decoupleR

R package to infer biological activities from omics data using a collection of methods.

https://github.com/saezlab/decoupler

Science Score: 36.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
  • DOI references
    Found 2 DOI reference(s) in README
  • Academic publication links
  • Committers with academic emails
    2 of 16 committers (12.5%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (17.4%) to scientific vocabulary

Keywords

r r-package rstats

Keywords from Contributors

proteomics bioconductor ontology transcriptomics phosphoproteomics network-modelling metabolomic-data data-integration multiview molecular-biology
Last synced: 10 months ago · JSON representation

Repository

R package to infer biological activities from omics data using a collection of methods.

Basic Info
Statistics
  • Stars: 261
  • Watchers: 4
  • Forks: 26
  • Open Issues: 15
  • Releases: 0
Topics
r r-package rstats
Created over 6 years ago · Last pushed over 1 year ago
Metadata Files
Readme Changelog License

README.Rmd

---
output: github_document
---



```{r, include = FALSE}
knitr::opts_chunk$set(
    collapse = TRUE,
    comment = "#>",
    fig.path = "man/figures/README-",
    out.width = "100%"
)
```

# decoupleR 


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[![BioC dev status](http://www.bioconductor.org/shields/build/devel/bioc/decoupleR.svg)](https://bioconductor.org/checkResults/devel/bioc-LATEST/decoupleR)
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## Overview

There are many methods that allow us to extract biological activities from omics data. 
`decoupleR` is a Bioconductor package containing different statistical methods to 
extract biological signatures from prior knowledge within a unified framework.
Additionally, it incorporates methods that take into account the sign and weight of 
network interactions. `decoupleR` can be used with any omic, as long as its 
features can be linked to a biological process based on prior knowledge. 
For example, in transcriptomics gene sets regulated by a transcription 
factor, or in phospho-proteomics phosphosites that are targeted by a kinase.
This is the R version, for its faster and memory efficient Python implementation go [here](https://decoupler-py.readthedocs.io/en/latest/).

For more information about how this package has been used with real data, please check the following links: - [decoupleR's general usage](https://saezlab.github.io/decoupleR/articles/decoupleR.html) - [Pathway activity inference in bulk RNA-seq](https://saezlab.github.io/decoupleR/articles/pw_bk.html) - [Pathway activity inference from scRNA-seq](https://saezlab.github.io/decoupleR/articles/pw_sc.html) - [Transcription factor activity inference in bulk RNA-seq](https://saezlab.github.io/decoupleR/articles/tf_bk.html) - [Transcription factor activity inference from scRNA-seq](https://saezlab.github.io/decoupleR/articles/tf_sc.html) - [Example of Kinase and TF activity estimation](https://saezlab.github.io/kinase_tf_mini_tuto/) - [decoupleR's manuscript repository](https://github.com/saezlab/decoupleR_manuscript) - [Python implementation](https://decoupler-py.readthedocs.io/en/latest/) # Installation `decoupleR` is an R package distributed as part of the Bioconductor project. To install the package, start R and enter: ```{r bioconductor_install, eval=FALSE} install.packages("BiocManager") BiocManager::install("decoupleR") ``` Alternatively, you can instead install the latest development version from [GitHub](https://github.com/) with: ```{r github_install, eval=FALSE} BiocManager::install("saezlab/decoupleR") ``` ## License Footprint methods inside `decoupleR` can be used for academic or commercial purposes, except `viper` which holds a non-commercial license. The data redistributed by `OmniPath` does not have a license, each original resource carries their own. [Here](https://omnipathdb.org/info) one can find the license information of all the resources in `OmniPath`. ## Citation Badia-i-Mompel P., Vélez Santiago J., Braunger J., Geiss C., Dimitrov D., Müller-Dott S., Taus P., Dugourd A., Holland C.H., Ramirez Flores R.O. and Saez-Rodriguez J. 2022. decoupleR: ensemble of computational methods to infer biological activities from omics data. Bioinformatics Advances. https://doi.org/10.1093/bioadv/vbac016

Owner

  • Name: Saez Lab
  • Login: saezlab
  • Kind: organization
  • Email: pub.saez@uni-heidelberg.de
  • Location: Germany

Institute for Computational Biomedicine - Julio Saez-Rodriguez's group

GitHub Events

Total
  • Commit comment event: 1
  • Issues event: 42
  • Watch event: 64
  • Issue comment event: 63
  • Push event: 5
  • Pull request event: 4
  • Fork event: 2
Last Year
  • Commit comment event: 1
  • Issues event: 42
  • Watch event: 64
  • Issue comment event: 63
  • Push event: 5
  • Pull request event: 4
  • Fork event: 2

