To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("mvGST")
In most cases, you don't need to download the package archive at all.
mvGST
Multivariate and directional gene set testing
Bioconductor version: 3.0
mvGST provides platform-independent tools to identify GO terms (gene sets) that are differentially active (up or down) in multiple contrasts of interest. Given a matrix of one-sided p-values (rows for genes, columns for contrasts), mvGST uses meta-analytic methods to combine p-values for all genes annotated to each gene set, and then classify each gene set as being significantly more active (1), less active (-1), or not significantly differentially active (0) in each contrast of interest. With multiple contrasts of interest, each gene set is assigned to a profile (across contrasts) of differential activity. Tools are also provided for visualizing (in a GO graph) the gene sets classified to a given profile.
Author: John R. Stevens and Dennis S. Mecham
Maintainer: John R. Stevens <john.r.stevens at usu.edu>
Citation (from within R,
enter citation("mvGST")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("mvGST")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("mvGST")
| R Script | mvGST Tutorial Vignette | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | DifferentialExpression, GO, GeneSetEnrichment, GraphAndNetwork, Microarray, OneChannel, Pathways, RNASeq, Software |
| Version | 1.0.0 |
| In Bioconductor since | BioC 3.0 (R-3.1) |
| License | GPL-3 |
| Depends | R (>= 2.10.0), GO.db, Rgraphviz |
| Imports | gProfileR, stringr, topGO, GOstats, annotate, AnnotationDbi, graph |
| LinkingTo | |
| Suggests | hgu133plus2.db, org.Hs.eg.db |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | mvGST_1.0.0.tar.gz |
| Windows Binary | mvGST_1.0.0.zip |
| Mac OS X 10.6 (Snow Leopard) | mvGST_1.0.0.tgz |
| Mac OS X 10.9 (Mavericks) | mvGST_1.0.0.tgz |
| Browse/checkout source | (username/password: readonly) |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Counting Reads for Differential Expression (parathyroideSE vignette)
- Annotation
- Annotating Variants
- Annotating Ranges
- Flow Cytometry and other assays
- Candidate Binding Sites for Known Transcription Factors
- Cloud-enabled cis-eQTL search and annotation
- RNA-Seq workflow: gene-level exploratory analysis and differential expression
- Changing genomic coordinate systems with rtracklayer::liftOver
- Mass spectrometry and proteomics data analysis
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