updated functionalities

.Rbuildignore

@@ -6,3 +6,4 @@
 ^pkgdown$
 ^README\.Rmd$
 ^\.github$
+^codecov\.yml$

.github/workflows/test-coverage.yaml

@@ -0,0 +1,50 @@
+# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples
+# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
+on:
+  push:
+    branches: [main, master]
+  pull_request:
+    branches: [main, master]
+
+name: test-coverage
+
+jobs:
+  test-coverage:
+    runs-on: ubuntu-latest
+    env:
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: r-lib/actions/setup-r@v2
+        with:
+          use-public-rspm: true
+
+      - uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          extra-packages: any::covr
+          needs: coverage
+
+      - name: Test coverage
+        run: |
+          covr::codecov(
+            quiet = FALSE,
+            clean = FALSE,
+            install_path = file.path(normalizePath(Sys.getenv("RUNNER_TEMP"), winslash = "/"), "package")
+          )
+        shell: Rscript {0}
+
+      - name: Show testthat output
+        if: always()
+        run: |
+          ## --------------------------------------------------------------------
+          find '${{ runner.temp }}/package' -name 'testthat.Rout*' -exec cat '{}' \; || true
+        shell: bash
+
+      - name: Upload test results
+        if: failure()
+        uses: actions/upload-artifact@v4
+        with:
+          name: coverage-test-failures
+          path: ${{ runner.temp }}/package

DESCRIPTION

@@ -15,7 +15,11 @@ Imports:
     magrittr,
     rlang,
     stats,
-    tidyr
+    tidyr,
+    ggplot2,
+    igraph,
+    RColorBrewer,
+    Biostrings
 Depends: 
     R (>= 2.10)
 LazyData: true

NAMESPACE

@@ -1,10 +1,21 @@
 # Generated by roxygen2: do not edit by hand
 
 export("%>%")
+export(MDT_boxplot)
+export(buildIsoNet)
 export(find_csmdts)
 export(find_mdts)
+export(plotExpression)
+export(prepare_Seq)
 export(remove_redundants)
 export(switch_calculator)
+export(visualize_network)
+import(data.table)
+import(ggplot2)
+import(igraph)
+importFrom(Biostrings,readDNAStringSet)
+importFrom(RColorBrewer,brewer.pal)
+importFrom(dplyr,across)
 importFrom(dplyr,arrange)
 importFrom(dplyr,count)
 importFrom(dplyr,desc)
@@ -14,7 +25,12 @@ importFrom(dplyr,filter)
 importFrom(dplyr,group_by)
 importFrom(dplyr,mutate)
 importFrom(dplyr,n)
+importFrom(dplyr,pull)
 importFrom(dplyr,select)
+importFrom(dplyr,summarise)
+importFrom(dplyr,summarize)
+importFrom(dplyr,ungroup)
+importFrom(ggplot2,geom_boxplot)
 importFrom(magrittr,"%>%")
 importFrom(rlang,.data)
 importFrom(stats,median)

README.Rmd

@@ -1,62 +1,62 @@
 ---
 output: github_document
 ---
+#
 
-# MDTToolset
-
-## THIS R PACKAGE IS CURRENTLY UNDER DEVELOPMENT
+## MDTToolset
 
+### THIS R PACKAGE IS CURRENTLY UNDER DEVELOPMENT
 
+### Overview
 The [R](https://www.r-project.org) package **MDTToolset** is designed to calculate the **M**ost **D**ominant **T**ranscript
-and their switches in the RNA-Seq datasets. It can;
-
-- remove redundant transcripts that has the same protein sequences, and
-  sum up their transcript counts.
-- calculate Most dominant transcripts in RNA-Seq data with flexible cutoffs (e.g
-  user-defined transcript expression cutoff and enrichment cutoff)
-- calculate MDTs found in user-defined percentage of samples
-- calculate MDT Switching events with flexible cutoffs (e.g. user-defined cutoffs)
-- integrate isoform interaction network with the MDT switches to understand their functional impact on protein interaction network
-
+and their switches in the RNA-Seq datasets. It enables users to:
 
-## Installation
-
-You can install the development version of MDTToolset from [GitHub](https://github.com/KarakulakTulay/MDTToolset) with:
+- Remove redundant transcripts with identical protein sequences and aggregate their transcript counts.
+- Calculate the most dominant transcripts in RNA-Seq data using flexible cutoffs, such as user-defined transcript expression and enrichment cutoffs.
+- Identify MDTs present in a user-defined percentage of samples.
+- Calculate MDT Switching events with flexible user-defined cutoffs.
+- Integrate the isoform interaction network with the MDT switches to understand their functional impact on the protein interaction network.
+- Visualize the expression of MDTs and disease-specific MDTs (dMDTs).
+- Visualize the network of dMDTs.
 
 
-``` r
-# install.packages("devtools")
-devtools::install_github("KarakulakTulay/MDTToolset")
-```
 
-## Background
+### Background
 
 Alternative splicing plays an essential role in development, tissue specificity and 
 essential cell functions. One gene can encode for many transcripts, one of those transcripts
 might be expressed at a significantly higher level than the other transcripts. These transcripts are 
 defined as most dominant transcripts (MDTs). In cancer, those canonical MDTs might be switched to 
-other transcripts which we call MDT switching event. This R package aims to find the MDTs in RNA-seq data
+other transcripts which we call MDT switching event. The *MDTToolset* aims to find the MDTs in RNA-seq data
 and evaluated the MDT switching event in a flexible user-defined way. The user can define cutoffs for 
 the transcript expression, and MDT enrichment. 
 
 
-## Example
+### How to Install
+
+You can install the development version of MDTToolset from [GitHub](https://github.com/KarakulakTulay/MDTToolset) with:
 
-```{r example}
-library(MDTToolset)
-## basic example code
 
+``` r
+# install.packages("devtools")
+devtools::install_github("KarakulakTulay/MDTToolset")
 ```
 
+### Vignettes
 
-## Documentation
+Please find a comprehensive workflow to MDTToolset in the [vignette](https://karakulaktulay.github.io/MDTToolset/articles/MDTToolset-vignette.html).
+
+
+### Documentation
 
 The HTML documentation of the latest version is available at
 [GitHub](https://github.com/KarakulakTulay/MDTToolset).
 
 
-## Credits
+### Credits
 
 The idea behind `MDTToolset` was developed by Abdullah Kahraman, and the original 
 perl codes for the calculation of MDTs and their switches can be found [here](https://github.com/abxka/CanIsoNet).
 
+
+

README.md

@@ -1,59 +1,62 @@
 
-# MDTToolset
+# 
 
-## THIS R PACKAGE IS CURRENTLY UNDER DEVELOPMENT
+## MDTToolset
 
-The [R](https://www.r-project.org) package **MDTToolset** is designed to
-calculate the **M**ost **D**ominant **T**ranscript and their switches in
-the RNA-Seq datasets. It can;
-
-- remove redundant transcripts that has the same protein sequences, and
-  sum up their transcript counts.
-- calculate Most dominant transcripts in RNA-Seq data with flexible
-  cutoffs (e.g user-defined transcript expression cutoff and enrichment
-  cutoff)
-- calculate MDTs found in user-defined percentage of samples
-- calculate MDT Switching events with flexible cutoffs
-  (e.g. user-defined cutoffs)
-- integrate isoform interaction network with the MDT switches to
-  understand their functional impact on protein interaction network
-
-## Installation
-
-You can install the development version of MDTToolset from
-[GitHub](https://github.com/KarakulakTulay/MDTToolset) with:
+### THIS R PACKAGE IS CURRENTLY UNDER DEVELOPMENT
 
-``` r
-# install.packages("devtools")
-devtools::install_github("KarakulakTulay/MDTToolset")
-```
+### Overview
 
-## Background
+The [R](https://www.r-project.org) package **MDTToolset** is designed to
+calculate the **M**ost **D**ominant **T**ranscript and their switches in
+the RNA-Seq datasets. It enables users to:
+
+- Remove redundant transcripts with identical protein sequences and
+  aggregate their transcript counts.
+- Calculate the most dominant transcripts in RNA-Seq data using flexible
+  cutoffs, such as user-defined transcript expression and enrichment
+  cutoffs.
+- Identify MDTs present in a user-defined percentage of samples.
+- Calculate MDT Switching events with flexible user-defined cutoffs.
+- Integrate the isoform interaction network with the MDT switches to
+  understand their functional impact on the protein interaction network.
+- Visualize the expression of MDTs and disease-specific MDTs (dMDTs).
+- Visualize the network of dMDTs.
+
+### Background
 
 Alternative splicing plays an essential role in development, tissue
 specificity and essential cell functions. One gene can encode for many
 transcripts, one of those transcripts might be expressed at a
 significantly higher level than the other transcripts. These transcripts
 are defined as most dominant transcripts (MDTs). In cancer, those
 canonical MDTs might be switched to other transcripts which we call MDT
-switching event. This R package aims to find the MDTs in RNA-seq data
+switching event. The *MDTToolset* aims to find the MDTs in RNA-seq data
 and evaluated the MDT switching event in a flexible user-defined way.
 The user can define cutoffs for the transcript expression, and MDT
 enrichment.
 
-## Example
+### How to Install
+
+You can install the development version of MDTToolset from
+[GitHub](https://github.com/KarakulakTulay/MDTToolset) with:
 
 ``` r
-library(MDTToolset)
-## basic example code
+# install.packages("devtools")
+devtools::install_github("KarakulakTulay/MDTToolset")
 ```
 
-## Documentation
+### Vignettes
+
+Please find a comprehensive workflow to MDTToolset in the
+[vignette](https://karakulaktulay.github.io/MDTToolset/articles/MDTToolset-vignette.html).
+
+### Documentation
 
 The HTML documentation of the latest version is available at
 [GitHub](https://github.com/KarakulakTulay/MDTToolset).
 
-## Credits
+### Credits
 
 The idea behind `MDTToolset` was developed by Abdullah Kahraman, and the
 original perl codes for the calculation of MDTs and their switches can

_pkgdown.yml

@@ -1,4 +1,7 @@
-url: ~
+url: https://karakulaktulay.github.io/MDTToolset/
 template:
   bootstrap: 5
-
+  params:
+    bootswatch: sandstone
+development:
+  mode: auto

codecov.yml

@@ -0,0 +1,14 @@
+comment: false
+
+coverage:
+  status:
+    project:
+      default:
+        target: auto
+        threshold: 1%
+        informational: true
+    patch:
+      default:
+        target: auto
+        threshold: 1%
+        informational: true