data # wrapper of Signac::GetGRangesFromEnsDb, adapting output to UCSC format genome_annotations <- get_genome_annotations(   ensdb_annotations = EnsDb.Hsapiens.v86::EnsDb.Hsapiens.v86)  # can also be downloaded, saved as an RDS objects for example Signac::Annotation(hummus@assays$peaks) <- genome_annotations rm(genome_annotations) # Load TF motifs from JASPAR2020 and chromVARmotifs in hummus object hummus@motifs_db <- get_tf2motifs() # by default human motifs"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"construction-of-the-multilayer-1","dir":"Articles","previous_headings":"General description of the pipeline","what":"2. Construction of the multilayer","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"can compute different layers bipartites indicated . example multilayer completed can also imported : data(chen_subset_hummus). object corresponds multilayer chen_dataset_subset completed. can go part 3, replacing hummus chen_subset_hummus step. Finally, can compute different layers , add afterwards. allows use faster methods compute networks (e.g. Arboreto gene network, ATACNet peak network, etc.).","code":""},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"compute-3-layers-and-2-bipartites","dir":"Articles","previous_headings":"General description of the pipeline > 2. Construction of the multilayer","what":"Compute 3 layers and 2 bipartites","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"!! Long step !! can also go directly part 3 “discovery tour”. :)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"tf---peaks-bipartite-reconstruction","dir":"Articles","previous_headings":"General description of the pipeline > 2. Construction of the multilayer","what":"2.1. TF - peaks bipartite reconstruction","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"TF - peaks bipartite computed using motifs_db object peak assay. can specify assay use filter TFs (e.g. “RNA” want use TFs expressed dataset). NULL, TFs motifs used. BSGenome object used identify location motifs intersect peak can also specify name bipartite added hummus object. default, named “tf_peak”.","code":"hummus <- bipartite_tfs2peaks(               hummus_object = hummus,               tf_expr_assay = \"RNA\", # use to filter TF on only expressed TFs,                                      # if NULL, all TFs with motifs are used               peak_assay = \"peaks\",               tf_multiplex_name = \"TF\",               genome = BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38,               )"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"genes---peaks-bipartite-reconstruction","dir":"Articles","previous_headings":"General description of the pipeline > 2. Construction of the multilayer","what":"2.2. Genes - peaks bipartite reconstruction","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"Peaks - genes bipartite computed","code":"hummus <- bipartite_peaks2genes(                       hummus_object = hummus,                       gene_assay = \"RNA\",                       peak_assay = \"peaks\",                       store_network = FALSE,                       )"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"compute-layer-networks-and-add-it-to-hummus-object","dir":"Articles","previous_headings":"General description of the pipeline > 2. Construction of the multilayer > 2.2. Genes - peaks bipartite reconstruction","what":"Compute layer networks and add it to hummus object","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"one three layers computed individually.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"compute-the-tf-network-from-omnipath-database","dir":"Articles","previous_headings":"General description of the pipeline > 2. Construction of the multilayer","what":"2.3. Compute the TF network from OmniPath database","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"currently use OmniPath R package fetch TF interactions. can first specify want use TFs expressed dataset (RNA assay hummus object). gene_assay NULL, TFs motifs used.  can specify interactions want keep ‘source_target’ argument (“” | “”). “”, interactions 2 TFs present dataset kept. “”, interactions involving least one TF present dataset kept. Finally, can specify name multiplex name network added hummus object. added network undirected unweighted since PPI OmniPath database directional return weight .","code":"hummus <- compute_tf_network(hummus,                             gene_assay = \"RNA\", # default = None ;                                                 # If a assay is provided,                                                 # only the TFs that are present                                                 # will be considered                             verbose = 1,                             #source_target = \"OR\",                             multiplex_name = \"TF\",                             tf_network_name = \"TF_network\")"},{"path":[]},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"this-step-can-be-very-slow-if-you-have-thousands-of-cells","dir":"Articles","previous_headings":"General description of the pipeline > 2. Construction of the multilayer","what":"!! This step can be very slow if you have thousands of cells !!","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"Current recommendation big dataset compute network GRNBoost2 thorugh arboreto add hummus object afterwards. Different methods can used compute gene network. now, GENIE3 implemented HuMMuS. can specify assay use compute network (gene_assay). can specify number cores use compute network. can also specify want save network locally (store_network = TRUE) (store_network = FALSE). choose save network, need specify output file name (output_file). returned network considered undirected weighted. GENIE3 returns directed network, symmetrize random walk restart exploration genes proximity.","code":"hummus <- compute_gene_network(               hummus,               gene_assay = \"RNA\",               method = \"GENIE3\",               verbose = 1,               number_cores = 5, # GENIE3 method can be ran                                 # parallelised on multiple cores               store_network = FALSE, # by default : FALSE, but                                      # each network can be saved                                       # when computed with hummus               output_file = \"gene_network.tsv\")"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"compute-the-peak-network-from-scatac-seq-w-cicero","dir":"Articles","previous_headings":"General description of the pipeline > 2. Construction of the multilayer","what":"2.5. Compute the peak network from scATAC-seq w/ Cicero","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"Different methods can used compute peak network. now, Cicero implemented HuMMuS. can specify assay use compute network (peak_assay). can also specify number cores use compute network. can also specify want save network locally (store_network = TRUE) (store_network = FALSE). choose save network, need specify output file name (output_file). returned network considered undirected weighted, since cis-regulatory interaction Cicero outputs directional.","code":"hummus <- compute_atac_peak_network(hummus,               atac_assay = \"peaks\",               verbose = 1,               genome = BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38,               store_network = FALSE)"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"analyse-of-the-multilayer-and-definition-of-grn","dir":"Articles","previous_headings":"General description of the pipeline","what":"3. Analyse of the multilayer and definition of GRN","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"","code":"data(chen_subset_hummus)  hummus <- chen_subset_hummus"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"save-the-mulilayer-in-a-classic-hierarchical-structure","dir":"Articles","previous_headings":"General description of the pipeline > 3. Analyse of the multilayer and definition of GRN","what":"3.1. Save the mulilayer in a classic hierarchical structure","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"package used random walk restart exploration (multixrank) requires currently save network files disk. simplify organisation file, possible save everything necessary function save_multilayer(). create folder (specified folder_name) containing files necessary run multixrank algorithm. folder contain following subfolders : * bipartite : containing bipartites files * multiplex : containing multiplex sub-subfolders * multiplex_1 (e.g. TF|peak|RNA) : containing network file layer multiplex * seed : contain seed files (necessary compute HuMMuS outputs later) * config : contain config files (necessary compute HuMMuS outputs later)","code":"save_multilayer(hummus = hummus,                 folder_name = \"chen_multilayer\") ## Warning in dir.create(folder_name): 'chen_multilayer' already exists ## Warning in dir.create(paste0(folder_name, \"/\", multiplex_folder)): ## 'chen_multilayer/multiplex' already exists ## Warning in dir.create(paste0(folder_name, \"/\", bipartite_folder)): ## 'chen_multilayer/bipartite' already exists ## Multiplex of  1  networks with 32 features. ##  Networks names:  TF_network[1] \"TF TF_network\" ## Warning in dir.create(paste0(folder_name, \"/\", multiplex_folder, \"/\", ## multiplex_name)): 'chen_multilayer/multiplex/RNA' already exists ## Multiplex of  1  networks with 2000 features. ##  Networks names:  RNA_GENIE3[1] \"RNA RNA_GENIE3\" ## Multiplex of  1  networks with 4639 features. ##  Networks names:  peak_network_cicero[1] \"peaks peak_network_cicero\""},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"retrieve-target-genes","dir":"Articles","previous_headings":"General description of the pipeline > 3. Analyse of the multilayer and definition of GRN","what":"3.2. Retrieve target genes","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"HuMMuS, inference GRN target gene TFs different outputs. Indeed, GRN computed making TFs compete regulate genes (random walk restart starting genes going TFs), target genes computed making genes compete regulated TFs (random walk restart starting TFs going genes). target genes output, can specify list TFs (tf_list) use seed (NULL default, TFs used seed). links seed TFs genes computed. can also specify list genes use. score genes present network gene_list returned.","code":"ATF2_genes <- define_target_genes(   hummus,   tf_list = list(\"ATF2\"),   multilayer_f = \"chen_multilayer\",   njobs = 1   ) ## multiplexes_list :  {'TF': {'TF_network': '00'}, 'RNA': {'RNA_GENIE3': '01'}, 'peaks': {'peak_network_cicero': '01'}} ## bipartites_list :  {'tf_peak.tsv': {'multiplex_right': 'TF', 'multiplex_left': 'peaks'}, 'atac_rna.tsv': {'multiplex_right': 'peaks', 'multiplex_left': 'RNA'}} ## folder_multiplexes :  multiplex ## folder_bipartites :  bipartite ## gene_list :  None ## tf_list :  ['ATF2'] ## peak_list :  None ## config_filename :  target_genes_config.yml ## config_folder :  config ## tf_multiplex :  TF ## peak_multiplex :  peaks ## rna_multiplex :  RNA ## update_config :  True ## save :  False ## return_df :  True ## output_f :  None ## njobs :  1 ## {'TF': {'TF_network': '00'}, 'RNA': {'RNA_GENIE3': '01'}, 'peaks': {'peak_network_cicero': '01'}} ## bipartites_type has been provided throguh a list, make sure the order matches the one of the 'bipartites' dictionary' keys. head(ATF2_genes) ##   layer                   path_layer        score   tf     gene ## 1   RNA multiplex/RNA/RNA_GENIE3.tsv 5.291440e-05 ATF2    CDC5L ## 2   RNA multiplex/RNA/RNA_GENIE3.tsv 4.570328e-05 ATF2     ATF3 ## 3   RNA multiplex/RNA/RNA_GENIE3.tsv 4.486208e-05 ATF2    ATP5I ## 4   RNA multiplex/RNA/RNA_GENIE3.tsv 4.485191e-05 ATF2 CCNB1IP1 ## 5   RNA multiplex/RNA/RNA_GENIE3.tsv 4.482241e-05 ATF2   DGCR14 ## 6   RNA multiplex/RNA/RNA_GENIE3.tsv 4.176609e-05 ATF2    ATAT1 target_genes <- define_target_genes(   hummus,   multilayer_f = \"chen_multilayer\",   njobs = 1   ) ## multiplexes_list :  {'TF': {'TF_network': '00'}, 'RNA': {'RNA_GENIE3': '01'}, 'peaks': {'peak_network_cicero': '01'}} ## bipartites_list :  {'tf_peak.tsv': {'multiplex_right': 'TF', 'multiplex_left': 'peaks'}, 'atac_rna.tsv': {'multiplex_right': 'peaks', 'multiplex_left': 'RNA'}} ## folder_multiplexes :  multiplex ## folder_bipartites :  bipartite ## gene_list :  None ## tf_list :  None ## peak_list :  None ## config_filename :  target_genes_config.yml ## config_folder :  config ## tf_multiplex :  TF ## peak_multiplex :  peaks ## rna_multiplex :  RNA ## update_config :  True ## save :  False ## return_df :  True ## output_f :  None ## njobs :  1 ## {'TF': {'TF_network': '00'}, 'RNA': {'RNA_GENIE3': '01'}, 'peaks': {'peak_network_cicero': '01'}} ## bipartites_type has been provided throguh a list, make sure the order matches the one of the 'bipartites' dictionary' keys. head(target_genes) ##   layer                   path_layer        score   tf     gene ## 1   RNA multiplex/RNA/RNA_GENIE3.tsv 0.0002318541 CUX1   CHRNB1 ## 2   RNA multiplex/RNA/RNA_GENIE3.tsv 0.0002299783 CUX1    CDC5L ## 3   RNA multiplex/RNA/RNA_GENIE3.tsv 0.0002217501 CUX1    ALG11 ## 4   RNA multiplex/RNA/RNA_GENIE3.tsv 0.0002211187 CUX1    CDCA5 ## 5   RNA multiplex/RNA/RNA_GENIE3.tsv 0.0002201921 CUX1    AGBL5 ## 6   RNA multiplex/RNA/RNA_GENIE3.tsv 0.0001498125 BPTF CDC42SE1"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"define-grn","dir":"Articles","previous_headings":"General description of the pipeline > 3. Analyse of the multilayer and definition of GRN","what":"3.3. Define GRN","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"GRN defined using multixrank algorithm. requires hummuspy python package installed (pip install hummuspy). can parallelised using njobs argument. can also specify list genes list TFs use.","code":"grn <- define_grn(   hummus,   multilayer_f = \"chen_multilayer\",   njobs = 1   ) head(grn)"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"retrieve-enhancers","dir":"Articles","previous_headings":"General description of the pipeline > 3. Analyse of the multilayer and definition of GRN","what":"3.4. Retrieve enhancers","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"can also specify list peaks use.","code":"enhancers <- define_enhancers(   hummus,   gene_list = list(\"ATF2\"),   multilayer_f = \"chen_multilayer\",   njobs = 1   ) ## multiplexes_list :  {'TF': {'TF_network': '00'}, 'RNA': {'RNA_GENIE3': '01'}, 'peaks': {'peak_network_cicero': '01'}} ## bipartites_list :  {'tf_peak.tsv': {'multiplex_right': 'TF', 'multiplex_left': 'peaks'}, 'atac_rna.tsv': {'multiplex_right': 'peaks', 'multiplex_left': 'RNA'}} ## folder_multiplexes :  multiplex ## folder_bipartites :  bipartite ## gene_list :  ['ATF2'] ## tf_list :  None ## peak_list :  None ## config_filename :  enhancers_config.yml ## config_folder :  config ## tf_multiplex :  TF ## peak_multiplex :  peaks ## rna_multiplex :  RNA ## update_config :  True ## save :  False ## return_df :  True ## output_f :  None ## njobs :  1 ## {'TF': {'TF_network': '00'}, 'RNA': {'RNA_GENIE3': '01'}, 'peaks': {'peak_network_cicero': '01'}} ## bipartites_type has been provided throguh a list, make sure the order matches the one of the 'bipartites' dictionary' keys. head(enhancers) ##   layer                              path_layer        score gene ## 1 peaks multiplex/peaks/peak_network_cicero.tsv 0.0008951819 ATF2 ## 2 peaks multiplex/peaks/peak_network_cicero.tsv 0.0007383304 ATF2 ## 3 peaks multiplex/peaks/peak_network_cicero.tsv 0.0006763254 ATF2 ## 4 peaks multiplex/peaks/peak_network_cicero.tsv 0.0004115710 ATF2 ## 5 peaks multiplex/peaks/peak_network_cicero.tsv 0.0003972408 ATF2 ## 6 peaks multiplex/peaks/peak_network_cicero.tsv 0.0003850920 ATF2 ##                       peak ## 1   chr6-44387360-44388305 ## 2 chr3-107522766-107524070 ## 3 chr7-102125135-102125606 ## 4   chr7-73738654-73739271 ## 5  chr10-73874242-73875104 ## 6  chr16-67561885-67563510"},{"path":"https://cantinilab.github.io/HuMMuS/articles/chen_vignette.html","id":"retrieve-binding-regions","dir":"Articles","previous_headings":"General description of the pipeline > 3. Analyse of the multilayer and definition of GRN","what":"3.5. Retrieve binding regions","title":"Predict GRN from scRNA+scATAC data (Chen 2018 dataset)","text":"binding regions output, can specify list TFs (tf_list) use seed (NULL default, TFs used seed). links seed TFs peaks computed. can also specify list peaks use. score peaks present network peak_list returned.","code":"binding_regions <- define_binding_regions(   hummus,   multilayer_f = \"chen_multilayer\",   njobs = 1   ) ## multiplexes_list :  {'TF': {'TF_network': '00'}, 'RNA': {'RNA_GENIE3': '01'}, 'peaks': {'peak_network_cicero': '01'}} ## bipartites_list :  {'tf_peak.tsv': {'multiplex_right': 'TF', 'multiplex_left': 'peaks'}, 'atac_rna.tsv': {'multiplex_right': 'peaks', 'multiplex_left': 'RNA'}} ## folder_multiplexes :  multiplex ## folder_bipartites :  bipartite ## gene_list :  None ## tf_list :  None ## peak_list :  None ## config_filename :  binding_regions_config.yml ## config_folder :  config ## tf_multiplex :  TF ## peak_multiplex :  peaks ## rna_multiplex :  RNA ## update_config :  True ## save :  False ## return_df :  True ## output_f :  None ## njobs :  1 ## {'TF': {'TF_network': '00'}, 'RNA': {'RNA_GENIE3': '01'}, 'peaks': {'peak_network_cicero': '01'}} ## bipartites_type has been provided throguh a list, make sure the order matches the one of the 'bipartites' dictionary' keys. head(binding_regions) ##   layer                              path_layer       score   tf ## 1 peaks multiplex/peaks/peak_network_cicero.tsv 0.001680402 CUX1 ## 2 peaks multiplex/peaks/peak_network_cicero.tsv 0.001675393 CUX1 ## 3 peaks multiplex/peaks/peak_network_cicero.tsv 0.001674121 CUX1 ## 4 peaks multiplex/peaks/peak_network_cicero.tsv 0.001559648 CUX1 ## 5 peaks multiplex/peaks/peak_network_cicero.tsv 0.001502478 CUX1 ## 6 peaks multiplex/peaks/peak_network_cicero.tsv 0.001502093 CUX1 ##                       peak ## 1   chr1-65002512-65003322 ## 2   chrX-48971714-48972653 ## 3   chr1-65419692-65420979 ## 4   chrX-48918888-48919598 ## 5   chr8-24955892-24956818 ## 6 chr2-201642365-201643651"},{"path":"https://cantinilab.github.io/HuMMuS/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Rémi Trimbour. Author, maintainer.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Trimbour R (2024). HuMMuS: Heterogeneous Multilayer Network Multi-Omics Single-Cell Data. R package version 0.0.2, https://cantinilab.github.io/HuMMuS/.","code":"@Manual{,   title = {HuMMuS: Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data},   author = {Rémi Trimbour},   year = {2024},   note = {R package version 0.0.2},   url = {https://cantinilab.github.io/HuMMuS/}, }"},{"path":[]},{"path":"https://cantinilab.github.io/HuMMuS/index.html","id":"heterogeneous-multilayer-network-for-multi-omics-single-cell-data","dir":"","previous_headings":"","what":"Heterogeneous Multilayer network for Multi-omics Single-cell data","title":"Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data","text":"HuMMuS exploits multi-omics single-cell measurements infer numerous regulatory mechanisms. Inter-omics (e.g. peak-gene, TF-peak) intra-omics interactions (e.g. peak-peak, gene-gene, TF-TF) considered capture regulatory interactions macromolecule cooperations.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/index.html","id":"overview","dir":"","previous_headings":"","what":"Overview","title":"Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data","text":"current outputs available HuMMuS gene regulatory networks (GRNs) enhancers TF - DNA binding regions TF - target genes.","code":""},{"path":[]},{"path":"https://cantinilab.github.io/HuMMuS/index.html","id":"scrna--scatac","dir":"","previous_headings":"Overview","what":"scRNA + scATAC","title":"Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data","text":"Like current state---art methods infer GRN, propose minimal version HuMMuS based scRNA-seq + scATAC-seq data (paired unpaired).","code":""},{"path":"https://cantinilab.github.io/HuMMuS/index.html","id":"use-of-additional-modalities","dir":"","previous_headings":"Overview","what":"Use of additional modalities","title":"Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data","text":"HuMMuS developed extendable additional biological modality interest. possible add additional network already existing modality (e.g. prior-knowledge network data-driven network genes), new modality (e.g. adding epigenetic proteomic networks). now, personalisation requires use directly hummuspy (python package) functions end pipeline write configuration files manually. simplified soon !","code":""},{"path":"https://cantinilab.github.io/HuMMuS/index.html","id":"tutorialsvignettes","dir":"","previous_headings":"","what":"Tutorials/Vignettes","title":"Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data","text":"Infer gene regulatory network outputs unpaired/paired scRNA+scATAC data shows application HuMMuS Chen dataset, used benchmark HuMMuS publication.