Bioconductor version: Release (3.14)
The package generally provides methods for gene set enrichment analysis of high-throughput RNA-Seq data by integrating differential expression and splicing. It uses negative binomial distribution to model read count data, which accounts for sequencing biases and biological variation. Based on permutation tests, statistical significance can also be achieved regarding each gene's differential expression and splicing, respectively.
Author: Xi Wang <Xi.Wang at newcastle.edu.au>
Maintainer: Xi Wang <Xi.Wang at dkfz.de>
Citation (from within R,
enter citation("SeqGSEA")
):
To install this package, start R (version "4.1") and enter:
if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("SeqGSEA")
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("SeqGSEA")
R Script | Gene set enrichment analysis of RNA-Seq data with the SeqGSEA package | |
Reference Manual | ||
Text | NEWS |
biocViews | DifferentialExpression, DifferentialSplicing, GeneExpression, GeneSetEnrichment, ImmunoOncology, RNASeq, Sequencing, Software |
Version | 1.34.0 |
In Bioconductor since | BioC 2.12 (R-3.0) (9 years) |
License | GPL (>= 3) |
Depends | Biobase, doParallel, DESeq2 |
Imports | methods, biomaRt |
LinkingTo | |
Suggests | GenomicRanges |
SystemRequirements | |
Enhances | |
URL | |
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 | SeqGSEA_1.34.0.tar.gz |
Windows Binary | SeqGSEA_1.34.0.zip |
macOS 10.13 (High Sierra) | SeqGSEA_1.34.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/SeqGSEA |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/SeqGSEA |
Package Short Url | https://bioconductor.org/packages/SeqGSEA/ |
Package Downloads Report | Download Stats |
Old Source Packages for BioC 3.14 | Source Archive |
Documentation »
Bioconductor
R / CRAN packages and documentation
Support »
Please read the posting guide. Post questions about Bioconductor to one of the following locations: