decoupleR

DOI: 10.18129/B9.bioc.decoupleR    

Package to decouple gene sets from statistics

Bioconductor version: Release (3.13)

Transcriptome profiling followed by differential gene expression analysis often leads to lists of genes that are hard to analyze and interpret. Downstream analysis tools can be used to summarize deregulation events into a smaller set of biologically interpretable features. In particular, methods that estimate the activity of transcription factors (TFs) from gene expression are commonly used. It has been shown that the transcriptional targets of a TF yield a much more robust estimation of the TF activity than observing the expression of the TF itself. Consequently, for the estimation of transcription factor activities, a network of transcriptional regulation is required in combination with a statistical algorithm that summarizes the expression of the target genes into a single activity score. Over the years, many different regulatory networks and statistical algorithms have been developed, mostly in a fixed combination of one network and one algorithm. To systematically evaluate both networks and algorithms, we developed decoupleR , an R package that allows users to apply efficiently any combination provided.

Author: Jesús Vélez [cre, aut] , Christian H. Holland [aut]

Maintainer: Jesús Vélez <jvelezmagic at gmail.com>

Installation

To install this package, start R (version "4.1") and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("decoupleR")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("decoupleR")

 

HTML	R Script	Introduction to decoupleR
PDF		Reference Manual
Text		NEWS

Details

biocViews	DifferentialExpression, FunctionalGenomics, GeneExpression, GeneRegulation, Network, Software, StatisticalMethod, Transcription
Version	1.0.0
In Bioconductor since	BioC 3.13 (R-4.1) (< 6 months)
License	GPL-3
Depends	R (>= 4.0)
Imports	broom, dplyr, GSVA, magrittr, Matrix, purrr, rlang, speedglm, stats, stringr, tibble, tidyr, tidyselect, viper, withr
LinkingTo
Suggests	BiocStyle, covr, knitr, pkgdown, RefManageR, rmarkdown, roxygen2, sessioninfo, testthat
SystemRequirements
Enhances
URL	https://saezlab.github.io/decoupleR/
BugReports	https://github.com/saezlab/decoupleR/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	decoupleR_1.0.0.tar.gz
Windows Binary	decoupleR_1.0.0.zip
macOS 10.13 (High Sierra)	decoupleR_1.0.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/decoupleR
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/decoupleR
Package Short Url	https://bioconductor.org/packages/decoupleR/
Package Downloads Report	Download Stats