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bio-la authored Feb 9, 2024
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165 changes: 161 additions & 4 deletions .gitignore
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dist/
panpipes/__pycache__
# Byte-compiled / optimized / DLL files
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# C extensions
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19 changes: 0 additions & 19 deletions .readthedocs.yaml
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# .readthedocs.yaml
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43 changes: 22 additions & 21 deletions CHANGELOG.md
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Releases
===========

# Changelog

## [latest]

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## v0.4.1

### added

- added example multiome submission file 10X_h5
- added example multiome submission file cellranger
- workflows & tutorials for `qc_spatial`, `preprocess_spatial`, and `deconvolution_spatial` to readthedocs
- tutorial for `vis`
- added PCA parameters in pipeline_preprocess.py for PROT modality to fix issue #120
- added full control of dimred params for all modalities in pipeline_preprocess.py
- more info on custom genes format files added to documentation
- parsing summary files for cellranger multi version < 7
- parsing summary files for cellranger multi version < 7
- added checks for n_pcs in run_neighbors_method_choice
- added filtering by HVF for atac


### fixed

- changed typo in tutorial paths for clustering and deconvolution
- fix io to read cellranger outs folder for atac.
- fixes to refmap workflow
- fix io to read cellranger outs folder for atac.
- fixes to refmap workflow
- typos & capitalization in the pipeline.yml files of `qc_spatial`, `preprocess_spatial`, and `deconvolution_spatial`, `vis`
- remove `assay`, `sample_prefix`, and `modalities` parameters from the `qc_spatial` pipeline.yml
- remove `assay`, `sample_prefix`, and `modalities` parameters from the `qc_spatial` pipeline.yml
- remove `sample_prefix` and `modalities` parameters from the `preprocess_spatial` pipeline.yml
- fixed error in `preprocess_spatial` when `filtering: run: False`
-> now able to run no filtering without needing to save the MuData in `filtered.data` before running the pipeline
- fixed error in `vis`
- change PARAMS['custom_markers_minimal'] -> PARAMS['custom_markers']['files']['minimal']
- change PARAMS['custom_markers_minimal'] -> PARAMS['custom_markers']['files']['minimal']
- fix to avoid rerunning HVF and explicitly check X layer before normalization in pipeline_preprocess.py
- fix plotting of umaps after batch correction
- fix fetching string scvi if present in mudata for wnn
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- fixed filtering HVG for rna
- moved pynndescent to PyPi dependencies


### dependencies

## v0.4.0

Big Change! the submission files for the `ingest` workflow have now changed! we require the paths to the Gene expression (RNA/GEX) and Protein (ADT) to have the following headers.


| sample_id | rna_path | rna_filetype | prot_path | prot_filetype |
| --------- | ----------- | ------------ | ------------ | ------------- |
| sampleX | path/to/rna | 10X_h5 | path/to/prot | 10x_h5 |
| | | | | |


See tutorials for examples of submission files.


### added

- merged PR #111:
- LSI in panpipes_preprocess is run on the highly variable features
- n_comp for LSI

### fixed

- changed all instances of ADT into PROT
- changed all instances of GEX to RNA
- changed the params to fix plotting as mentioned in issue #41
- typo in readme
- set default seaborn <=0.12.2 to avoid issue #104, #126

### dependencies

## v0.3.1
- set default matplotlib<=3.7.3 to avoid issue #104.

- set default matplotlib<=3.7.3 to avoid issue #104.

## v0.3.0

### added

- Spatial data analysis is now included in panpipes
- panpipes qc_spatial
- panpipes preprocess_spatial
- panpipes_deconvolution_spatial
- panpipes qc_spatial
- panpipes preprocess_spatial
- panpipes_deconvolution_spatial

### fixed

- make sure columns from individual modalities that are not in the multimodal outer obs can be used to

### dependencies

- additional dependencies: squidpy, cell2location, openpyxl

## v0.2.0
- First public version of panpipes
- contains qc_mm, preprocess, intergration, clustering


- First public version of panpipes
- contains qc_mm, preprocess, intergration, clustering
56 changes: 31 additions & 25 deletions README.md
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[![PyPI version](https://badge.fury.io/py/panpipes.svg)](https://badge.fury.io/py/panpipes)
# Panpipes - multimodal single cell pipelines

Created and Maintained by Charlotte Rich-Griffin and Fabiola Curion
Additional contributors: Sarah Ouologuem, Devika Agarwal, and Tom Thomas
# Panpipes - multimodal single cell pipelines

## Overview

**See our [documentation](https://panpipes-pipelines.readthedocs.io/en/latest/) and our [preprint](https://www.biorxiv.org/content/10.1101/2023.03.11.532085v1)**:
Panpipes: a pipeline for multiomic single-cell data analysis
Charlotte Rich-Griffin*, Fabiola Curion*, Tom Thomas, Devika Agarwal, Fabian J. Theis, Calliope A. Dendrou.
bioRxiv 2023.03.11.532085;
doi: https://doi.org/10.1101/2023.03.11.532085
Panpipes is a set of computational workflows designed to automate multimodal single-cell and spatial transcriptomic analyses by incorporating widely-used Python-based tools to perform quality control, preprocessing, integration, clustering, and reference mapping at scale.
Panpipes allows reliable and customisable analysis and evaluation of individual and integrated modalities, thereby empowering decision-making before downstream investigations.

**See our [documentation](https://panpipes-pipelines.readthedocs.io/en/latest/) and our [preprint](https://www.biorxiv.org/content/10.1101/2023.03.11.532085v2)**:

# Introduction
These workflows use cgat-core pipeline software
These workflows make use of [cgat-core](https://github.com/cgat-developers/cgat-core):

Available workflows:
1. "ingest" : for the ingestion of data and computation of QC metrics
2. "preprocess" : for filtering and normalising of each modality
3. "integration" : integrate and batch correction using single and multimodal methods
4. "clustering" : cell clustering on single modalities
5. "refmap" : transfer scvi-tools models from published data to your data
6. "vis" : visualize metrics from other pipelines in the context of experiment metadata
7. "qc_spatial" : for the ingestion of spatial transcriptomics (ST) data (Vizgen, Visium) and computation of QC metrics
8. "preprocess_spatial" : for filtering and normalizing ST data
9. "deconvolution_spatial" : for the cell type deconvolution of ST slides


# Installation and configuration
See [installation instructions here](https://panpipes-pipelines.readthedocs.io/en/latest/install.html)

1. "ingest" : Ingest data and compute quality control metrics
2. "preprocess" : Filter and normalize per modality
3. "integration" : Integrate and batch correct using single and multimodal methods
4. "clustering" : Cluster cells per modality
5. "refmap" : Map queries against reference datasets
6. "vis" : Visualize metrics from other pipelines in the context of experiment metadata
7. "qc_spatial" : Ingest spatial transcriptomics data (Vizgen, Visium) and compute quality control metrics
8. "preprocess_spatial" : Filtering and normalize spatial transcriptomics data
9. "deconvolution_spatial" : Deconvolve cell types of spatial transcriptomics slides

## Installation and configuration

See [installation instructions here](https://panpipes-pipelines.readthedocs.io/en/latest/install.html)

Oxford BMRC Rescomp users find additional advice in [docs/installation_rescomp](https://github.com/DendrouLab/panpipes/blob/main/docs/installation_rescomp.md)

# Releases
## Releases

`panpipes v0.4.0` is out [now](./CHANGELOG.md)!
`panpipes v0.4.0` is out [now](./CHANGELOG.md)!

The `ingest` workflow now expects different headers for the RNA and Protein modalities.
Check the example [submission file](https://github.com/DendrouLab/panpipes/blob/main/docs/usage/sample_file_qc_mm.md) and the [documentation](https://panpipes-pipelines.readthedocs.io/en/latest/usage/setup_for_qc_mm.html) for more detailed instructions.

## Citation

[Panpipes: a pipeline for multiomic single-cell and spatial transcriptomic data analysis
Fabiola Curion, Charlotte Rich-Griffin, Devika Agarwal, Sarah Ouologuem, Tom Thomas, Fabian J. Theis, Calliope A. Dendrou
bioRxiv 2023.03.11.532085; doi: https://doi.org/10.1101/2023.03.11.532085](https://www.biorxiv.org/content/10.1101/2023.03.11.532085v2)

## Contributors

Created and Maintained by Charlotte Rich-Griffin and Fabiola Curion.
Additional contributors: Sarah Ouologuem, Devika Agarwal, Lilly May, Kevin Rue-Albrecht.
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