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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("pcaGoPromoter")
In most cases, you don't need to download the package archive at all.
pcaGoPromoter
pcaGoPromoter is used to analyze DNA micro array data
Bioconductor version: 2.14
This package contains functions to ease the analyses of DNA micro arrays. It utilizes principal component analysis as the initial multivariate analysis, followed by functional interpretation of the principal component dimensions with overrepresentation analysis for GO terms and regulatory interpretations using overrepresentation analysis of predicted transcription factor binding sites with the primo algorithm.
Author: Morten Hansen, Jorgen Olsen
Maintainer: Morten Hansen <mhansen at sund.ku.dk>
Citation (from within R,
enter citation("pcaGoPromoter")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("pcaGoPromoter")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("pcaGoPromoter")
| R Script | pcaGoPromoter | |
| Reference Manual |
Details
| biocViews | GO, GeneExpression, Microarray, Software, Visualization |
| Version | 1.8.0 |
| In Bioconductor since | BioC 2.10 (R-2.15) |
| License | GPL (>= 2) |
| Depends | R (>= 2.14.0), ellipse |
| Imports | Biobase(>= 2.10.0), AnnotationDbi |
| Suggests | Rgraphviz, GO.db, hgu133plus2.db, mouse4302.db, rat2302.db, hugene10sttranscriptcluster.db, mogene10sttranscriptcluster.db, Biostrings, pcaGoPromoter.Hs.hg19, pcaGoPromoter.Mm.mm9, pcaGoPromoter.Rn.rn4, serumStimulation, parallel |
| System Requirements | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | pcaGoPromoter_1.8.0.tar.gz |
| Windows Binary | pcaGoPromoter_1.8.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | pcaGoPromoter_1.8.0.tgz |
| Mac OS X 10.9 (Mavericks) | pcaGoPromoter_1.8.0.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
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