To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("pvac")
In most cases, you don't need to download the package archive at all.
pvac
PCA-based gene filtering for Affymetrix arrays
Bioconductor version: 3.0
The package contains the function for filtering genes by the proportion of variation accounted for by the first principal component (PVAC).
Author: Jun Lu and Pierre R. Bushel
Maintainer: Jun Lu <jlu276 at gmail.com>, Pierre R. Bushel <bushel at niehs.nih.gov>
Citation (from within R,
enter citation("pvac")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("pvac")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("pvac")
| R Script | PCA-based gene filtering for Affymetrix GeneChips | |
| Reference Manual |
Details
| biocViews | Microarray, OneChannel, QualityControl, Software |
| Version | 1.14.0 |
| In Bioconductor since | BioC 2.8 (R-2.13) |
| License | LGPL (>= 2.0) |
| Depends | R (>= 2.8.0) |
| Imports | affy(>= 1.20.0), stats, Biobase |
| LinkingTo | |
| Suggests | pbapply, affydata, ALLMLL, genefilter |
| 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 | pvac_1.14.0.tar.gz |
| Windows Binary | pvac_1.14.0.zip |
| Mac OS X 10.6 (Snow Leopard) | pvac_1.14.0.tgz |
| Mac OS X 10.9 (Mavericks) | pvac_1.14.0.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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