This package is for version 3.13 of Bioconductor; for the stable, up-to-date release version, see decoupleR.
Bioconductor version: 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>
Citation (from within R,
enter citation("decoupleR")
):
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.
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 |
Reference Manual | ||
Text | NEWS |
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 |
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 |
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