To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("PGSEA")
In most cases, you don't need to download the package archive at all.
PGSEA
Parametric Gene Set Enrichment Analysis
Bioconductor version: 3.0
Parametric Analysis of Gene Set Enrichment
Author: Kyle Furge <kyle.furge at vai.org> and Karl Dykema <karl.dykema at vai.org>
Maintainer: Karl Dykema <karl.dykema at vai.org>
Citation (from within R,
enter citation("PGSEA")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("PGSEA")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("PGSEA")
| R Script | HOWTO: PGSEA | |
| R Script | HOWTO: PGSEA Example Workflow | |
| Reference Manual |
Details
| biocViews | Microarray, Software |
| Version | 1.40.0 |
| In Bioconductor since | BioC 2.0 (R-2.5) |
| License | GPL-2 |
| Depends | R (>= 2.10), GO.db, KEGG.db, AnnotationDbi, annaffy, methods, Biobase(>= 2.5.5) |
| Imports | |
| LinkingTo | |
| Suggests | GSEABase, GEOquery, org.Hs.eg.db, hgu95av2.db, limma |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | GeneExpressionSignature |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | PGSEA_1.40.0.tar.gz |
| Windows Binary | PGSEA_1.40.0.zip |
| Mac OS X 10.6 (Snow Leopard) | PGSEA_1.40.0.tgz |
| Mac OS X 10.9 (Mavericks) | PGSEA_1.40.0.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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