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data","text":"HuMMuS now ready R requires python dependencies (hummuspy).","code":""},{"path":"https://cantinilab.github.io/HuMMuS/index.html","id":"hummus-python-dependency","dir":"","previous_headings":"Installation","what":"HuMMuS python dependency","title":"Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data","text":"Python package hummuspy preferably installed using pip (terminal conda environment e.g) Alternatively, can also install directly R using reticulate package:","code":"conda create -n hummuspy_env python conda activate hummuspy_env pip install hummuspy library(reticulate) py_install(\"hummuspy\", envname = \"r-reticulate\", method=\"auto\")"},{"path":"https://cantinilab.github.io/HuMMuS/index.html","id":"hummus-r-package","dir":"","previous_headings":"Installation","what":"HuMMuS R package","title":"Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data","text":"Core R package can installed directly R: running HuMMuS, ’re using multiple conda environment need make sure reticulate points toward one hummuspy installed. can precise beginning code : details setup reticulate connection, see: https://rstudio.github.io/reticulate","code":"devtools::install_github(\"cantinilab/HuMMuS\") library(reticulate) # Using a specific conda environment envname = \"hummuspy_env\" # or \"r-reticulate\" for e.g. use_condaenv(envname, required = TRUE)"},{"path":"https://cantinilab.github.io/HuMMuS/index.html","id":"scatac-processing","dir":"","previous_headings":"Installation","what":"scATAC processing","title":"Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data","text":"compute directly scATAC data HuMMuS, currently propose use Cicero. requires version running Monocle3. need install Monocle3, Cicero: encounter troubles Monocle3 installation, ubuntu can try run: sudo apt-get install libgdal-dev libgeos-dev libproj-dev. can also go github page help. previous version Monocle (1 2) still R session can cause troubles. encounter even restarting R session,, try remove.packages(\"monocle\") reinstall Monocle3 Cicero","code":"devtools::install_github(\"cole-trapnell-lab/monocle3\") devtools::install_github(\"cole-trapnell-lab/cicero-release\", ref = \"monocle3\")"},{"path":"https://cantinilab.github.io/HuMMuS/index.html","id":"data-accessibility","dir":"","previous_headings":"","what":"Data accessibility","title":"Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data","text":"reproduce HuMMuS results presented manuscript, preprocessed data accessible  quick tests, Chen dataset preprocessed accessible directly package Seurat object: load(chen_dataset), along subset version load(chen_dataset_subset).","code":""},{"path":"https://cantinilab.github.io/HuMMuS/index.html","id":"cite-us","dir":"","previous_headings":"","what":"Cite us","title":"Heterogeneous Multilayer Network for Multi-Omics Single-Cell Data","text":"Trimbour R., Deutschmann . M., Cantini L. Molecular mechanisms reconstruction single-cell multi-omics data HuMMuS. Bioinformatics (2024), btae143. doi: https://doi.org/10.1093/bioinformatics/btae143","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/DefaultAssay.html","id":null,"dir":"Reference","previous_headings":"","what":"Get Default assays of Hummus_Object (based on Seurat) — DefaultAssay","title":"Get Default assays of Hummus_Object (based on Seurat) — DefaultAssay","text":"Get set default assay","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/DefaultAssay.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get Default assays of Hummus_Object (based on Seurat) — DefaultAssay","text":"","code":"# S3 method for Hummus_Object DefaultAssay(object, ...)  DefaultAssay(object, ...)  DefaultAssay(object, ...) <- value"},{"path":"https://cantinilab.github.io/HuMMuS/reference/DefaultAssay.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get Default assays of Hummus_Object (based on Seurat) — DefaultAssay","text":"object object value Name assay set default","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/DefaultAssay.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get Default assays of Hummus_Object (based on Seurat) — DefaultAssay","text":"DefaultAssay: name default assay DefaultAssay<-: object default assay updated","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/DefaultAssay.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Get Default assays of Hummus_Object (based on Seurat) — DefaultAssay","text":"","code":"# Get current default assay DefaultAssay(object = pbmc_small) #> Error in eval(expr, envir, enclos): object 'pbmc_small' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/Hummus_Object-class.html","id":null,"dir":"Reference","previous_headings":"","what":"The Hummus_Object class — Hummus_Object-class","title":"The Hummus_Object class — Hummus_Object-class","text":"Hummus_Object object extended Seurat object storage analysis heterogeneous multilayer network","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/Hummus_Object-class.html","id":"slots","dir":"Reference","previous_headings":"","what":"Slots","title":"The Hummus_Object class — Hummus_Object-class","text":"multilayer (multilayer) - Multilayer object motifs_db (motifs_db) - Motifs database assay (list) - List assays","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/Initiate_Hummus_Object.html","id":null,"dir":"Reference","previous_headings":"","what":"Initiate a hummus object — Initiate_Hummus_Object","title":"Initiate a hummus object — Initiate_Hummus_Object","text":"Initiate hummus object","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/Initiate_Hummus_Object.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Initiate a hummus object — Initiate_Hummus_Object","text":"","code":"Initiate_Hummus_Object(   seurat_assays,   active.assay = NULL,   multilayer = NULL,   motifs_db = NULL )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/Initiate_Hummus_Object.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Initiate a hummus object — Initiate_Hummus_Object","text":"seurat_assays Seurat object list Seurat assays active.assay name active assay. Default: NULL multilayer multilayer object. Default: NULL motifs_db motifs_db object. Default: NULL","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/Initiate_Hummus_Object.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Initiate a hummus object — Initiate_Hummus_Object","text":"hummus object","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/Initiate_Hummus_Object.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Initiate a hummus object — Initiate_Hummus_Object","text":"","code":"seurat_object <- Seurat::CreateSeuratObject(counts = matrix(rnorm(1000), nrow = 100, ncol = 10)) #> Error in loadNamespace(x): there is no package called ‘Seurat’          hummus <- InitiateHummus_Object(seurat_object) #> Error in InitiateHummus_Object(seurat_object): could not find function \"InitiateHummus_Object\"          hummus #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/VariableFeatures.html","id":null,"dir":"Reference","previous_headings":"","what":"Variable features of assays in Hummus_Object (based on Seurat) — VariableFeatures","title":"Variable features of assays in Hummus_Object (based on Seurat) — VariableFeatures","text":"Variable features assays Hummus_Object (based Seurat)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/VariableFeatures.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Variable features of assays in Hummus_Object (based on Seurat) — VariableFeatures","text":"","code":"# S3 method for Hummus_Object VariableFeatures(   object,   method = NULL,   assay = NULL,   nfeatures = NULL,   layer = NA,   simplify = TRUE,   selection.method = lifecycle::deprecated(),   ... )  VariableFeatures(object, method = NULL, ...)  VariableFeatures(object, ...) <- value"},{"path":"https://cantinilab.github.io/HuMMuS/reference/VariableFeatures.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Variable features of assays in Hummus_Object (based on Seurat) — VariableFeatures","text":"value character vector variable features","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/VariableFeatures.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Variable features of assays in Hummus_Object (based on Seurat) — VariableFeatures","text":"VariableFeatures: vector variable features","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/add_network.html","id":null,"dir":"Reference","previous_headings":"","what":"Add a network to a multiplex, a multilayer or an hummus object — add_network","title":"Add a network to a multiplex, a multilayer or an hummus object — add_network","text":"Add network multiplex, multilayer hummus object","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/add_network.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Add a network to a multiplex, a multilayer or an hummus object — add_network","text":"","code":"add_network(   object,   network,   network_name,   multiplex_name = NULL,   directed = FALSE,   weighted = FALSE,   verbose = 1 )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/add_network.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Add a network to a multiplex, a multilayer or an hummus object — add_network","text":"object multiplex, multilayer hummus object network network (edge list) network_name name network multiplex_name name multiplex. Default: NULL object multiplex already directed Logical indicating network directed. Default: FALSE weighted Logical indicating network weighted. Default: FALSE verbose (integer) - Display function messages. Set 0 message displayed, >= 1 details.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/add_network.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Add a network to a multiplex, a multilayer or an hummus object — add_network","text":"multiplex, multilayer hummus object added network","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/add_network.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Add a network to a multiplex, a multilayer or an hummus object — add_network","text":"","code":"hummus <- add_network(                            object = hummus,                            network = atac_peak_network,                            network_name = network_name,                            multiplex_name = multiplex_name,                            weighted = TRUE,                            directed = FALSE) #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/aggregate_matrix.html","id":null,"dir":"Reference","previous_headings":"","what":"Aggregate matrix over groups — aggregate_matrix","title":"Aggregate matrix over groups — aggregate_matrix","text":"Aggregate matrix groups","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/aggregate_matrix.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Aggregate matrix over groups — aggregate_matrix","text":"","code":"aggregate_matrix(x, groups = NULL, fun = \"mean\")"},{"path":"https://cantinilab.github.io/HuMMuS/reference/aggregate_matrix.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Aggregate matrix over groups — aggregate_matrix","text":"groups character vector groups aggregate . fun summary function applied group.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/aggregate_matrix.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Aggregate matrix over groups — aggregate_matrix","text":"summary matrix.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite-class.html","id":null,"dir":"Reference","previous_headings":"","what":"Bipartite class — bipartite-class","title":"Bipartite class — bipartite-class","text":"Bipartite object stores bipartite network (edge list) names left right features' multiplexes.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite-class.html","id":"slots","dir":"Reference","previous_headings":"","what":"Slots","title":"Bipartite class — bipartite-class","text":"network (data.frame) - Bipartite network (edge list) multiplex_left (character) - Left features' multiplex multiplex_right (character) - Right features' multiplex","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite-class.