Committers

Last synced: about 1 year ago

All Time
  • Total Commits: 692
  • Total Committers: 16
  • Avg Commits per committer: 43.25
  • Development Distribution Score (DDS): 0.652
Past Year
  • Commits: 10
  • Committers: 3
  • Avg Commits per committer: 3.333
  • Development Distribution Score (DDS): 0.2
Top Committers
Name Email Commits
Jesús Vélez Santiago j****z@l****x 241
PauBadiaM p****l@g****m 227
Christian c****8@g****m 96
deeenes t****s@g****m 59
petrsh p****s@c****z 22
enblacar e****6@g****m 8
Nitesh Turaga n****a@g****m 6
J Wokaty j****y@s****u 6
Ricardo Ramirez r****z@l****x 6
Petr Taus 5****h 5
fanzheng10 f****1@g****m 4
Sophia Müller-Dott s****d@h****e 4
Attila Gabor g****7@g****m 3
adugourd a****d@b****e 3
Christina Schmidt c****1@o****e 1
GitHub Actions a****s@g****m 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 10 months ago

All Time
  • Total issues: 114
  • Total pull requests: 46
  • Average time to close issues: about 1 month
  • Average time to close pull requests: 29 days
  • Total issue authors: 99
  • Total pull request authors: 12
  • Average comments per issue: 1.89
  • Average comments per pull request: 0.22
  • Merged pull requests: 38
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 32
  • Pull requests: 3
  • Average time to close issues: 29 days
  • Average time to close pull requests: about 1 hour
  • Issue authors: 30
  • Pull request authors: 2
  • Average comments per issue: 0.66
  • Average comments per pull request: 0.0
  • Merged pull requests: 2
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • kiwipeel (5)
  • adugourd (3)
  • ZZQ-1117 (2)
  • Chengwei94 (2)
  • roskcl (2)
  • kasayadior (2)
  • deeenes (2)
  • imerelli (2)
  • t1nnenissen (2)
  • harimchun (2)
  • christianholland (2)
  • EJeremy12 (1)
  • DuruTuncer (1)
  • charlotteboys (1)
  • akramdi (1)
Pull Request Authors
  • jvelezmagic (15)
  • PauBadiaM (13)
  • dbdimitrov (5)
  • smuellerd (3)
  • ChristinaSchmidt1 (2)
  • adugourd (2)
  • gabora (1)
  • christianholland (1)
  • sebrauschert (1)
  • enblacar (1)
  • fanzheng10 (1)
  • roramirezf (1)
Top Labels
Issue Labels
question (14) database/omnipath (7) enhancement (5) bug (5)
Pull Request Labels
enhancement (5) documentation (4) bug (1)

Packages

  • Total packages: 3
  • Total downloads:
    • bioconductor 57,720 total
  • Total dependent packages: 3
    (may contain duplicates)
  • Total dependent repositories: 0
    (may contain duplicates)
  • Total versions: 14
  • Total maintainers: 1
proxy.golang.org: github.com/saezlab/decoupleR
  • Versions: 4
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.4%
Average: 5.6%
Dependent repos count: 5.8%
Last synced: 11 months ago
proxy.golang.org: github.com/saezlab/decoupler
  • Versions: 4
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.4%
Average: 5.6%
Dependent repos count: 5.8%
Last synced: 11 months ago
bioconductor.org: decoupleR

decoupleR: Ensemble of computational methods to infer biological activities from omics data

  • Versions: 6
  • Dependent Packages: 3
  • Dependent Repositories: 0
  • Downloads: 57,720 Total
Rankings
Dependent repos count: 0.0%
Dependent packages count: 0.0%
Average: 15.9%
Downloads: 47.6%
Maintainers (1)
Last synced: 11 months ago

Dependencies

DESCRIPTION cran
  • R >= 4.0 depends
  • Matrix * imports
  • broom * imports
  • dplyr * imports
  • magrittr * imports
  • purrr * imports
  • rlang * imports
  • stats * imports
  • stringr * imports
  • tibble * imports
  • tidyr * imports
  • tidyselect * imports
  • withr * imports
  • AUCell * suggests
  • BiocStyle * suggests
  • GSVA * suggests
  • OmnipathR * suggests
  • RefManageR * suggests
  • Seurat * suggests
  • SummarizedExperiment * suggests
  • covr * suggests
  • fgsea >= 1.15.4 suggests
  • ggplot2 * suggests
  • ggrepel * suggests
  • glmnet >= 4.1.0 suggests
  • knitr * suggests
  • patchwork * suggests
  • pheatmap * suggests
  • pkgdown * suggests
  • ranger * suggests
  • rmarkdown * suggests
  • roxygen2 * suggests
  • rpart * suggests
  • sessioninfo * suggests
  • testthat * suggests
  • viper * suggests
.github/workflows/check-bioc.yml actions
  • actions/cache v2 composite
  • actions/checkout v2 composite
  • actions/upload-artifact master composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite