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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("oposSOM")
In most cases, you don't need to download the package archive at all.
oposSOM
Comprehensive analysis of transciptome data
Bioconductor version: 3.0
This package translates microarray expression data into metadata of reduced dimension. It provides various sample-centered and group-centered visualizations, sample similarity analyses and functional enrichment analyses. The underlying SOM algorithm combines feature clustering, multidimensional scaling and dimension reduction, along with strong visualization capabilities. It enables extraction and description of functional expression modules inherent in the data.
Author: Henry Wirth <wirth at izbi.uni-leipzig.de> and Martin Kalcher <mkalcher at porkbox.net>
Maintainer: Henry Wirth <wirth at izbi.uni-leipzig.de>
Citation (from within R,
enter citation("oposSOM")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("oposSOM")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("oposSOM")
| R Script | oposSOM Example | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | DataRepresentation, DifferentialExpression, GeneExpression, GeneSetEnrichment, Software, Visualization |
| Version | 1.1.1 |
| In Bioconductor since | BioC 3.0 (R-3.1) |
| License | GPL (>=2) |
| Depends | R (>= 3.0) |
| Imports | som, fastICA, scatterplot3d, pixmap, fdrtool, ape, igraph, KernSmooth, parallel, biomaRt, Biobase |
| LinkingTo | |
| Suggests | |
| SystemRequirements | |
| Enhances | |
| URL | http://som.izbi.uni-leipzig.de |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | oposSOM_1.1.1.tar.gz |
| Windows Binary | oposSOM_1.1.1.zip |
| Mac OS X 10.6 (Snow Leopard) | oposSOM_1.1.1.tgz |
| Mac OS X 10.9 (Mavericks) | oposSOM_1.1.1.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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