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Bipartite class — bipartite-class","text":"","code":"bipartite <- bipartite(                           network = bipartite_network,                          multiplex_left = \"RNA\",                         multiplex_right = \"peaks\") #> Error in bipartite(network = bipartite_network, multiplex_left = \"RNA\",     multiplex_right = \"peaks\"): could not find function \"bipartite\""},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite_peaks2genes.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute links between DNA regions and genenames — bipartite_peaks2genes","title":"Compute links between DNA regions and genenames — bipartite_peaks2genes","text":"Compute add bipartite DNA regions genenames hummus object. Links computed based distance peaks gene's TSS location gene.range annotations. Call find_peaks_near_genes function, can use different methods.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite_peaks2genes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute links between DNA regions and genenames — bipartite_peaks2genes","text":"","code":"bipartite_peaks2genes(   hummus_object,   gene_assay = \"RNA\",   peak_assay = \"peaks\",   gene_multiplex_name = NULL,   peak_multiplex_name = NULL,   peak_to_gene_method = \"Signac\",   upstream = 500,   downstream = 500,   only_tss = TRUE,   store_network = FALSE,   output_file = NULL,   bipartite_name = \"atac_rna\" )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite_peaks2genes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute links between DNA regions and genenames — bipartite_peaks2genes","text":"hummus_object (hummus_object) - Hummus object. gene_assay (character) - Name assay containing gene expression data. Default: \"RNA\". peak_assay (character) - Name assay containing DNA regions (ATAC peaks). Default: \"peaks\". gene_multiplex_name (character) - Name multiplex containing genes. NULL, name gene assay used. peak_multiplex_name (character) - Name multiplex containing DNA regions (ATAC peaks). NULL, name peak assay used. peak_to_gene_method (character) - Method use compute links peaks genes. Default: \"Signac\". 'Signac' - Use Signac::Extend extend genes. 'GREAT' - implemented yet. upstream (int) - Upstream distance TSS consider potential promoter. downstream (int) - Downstream distance TSS consider potential promoter. only_tss (logical) - TRUE, TSS considered. store_network (bool) - Save bipartite directly (TRUE, default) return without saving disk (FALSE). output_file (character) - Name output_file (store_bipartite == TRUE). Default: NULL. bipartite_name (character) - Name bipartite. Default: \"atac_rna\". verbose (integer) Display function messages. Set 0 message displayed, >= 1 details. Default: 1.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite_peaks2genes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute links between DNA regions and genenames — bipartite_peaks2genes","text":"hummus_object (hummus_object) - Hummus object w/ atac-rna bipartite added multilayer slot","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite_peaks2genes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute links between DNA regions and genenames — bipartite_peaks2genes","text":"","code":"hummus <- bipartite_peaks2genes(                        hummus_object = hummus,                        gene_assay = \"RNA\",                        peak_assay = \"peaks\",                        gene_multiplex_name = \"RNA\",                        peak_multiplex_name = \"peaks\",                        peak_to_gene_method = \"Signac\",                        upstream = 500,                        downstream = 500,                        only_tss = TRUE,                        store_network = FALSE,                        bipartite_name = \"atac_rna\") #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite_tfs2peaks.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute links between TFs and DNA regions (ATAC peaks) — bipartite_tfs2peaks","title":"Compute links between TFs and DNA regions (ATAC peaks) — bipartite_tfs2peaks","text":"Compute add bipartite TFs DNA regions hummus object. Links computed based binding motifs TFs locations reference genome. Currently based Signac AddMotifs function (--> motifmachR, based MOODs algorithm).","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite_tfs2peaks.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute links between TFs and DNA regions (ATAC peaks) — bipartite_tfs2peaks","text":"","code":"bipartite_tfs2peaks(   hummus_object,   tf_expr_assay = \"RNA\",   peak_assay = \"peaks\",   tf_multiplex_name = NULL,   peak_multiplex_name = NULL,   genome,   store_network = FALSE,   output_file = NULL,   verbose = 1,   bipartite_name = \"tf_peak\" )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite_tfs2peaks.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute links between TFs and DNA regions (ATAC peaks) — bipartite_tfs2peaks","text":"hummus_object (hummus_object) - Hummus object. tf_expr_assay (character) - Name assay containing TF expression data. NULL, TFs motif used. Default: \"RNA\". peak_assay (character) - Name assay containing DNA regions (ATAC peaks). Default: \"peaks\". tf_multiplex_name (character) - Name multiplex containing TFs. NULL, name TF assay used. peak_multiplex_name (character) - Name multiplex containing DNA regions (ATAC peaks). NULL, name peak assay used. genome (BSgenome object) - Reference genome. store_network (bool) - Save bipartite directly (TRUE, default) return without saving disk (FALSE). output_file (character) - Name output_file (store_bipartite == TRUE). Default: NULL. verbose (integer) Display function messages. Set 0 message displayed, >= 1 details. Default: 1. bipartite_name (character) - Name bipartite. Default: \"tf_peak\".","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite_tfs2peaks.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute links between TFs and DNA regions (ATAC peaks) — bipartite_tfs2peaks","text":"hummus_object (hummus_object) - Hummus object TF-peak bipartite added multilayer slot","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/bipartite_tfs2peaks.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute links between TFs and DNA regions (ATAC peaks) — bipartite_tfs2peaks","text":"","code":"hummus <- bipartite_tfs2peaks(                      hummus_object = hummus,                      tf_expr_assay = \"RNA\",                      peak_assay = \"peaks\",                      tf_multiplex_name = \"TF\",                      peak_multiplex_name = \"peaks\",           genome = BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38,                      store_network = FALSE,                      verbose = 1,                      bipartite_name = \"tf_peak\") #> Computing TF-peak bipartite #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_atac_peak_network.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute peak network from scATAC-seq data — compute_atac_peak_network","title":"Compute peak network from scATAC-seq data — compute_atac_peak_network","text":"function create network atac data (theory data wtih peaks coordinates features). Different method implemented point (e.g. RENIN), now Cicero still reference method available","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_atac_peak_network.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute peak network from scATAC-seq data — compute_atac_peak_network","text":"","code":"compute_atac_peak_network(   hummus,   atac_assay = \"peaks\",   genome = BSgenome.Hsapiens.UCSC.hg38::BSgenome.Hsapiens.UCSC.hg38,   method = \"cicero\",   multiplex_name = NULL,   network_name = NULL,   store_network = FALSE,   output_file = NULL,   threshold = 0,   number_cells_per_clusters = 50,   sample_num = 100,   seed = 2025,   verbose = 1,   window = 5e+05,   reduction_method = \"UMAP\" )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_atac_peak_network.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute peak network from scATAC-seq data — compute_atac_peak_network","text":"hummus (Hummus_Object) - Hummus object atac_assay (character) - Name assay containing atac peaks data. genome (BSgenome) - Genome used compute distance peaks. method (character) - Method used infer network edges. 'cicero' - Use cicero infer regulatory networks. 'method' - . multiplex_name (character) - Name multiplex add network . Default 'peaks'. network_name (character) - Name network multiplex add network . Default 'peak_network'. store_network (bool) - Save network directly (TRUE, default) return without saving disk (FALSE). output_file (character) - Name output_file (store_network == TRUE). threshold (interger, default 0) - Minimal threshold select tf-gene edges. number_cells_per_clusters (integer) - Number cells grouped territory define pseudocells sample_num (integer | Cicero) - Number pseudocells sample territory. Default 100. seed (integer | Cicero) - Seed used sample pseudocells. Default 2025 verbose (integer) - Display function messages. Set 0 message displayed, >= 1 details. window (integer) - Size window consider potential cis-regulatory cooperations peaks. Default 500K base pairs. reduction_method (character | Cicero) - Method used reduce dimensionality data identify territories. Default 'UMAP'.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_atac_peak_network.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute peak network from scATAC-seq data — compute_atac_peak_network","text":"(data.frame) - Return list network interactions peaks","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_atac_peak_network.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Compute peak network from scATAC-seq data — compute_atac_peak_network","text":"Method descriptions : Cicero Use patial corelation peaks given window (e.g. : less distant 500K base pairs)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_atac_peak_network.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute peak network from scATAC-seq data — compute_atac_peak_network","text":"","code":"hummus <- compute_atac_peak_network(hummus) #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_gene_network.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute gene netwok from scRNA-seq data — compute_gene_network","title":"Compute gene netwok from scRNA-seq data — compute_gene_network","text":"function create network rna data (theory data wtih genes features). Different method implemented point (suggestion welcomed ! :) ), now Genie3 still reference method available","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_gene_network.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute gene netwok from scRNA-seq data — compute_gene_network","text":"","code":"compute_gene_network(   hummus,   gene_assay = \"RNA\",   tfs = NULL,   method = \"GENIE3\",   multiplex_name = NULL,   network_name = NULL,   store_network = FALSE,   output_file = NULL,   threshold = 0,   number_cores = 1,   verbose = 1 )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_gene_network.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute gene netwok from scRNA-seq data — compute_gene_network","text":"hummus (Hummus_Object) - Hummus object gene_assay (character) - Name assay containing gene expression data. tfs vector(character) - List tfs considered. NULL, TFs motifs hummus object used. method (character) - Method used infer network edges. 'Genie3' - Use tree random forest infer regulatory networks. 'method' - . multiplex_name (character) - Name multiplex add network . Default 'RNA'. network_name (character) - Name network multiplex add network . Default 'RNA_network'. store_network (bool) - Save network directly (TRUE, default) return without saving disk (FALSE). output_file (character) - Name output_file (store_network == TRUE). threshold (interger, default 0) - Minimal threshold select tf-gene edges. number_cores (interger, default 1) - Number thread used parallelizable methods. verbose (integer) - Display function messages. Set 0 message displayed, >= 1 details.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_gene_network.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute gene netwok from scRNA-seq data — compute_gene_network","text":"(data.frame) - Return list network interactions genes","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_gene_network.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Compute gene netwok from scRNA-seq data — compute_gene_network","text":"Method descriptions : Genie3 Use tree random forest infer regulatory networks : https://bioconductor.org/packages/release/bioc/html/GENIE3.html","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_gene_network.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute gene netwok from scRNA-seq data — compute_gene_network","text":"","code":"hummus <- compute_gene_network(                                hummus,                                gene_assay = \"RNA\",                                method = \"GENIE3\",                                verbose = 1,                                number_cores = 8,                                store_network = FALSE) #> Computing gene network with  GENIE3  ... #> \tNo TFs list provided, fetching from hummus object... #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_tf_network.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute TF network and add it to hummus object — compute_tf_network","title":"Compute TF network and add it to hummus object — compute_tf_network","text":"Compute protein-protein interaction layer Omnipath request represent tf cooperativity. network top-layer HuMMuS multilayer.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_tf_network.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute TF network and add it to hummus object — compute_tf_network","text":"","code":"compute_tf_network(   hummus,   organism = 9606,   tfs = NA,   gene_assay = NULL,   method = NULL,   store_network = FALSE,   output_file = NULL,   source_target = \"AND\",   multiplex_name = \"TF\",   tf_network_name = \"TF_network\",   verbose = 1 )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_tf_network.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute TF network and add it to hummus object — compute_tf_network","text":"hummus (Hummus_Object) - Hummus object organism (integer)  - Specie identifier Omnipath fetch specific interactions tfs vector(character) - List tfs consider. NA, tfs extracted hummus object get_tfs function. gene_assay (character) - Name assay get tfs tfs provided. NULL, TFs motifs hummus object used. method (character) - Method used infer network edges. 'Omnipath' - Use Omnipath infer tf-tf networks. 'NULL' - fake connected network computed. 'method' - . store_network (bool) - Save network directly (TRUE, default) return without saving disk (FALSE). output_file (character) - Name output_file (store_network == TRUE). source_target (''|'') - Fetch interactions involving two considered tfs ('', default), one considered tfs element ('') multiplex_name (character) - Name multiplex add network . Default 'TF'. tf_network_name (character) - Name network multiplex add network . Default 'TF_network'. verbose (integer) - Display function messages. Set 0 message displayed, >= 1 details.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_tf_network.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute TF network and add it to hummus object — compute_tf_network","text":"(Hummus_Object) - Return hummus object new network added.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/compute_tf_network.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute TF network and add it to hummus object — compute_tf_network","text":"","code":"hummus <- compute_tf_network(hummus,                                        gene_assay = \"RNA\",                                        verbose = 1) #> Creating a fake TF network with all TFs connected to a fake node. #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/dMcast.html","id":null,"dir":"Reference","previous_headings":"","what":"Copy of the dMcast function from the Matrix.utils package, since this is off CRAN and does not seem to be maintained anymore internally — dMcast","title":"Copy of the dMcast function from the Matrix.utils package, since this is off CRAN and does not seem to be maintained anymore internally — dMcast","text":"Copy dMcast function Matrix.utils package, since CRAN seem maintained anymore internally","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/dMcast.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Copy of the dMcast function from the Matrix.utils package, since this is off CRAN and does not seem to be maintained anymore internally — dMcast","text":"","code":"dMcast(   data,   formula,   fun.aggregate = \"sum\",   value.var = NULL,   as.factors = FALSE,   factor.nas = TRUE,   drop.unused.levels = TRUE )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_binding_regions.html","id":null,"dir":"Reference","previous_headings":"","what":"Define binding_regions from hummus object — define_binding_regions","title":"Define binding_regions from hummus object — define_binding_regions","text":"Calling define_output function output_type = 'binding_regions'","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_binding_regions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Define binding_regions from hummus object — define_binding_regions","text":"","code":"define_binding_regions(   hummus_object,   multiplex_names = NULL,   bipartites_names = NULL,   config_name = \"binding_regions_config.yml\",   config_folder = \"config\",   tf_multiplex = \"TF\",   atac_multiplex = \"peaks\",   rna_multiplex = \"RNA\",   multilayer_f = \"multilayer\",   gene_list = NULL,   tf_list = NULL,   save = FALSE,   output_f = NULL,   return_df = TRUE,   suffix_bipartites = \".tsv\",   njobs = 1 )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_binding_regions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Define binding_regions from hummus object — define_binding_regions","text":"hummus_object hummus object multiplex_names vector multiplex names considered. must subset names multiplexes hummus object. bipartites_names vector bipartites names considered. must subset names bipartites hummus object. config_name name config file created hummuspy config_folder folder config file created tf_multiplex name multiplex containing TFs atac_multiplex name multiplex containing ATAC-seq peaks rna_multiplex name multiplex containing RNA-seq genes multilayer_f folder multilayer stored gene_list vector genes considered final binding regions (filtering done genes inferring binding_regions) tf_list vector TFs considered binding_regions (filtering done TFs inferring binding_regions) save boolean indicating binding_regions saved output_f name file binding_regions can saved (save == TRUE) return_df boolean indicating binding_regions returned dataframe suffix_bipartites suffix add bipartites names (indicate exact file location) njobs number jobs used computation binding_regions","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_binding_regions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Define binding_regions from hummus object — define_binding_regions","text":"dataframe containing binding_regions (return_df == TRUE)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_binding_regions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Define binding_regions from hummus object — define_binding_regions","text":"","code":"binding_regions <- define_binding_regions(hummus_object = hummus,                             multilayer_f = multilayer_folder,                             njobs = 5) #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_enhancers.html","id":null,"dir":"Reference","previous_headings":"","what":"Define enhancers from hummus object — define_enhancers","title":"Define enhancers from hummus object — define_enhancers","text":"Calling define_output function output_type = 'enhancers'","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_enhancers.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Define enhancers from hummus object — define_enhancers","text":"","code":"define_enhancers(   hummus_object,   multiplex_names = NULL,   bipartites_names = NULL,   config_name = \"enhancers_config.yml\",   config_folder = \"config\",   tf_multiplex = \"TF\",   atac_multiplex = \"peaks\",   rna_multiplex = \"RNA\",   multilayer_f = \"multilayer\",   gene_list = NULL,   tf_list = NULL,   save = FALSE,   output_f = NULL,   return_df = TRUE,   suffix_bipartites = \".tsv\",   njobs = 1 )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_enhancers.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Define enhancers from hummus object — define_enhancers","text":"hummus_object hummus object multiplex_names vector multiplex names considered. must subset names multiplexes hummus object. bipartites_names vector bipartites names considered. must subset names bipartites hummus object. config_name name config file created hummuspy config_folder folder config file created tf_multiplex name multiplex containing TFs atac_multiplex name multiplex containing ATAC-seq peaks rna_multiplex name multiplex containing RNA-seq genes multilayer_f folder multilayer stored gene_list vector genes considered final enhancers (filtering done genes inferring enhancers) tf_list vector TFs considered final enhancers (filtering done TFs inferring enhancers) save boolean indicating enhancers saved output_f name file enhancers saved (save == TRUE) return_df boolean indicating enhancers returned dataframe suffix_bipartites suffix add bipartites names (indicate exact file location) njobs number jobs used compute enhancers","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_enhancers.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Define enhancers from hummus object — define_enhancers","text":"dataframe containing enhancers (return_df == TRUE)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_enhancers.