To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("pcot2")
In most cases, you don't need to download the package archive at all.
pcot2
Principal Coordinates and Hotelling's T-Square method
Bioconductor version: 3.0
PCOT2 is a permutation-based method for investigating changes in the activity of multi-gene networks. It utilizes inter-gene correlation information to detect significant alterations in gene network activities. Currently it can be applied to two-sample comparisons.
Author: Sarah Song, Mik Black
Maintainer: Sarah Song <qson003 at stat.auckland.ac.nz>
Citation (from within R,
enter citation("pcot2")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("pcot2")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("pcot2")
| R Script | PCOT2 Vignette | |
| Reference Manual |
Details
| biocViews | DifferentialExpression, Microarray, Software |
| Version | 1.34.0 |
| In Bioconductor since | BioC 1.9 (R-2.4) |
| License | GPL (>= 2) |
| Depends | R (>= 2.0.0), grDevices, Biobase, amap |
| Imports | |
| LinkingTo | |
| Suggests | multtest, hu6800.db, KEGG.db, mvtnorm |
| 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 | pcot2_1.34.0.tar.gz |
| Windows Binary | pcot2_1.34.0.zip |
| Mac OS X 10.6 (Snow Leopard) | pcot2_1.34.0.tgz |
| Mac OS X 10.9 (Mavericks) | pcot2_1.34.0.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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