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Define enhancers from hummus object — define_enhancers","text":"","code":"enhancers <- define_enhancers(hummus_object = hummus,                             multilayer_f = multilayer_folder,                             njobs = 5) #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_general_config.html","id":null,"dir":"Reference","previous_headings":"","what":"Define general config file for hummuspy — define_general_config","title":"Define general config file for hummuspy — define_general_config","text":"Define general config file hummuspy","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_general_config.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Define general config file for hummuspy — define_general_config","text":"","code":"define_general_config(   hummus_object,   multiplex_names = NULL,   bipartites_names = NULL,   folder_multiplexes = \"multiplex\",   folder_bipartites = \"bipartites\",   seed_path = \"seed/seeds.txt\",   suffix = \".tsv\",   self_loops = FALSE,   restart_proba = 0.7,   save_configfile = FALSE,   config_name = \"config.yml\",   config_folder = \"config\",   multilayer_f = \"multilayer\",   suffix_bipartites = \".tsv\" )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_general_config.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Define general config file for hummuspy — define_general_config","text":"hummus_object hummus object multiplex_names vector multiplex names considered. must subset names multiplexes hummus object, NULL multiplexes considered. bipartites_names vector bipartites names considered. must subset names bipartites hummus object, NULL bipartites considered. folder_multiplexes folder multiplexes stored folder_bipartites folder bipartites stored seed_path path seed file self_loops boolean indicating self loops considered. restart_proba restart probability random walk (default = 0.7) save_configfile boolean indicating config file saved config_name name config file created hummuspy config_folder folder config file created (inside multilayer_f) multilayer_f folder multilayer stored suffix_bipartites suffix add bipartites names (indicate exact file name)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_general_config.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Define general config file for hummuspy — define_general_config","text":"config file hummuspy","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_grn.html","id":null,"dir":"Reference","previous_headings":"","what":"Define GRN from hummus object — define_grn","title":"Define GRN from hummus object — define_grn","text":"Calling define_output function output_type = 'GRN'","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_grn.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Define GRN from hummus object — define_grn","text":"","code":"define_grn(   hummus_object,   multiplex_names = NULL,   bipartites_names = NULL,   config_name = \"grn_config.yml\",   config_folder = \"config\",   tf_multiplex = \"TF\",   atac_multiplex = \"peaks\",   rna_multiplex = \"RNA\",   multilayer_f = \"multilayer\",   gene_list = NULL,   tf_list = NULL,   save = FALSE,   output_f = NULL,   return_df = TRUE,   suffix_bipartites = \".tsv\",   njobs = 1 )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_grn.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Define GRN from hummus object — define_grn","text":"hummus_object hummus object multiplex_names vector multiplex names considered. must subset names multiplexes hummus object. bipartites_names vector bipartites names considered. must subset names bipartites hummus object. config_name name config file created hummuspy config_folder folder config file created tf_multiplex name multiplex containing TFs atac_multiplex name multiplex containing ATAC-seq peaks rna_multiplex name multiplex containing RNA-seq genes multilayer_f folder multilayer stored gene_list vector genes considered final GRN (filtering done genes inferring GRN) tf_list vector TFs considered final GRN (filtering done TFs inferring GRN) save boolean indicating GRN saved output_f name file GRN saved (save == TRUE) return_df boolean indicating GRN returned dataframe suffix_bipartites suffix add bipartites names (indicate exact file location) njobs number jobs used computation GRN","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_grn.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Define GRN from hummus object — define_grn","text":"dataframe containing GRN (return_df == TRUE)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_grn.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Define GRN from hummus object — define_grn","text":"","code":"grn <- define_grn(hummus_object = hummus,                             multilayer_f = multilayer_folder,                             njobs = 5) #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_output.html","id":null,"dir":"Reference","previous_headings":"","what":"Define output from hummus object — define_output","title":"Define output from hummus object — define_output","text":"Define output hummus object","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_output.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Define output from hummus object — define_output","text":"","code":"define_output(   output_type,   hummus_object,   multiplex_names = NULL,   bipartites_names = NULL,   config_name = \"config.yml\",   config_folder = \"config\",   tf_multiplex = \"TF\",   atac_multiplex = \"peaks\",   rna_multiplex = \"RNA\",   multilayer_f = \"multilayer\",   gene_list = NULL,   tf_list = NULL,   save = FALSE,   output_f = NULL,   return_df = TRUE,   suffix_bipartites = \".tsv\",   njobs = 1 )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_output.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Define output from hummus object — define_output","text":"output_type type output defined hummus_object hummus object multiplex_names vector multiplex names considered. must subset names multiplexes hummus object. bipartites_names vector bipartites names considered. must subset names bipartites hummus object. config_name name config file created hummuspy config_folder folder config file created tf_multiplex name multiplex containing TFs atac_multiplex name multiplex containing ATAC-seq peaks rna_multiplex name multiplex containing RNA-seq genes multilayer_f folder multilayer stored gene_list vector genes considered target_genes (filtering done genes inferring target_genes) tf_list vector TFs considered final target_genes (filtering done TFs inferring target_genes) save boolean indicating target_genes saved output_f name file target_genes saved (save == TRUE) return_df boolean indicating target_genes returned dataframe suffix_bipartites suffix add bipartites names (indicate exact file location) njobs number jobs used compute target_genes","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_output.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Define output from hummus object — define_output","text":"dataframe containing target_genes (return_df == TRUE)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_output.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Define output from hummus object — define_output","text":"","code":"target_genes <- define_output('grn', hummus_object = hummus) #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_target_genes.html","id":null,"dir":"Reference","previous_headings":"","what":"Define target genes from hummus object — define_target_genes","title":"Define target genes from hummus object — define_target_genes","text":"Calling define_output function output_type = 'target_genes'","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_target_genes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Define target genes from hummus object — define_target_genes","text":"","code":"define_target_genes(   hummus_object,   multiplex_names = NULL,   bipartites_names = NULL,   config_name = \"target_genes_config.yml\",   config_folder = \"config\",   tf_multiplex = \"TF\",   atac_multiplex = \"peaks\",   rna_multiplex = \"RNA\",   multilayer_f = \"multilayer\",   gene_list = NULL,   tf_list = NULL,   save = FALSE,   output_f = NULL,   return_df = TRUE,   suffix_bipartites = \".tsv\",   njobs = 1 )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_target_genes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Define target genes from hummus object — define_target_genes","text":"hummus_object hummus object multiplex_names vector multiplex names considered. must subset names multiplexes hummus object. bipartites_names vector bipartites names considered. must subset names bipartites hummus object. config_name name config file created hummuspy config_folder folder config file created tf_multiplex name multiplex containing TFs atac_multiplex name multiplex containing ATAC-seq peaks rna_multiplex name multiplex containing RNA-seq genes multilayer_f folder multilayer stored gene_list vector genes considered target_genes (filtering done genes inferring target_genes) tf_list vector TFs considered final target_genes (filtering done TFs inferring target_genes) save boolean indicating target_genes saved output_f name file target_genes saved (save == TRUE) return_df boolean indicating target_genes returned dataframe suffix_bipartites suffix add bipartites names (indicate exact file location) njobs number jobs used compute target_genes","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_target_genes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Define target genes from hummus object — define_target_genes","text":"dataframe containing target_genes (return_df == TRUE)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/define_target_genes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Define target genes from hummus object — define_target_genes","text":"","code":"target_genes <- define_target_genes(hummus_object = hummus,                             multilayer_f = multilayer_folder,                             njobs = 5) #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/fast_aggregate.html","id":null,"dir":"Reference","previous_headings":"","what":"Copy of the aggregate.Matrix function from the Matrix.utils package, since this is off CRAN and does not seem to be maintained anymore internally — fast_aggregate","title":"Copy of the aggregate.Matrix function from the Matrix.utils package, since this is off CRAN and does not seem to be maintained anymore internally — fast_aggregate","text":"Copy aggregate.Matrix function Matrix.utils package, since CRAN seem maintained anymore internally","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/fast_aggregate.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Copy of the aggregate.Matrix function from the Matrix.utils package, since this is off CRAN and does not seem to be maintained anymore internally — fast_aggregate","text":"","code":"fast_aggregate(x, groupings = NULL, form = NULL, fun = \"sum\", ...)"},{"path":"https://cantinilab.github.io/HuMMuS/reference/find_peaks_near_genes.html","id":null,"dir":"Reference","previous_headings":"","what":"Associate peaks to genes based on distance to TSS (or gene body) — find_peaks_near_genes","title":"Associate peaks to genes based on distance to TSS (or gene body) — find_peaks_near_genes","text":"Associate peaks genes based distance TSS (gene body)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/find_peaks_near_genes.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Associate peaks to genes based on distance to TSS (or gene body) — find_peaks_near_genes","text":"","code":"find_peaks_near_genes(   peaks,   genes,   sep = c(\"-\", \"-\"),   method = c(\"Signac\", \"GREAT\"),   upstream = 1e+05,   downstream = 0,   extend = 1e+06,   only_tss = FALSE,   verbose = TRUE )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/find_peaks_near_genes.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Associate peaks to genes based on distance to TSS (or gene body) — find_peaks_near_genes","text":"peaks vector(character) - List peaks. genes vector(character) - List genes. sep vector(character) - Separator chromosome, start end position. Default: c('-', '-'). method (character) - Method use. Default: \"Signac\". 'Signac' - Use Signac::Extend extend genes. 'GREAT' - implemented yet. upstream (int) - Upstream distance TSS consider potential promoter. downstream (int) - Downstream distance TSS consider potential promoter. extend (int) - Integer defining distance upstream downstream basal regulatory region. Used method 'GREAT'. only_tss (logical) - TRUE, TSS considered. verbose (logical) - TRUE, print progress messages.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/find_peaks_near_genes.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Associate peaks to genes based on distance to TSS (or gene body) — find_peaks_near_genes","text":"(matrix) - Matrix peaks x genes 1 peak near gene.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/find_peaks_near_genes.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Associate peaks to genes based on distance to TSS (or gene body) — find_peaks_near_genes","text":"","code":"TODO #> Error in eval(expr, envir, enclos): object 'TODO' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/format_bipartites_names.html","id":null,"dir":"Reference","previous_headings":"","what":"Format bipartites names for python hummuspy package config functions — format_bipartites_names","title":"Format bipartites names for python hummuspy package config functions — format_bipartites_names","text":"Format bipartites names python hummuspy package config functions","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/format_bipartites_names.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format bipartites names for python hummuspy package config functions — format_bipartites_names","text":"","code":"format_bipartites_names(   hummus_object,   bipartites_names = NULL,   suffix_bipartites = \".tsv\" )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/format_bipartites_names.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format bipartites names for python hummuspy package config functions — format_bipartites_names","text":"hummus_object hummus object bipartites_names vector bipartites names considered. must subset names bipartites hummus object. suffix_bipartites suffix add bipartites location","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/format_bipartites_names.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format bipartites names for python hummuspy package config functions — format_bipartites_names","text":"list bipartites names formatted hummuspy config funtions element list list containing right left layer connected bipartite","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/format_bipartites_names.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format bipartites names for python hummuspy package config functions — format_bipartites_names","text":"","code":"bipartites_dictionary <- format_bipartites_names(                                       hummus_object = hummus,                                       bipartites_names = c(\"atac_rna\",                                                            \"tf_peaks\")) #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/format_multiplex_names.html","id":null,"dir":"Reference","previous_headings":"","what":"Format multiplex names for python hummuspy package config functions — format_multiplex_names","title":"Format multiplex names for python hummuspy package config functions — format_multiplex_names","text":"Format multiplex names python hummuspy package config functions","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/format_multiplex_names.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Format multiplex names for python hummuspy package config functions — format_multiplex_names","text":"","code":"format_multiplex_names(hummus_object, multiplex_names = NULL)"},{"path":"https://cantinilab.github.io/HuMMuS/reference/format_multiplex_names.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Format multiplex names for python hummuspy package config functions — format_multiplex_names","text":"hummus_object hummus object multiplex_names vector multiplex names considered. must subset names multiplexes hummus object.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/format_multiplex_names.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Format multiplex names for python hummuspy package config functions — format_multiplex_names","text":"list multiplexes names formatted hummuspy config funtions element list list network types (directed/weighted) name networks named hummus object","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/format_multiplex_names.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Format multiplex names for python hummuspy package config functions — format_multiplex_names","text":"","code":"multiplexes_dictionary <- format_multiplex_names(                                        hummus_object = hummus,                                        multiplex_names = c(\"TF\", \"peaks\")) #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_genome_annotations.html","id":null,"dir":"Reference","previous_headings":"","what":"Fetch online genome annotations from Ensembldb database — get_genome_annotations","title":"Fetch online genome annotations from Ensembldb database — get_genome_annotations","text":"Fetch online genome annotations Ensembldb database","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_genome_annotations.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fetch online genome annotations from Ensembldb database — get_genome_annotations","text":"","code":"get_genome_annotations(   ensdb_annotations = EnsDb.Hsapiens.v86::EnsDb.Hsapiens.v86 )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_genome_annotations.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fetch online genome annotations from Ensembldb database — get_genome_annotations","text":"EnsDb_annotations (EndsDb object) - Ensembldb database (default: EnsDb.Hsapiens.v86::EnsDb.Hsapiens.v86","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_genome_annotations.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fetch online genome annotations from Ensembldb database — get_genome_annotations","text":"gene_range (GRanges object) - Genome annotations","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_genome_annotations.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fetch online genome annotations from Ensembldb database — get_genome_annotations","text":"","code":"gene_range = get_genome_annotations(EnsDb.Hsapiens.v86::EnsDb.Hsapiens.v86) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.) #> Warning: The 2 combined objects have no sequence levels in common. (Use #>   suppressWarnings() to suppress this warning.)"},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_tf2motifs.html","id":null,"dir":"Reference","previous_headings":"","what":"Fetch online TF motifs from JASPAR2020 and chromVARmotifs — get_tf2motifs","title":"Fetch online TF motifs from JASPAR2020 and chromVARmotifs — get_tf2motifs","text":"Fetch online TF motifs JASPAR2020 chromVARmotifs","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_tf2motifs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fetch online TF motifs from JASPAR2020 and chromVARmotifs — get_tf2motifs","text":"","code":"get_tf2motifs(species = \"human\")"},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_tf2motifs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fetch online TF motifs from JASPAR2020 and chromVARmotifs — get_tf2motifs","text":"species (character) - Species name (default: \"human\")","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_tf2motifs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fetch online TF motifs from JASPAR2020 and chromVARmotifs — get_tf2motifs","text":"motifs_db (motifs_db object) - TF2motifs + motifs PWMs","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_tf2motifs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fetch online TF motifs from JASPAR2020 and chromVARmotifs — get_tf2motifs","text":"","code":"motifs_db = get_tf2motifs(species = \"human\")"},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_tfs.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract TF names from scRNA data and tf2motifs — get_tfs","title":"Extract TF names from scRNA data and tf2motifs — get_tfs","text":"Extract TF names scRNA data tf2motifs","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_tfs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract TF names from scRNA data and tf2motifs — get_tfs","text":"","code":"get_tfs(   hummus,   assay = NULL,   store_tfs = TRUE,   output_file = NULL,   verbose = 0 )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_tfs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract TF names from scRNA data and tf2motifs — get_tfs","text":"output_file (character) - Path output file. verbose (integer) - Verbosity level. Default: 1. species (character) - Species name. Default: \"human\". genes (vector(character)) - List expressed genes. tf2motifs (data.frame) - TF motifs names mapping. Columns: motif, tf.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/get_tfs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract TF names from scRNA data and tf2motifs — get_tfs","text":"TFs (vector(character)) - List TFs expressed motifs.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/motifs_db-class.html","id":null,"dir":"Reference","previous_headings":"","what":"Motifs database class — motifs_db-class","title":"Motifs database class — motifs_db-class","text":"MotifsDatabase object stores motifs(PFM matrices) tf2motifs (TF motifs names mapping) data.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/motifs_db-class.html","id":"slots","dir":"Reference","previous_headings":"","what":"Slots","title":"Motifs database class — motifs_db-class","text":"motifs (TFBSTools::PWMatrixList) - PFM matrices. tf2motifs (data.frame) - TF motif names mapping. Columns: motif, tf.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/multilayer-class.html","id":null,"dir":"Reference","previous_headings":"","what":"Multilayer class — multilayer-class","title":"Multilayer class — multilayer-class","text":"Multilayer object stores list bipartite networks list multiplex networks. can also stores config list create yaml file, used parametrize random walk restart explore multilayer.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/multilayer-class.html","id":"slots","dir":"Reference","previous_headings":"","what":"Slots","title":"Multilayer class — multilayer-class","text":"bipartites (list) - List bipartite networks multiplex (list) - List multiplex networks config (list) - List parameters parametrize random walk restart explore multilayer","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/multiplex-class.html","id":null,"dir":"Reference","previous_headings":"","what":"Multiplex class — multiplex-class","title":"Multiplex class — multiplex-class","text":"Multiplex object stores list networks, list features list logicals indicating network directed weighted.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/multiplex-class.html","id":"slots","dir":"Reference","previous_headings":"","what":"Slots","title":"Multiplex class — multiplex-class","text":"networks (list) - List networks. features (vector) - Vector features. directed (list) - List logical indicating networks directed. weighted (list) - List logical indicating networks weighted.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/peaks_in_regulatory_elements.html","id":null,"dir":"Reference","previous_headings":"","what":"Filter peaks to those overlapping specific (regulatory) elements — peaks_in_regulatory_elements","title":"Filter peaks to those overlapping specific (regulatory) elements — peaks_in_regulatory_elements","text":"Function reduce list \"Peaks\" ones overlapping list \"RegEl\", e.g. regulatory elements, evolutionary conserved regions","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/peaks_in_regulatory_elements.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Filter peaks to those overlapping specific (regulatory) elements — peaks_in_regulatory_elements","text":"","code":"peaks_in_regulatory_elements(   Peaks,   RegEl,   sep_Peak1 = \"-\",   sep_Peak2 = \"-\",   sep_RegEl1 = \"-\",   sep_RegEl2 = \"-\" )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/peaks_in_regulatory_elements.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Filter peaks to those overlapping specific (regulatory) elements — peaks_in_regulatory_elements","text":"Peaks (character) vector genomic coordinates peaks RegEl (character) vector genomic coordinates regulatory elements sep_Peak1 (character) separator chromosome start position peak sep_Peak2 (character) separator start position end position peak sep_RegEl1 (character) separator chromosome start position regulatory element sep_RegEl2 (character) separator start position end position regulatory element","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/peaks_in_regulatory_elements.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Filter peaks to those overlapping specific (regulatory) elements — peaks_in_regulatory_elements","text":"(character) vector genomic coordinates peaks overlapping","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/peaks_in_regulatory_elements.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Filter peaks to those overlapping specific (regulatory) elements — peaks_in_regulatory_elements","text":"","code":"peaks_in_regulatory_elements(peaks, RegEl) #> Error in eval(expr, envir, enclos): object 'peaks' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/run_cicero_wrapper.html","id":null,"dir":"Reference","previous_headings":"","what":"Cicero wrapper function for the compute_atac_peak_network function — run_cicero_wrapper","title":"Cicero wrapper function for the compute_atac_peak_network function — run_cicero_wrapper","text":"function wrapper compute_atac_peak_network function layers.R. computes peak network scATAC-seq data using Cicero. returns data frame peak network. data frame also contains coaccess score edge. coaccess score probability two peaks accessible cell. coaccess score computed Cicero. Edges filtered based coaccess score. edges coaccess score > threshold kept.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/run_cicero_wrapper.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Cicero wrapper function for the compute_atac_peak_network function — run_cicero_wrapper","text":"","code":"run_cicero_wrapper(   hummus,   atac_assay,   genome,   window,   number_cells_per_clusters,   sample_num,   seed,   verbose,   threshold,   reduction_method = \"UMAP\" )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/run_cicero_wrapper.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Cicero wrapper function for the compute_atac_peak_network function — run_cicero_wrapper","text":"hummus hummus object atac_assay name assay containing scATAC-seq data genome genome object window window size used Cicero compute coaccess score number_cells_per_clusters number cells per cluster used Cicero compute coaccess score sample_num number samples used Cicero compute coaccess score seed seed used Cicero compute coaccess score verbose verbosity level threshold threshold used filter edges based coaccess score reduction_method method used monocle3 reduce dimension scATAC-seq data defining pseudocells. default UMAP.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/run_cicero_wrapper.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Cicero wrapper function for the compute_atac_peak_network function — run_cicero_wrapper","text":"data frame containing peak network","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/run_tf_null_wrapper.html","id":null,"dir":"Reference","previous_headings":"","what":"tf_null wrapper function for the tf_network function — run_tf_null_wrapper","title":"tf_null wrapper function for the tf_network function — run_tf_null_wrapper","text":"function wrapper tf_network function","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/run_tf_null_wrapper.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"tf_null wrapper function for the tf_network function — run_tf_null_wrapper","text":"","code":"run_tf_null_wrapper(   hummus = hummus,   organism = organism,   tfs = tfs,   gene_assay = gene_assay,   verbose = 1 )"},{"path":"https://cantinilab.github.io/HuMMuS/reference/run_tf_null_wrapper.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"tf_null wrapper function for the tf_network function — run_tf_null_wrapper","text":"hummus hummus object","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/save_multilayer.html","id":null,"dir":"Reference","previous_headings":"","what":"Save multilayer object files in a hierarchical structure on disk — save_multilayer","title":"Save multilayer object files in a hierarchical structure on disk — save_multilayer","text":"Save multilayer files Hummus_Object hierarchical structure disk, inside folder specified folder_name","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/save_multilayer.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Save multilayer object files in a hierarchical structure on disk — save_multilayer","text":"","code":"save_multilayer(hummus, folder_name, verbose = TRUE, suffix = \".tsv\")"},{"path":"https://cantinilab.github.io/HuMMuS/reference/save_multilayer.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Save multilayer object files in a hierarchical structure on disk — save_multilayer","text":"hummus hummus object folder_name name folder save multilayer verbose (integer) - Display function messages. Set 0 message displayed, >= 1 details. suffix suffix files save. Default: \".tsv\"","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/save_multilayer.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Save multilayer object files in a hierarchical structure on disk — save_multilayer","text":"Nothing, create folder containing multilayer object files","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/save_multilayer.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Save multilayer object files in a hierarchical structure on disk — save_multilayer","text":"","code":"folder_name = \"multilayer\" save_multilayer(hummus = hummus, folder_name = \"multilayer\") #> Error in eval(expr, envir, enclos): object 'hummus' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/store_network.html","id":null,"dir":"Reference","previous_headings":"","what":"Wrapper function to save a network or not — store_network","title":"Wrapper function to save a network or not — store_network","text":"Wrapper function save network file according store_network parameter. store_network TRUE, network saved output_file.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/store_network.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Wrapper function to save a network or not — store_network","text":"","code":"store_network(network, store_network, output_file, verbose = 1)"},{"path":"https://cantinilab.github.io/HuMMuS/reference/store_network.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Wrapper function to save a network or not — store_network","text":"network network (edge list) store_network Logical indicating network saved output_file name file save network verbose (integer) - Display function messages. Set 0 message displayed, >= 1 details.","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/store_network.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Wrapper function to save a network or not — store_network","text":"Nothing, save network file store_network TRUE","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/store_network.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Wrapper function to save a network or not — store_network","text":"","code":"network <- read.table(\"network.tsv\", header = TRUE, sep = \"\\t\") #> Warning: cannot open file 'network.tsv': No such file or directory #> Error in file(file, \"rt\"): cannot open the connection           store_network(network = network,               store_network = TRUE,               output_file = \"network.tsv\",               verbose = 1) #> \tStoring network in file :  network.tsv  #> Error in eval(expr, envir, enclos): object 'network' not found"},{"path":"https://cantinilab.github.io/HuMMuS/reference/sub-subset-Hummus_Object.html","id":null,"dir":"Reference","previous_headings":"","what":"Access assays in Hummus_Object (based on Seurat) — [[<-,Hummus_Object","title":"Access assays in Hummus_Object (based on Seurat) — [[<-,Hummus_Object","text":"Access assays Hummus_Object (based Seurat)","code":""},{"path":"https://cantinilab.github.io/HuMMuS/reference/sub-subset-Hummus_Object.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Access assays in Hummus_Object (based on Seurat) — [[<-,Hummus_Object","text":"","code":"# S3 method for Hummus_Object [[(x, i = missing_arg(), ..., drop = FALSE, na.rm = FALSE)"}]