MineICA

Analysis of an ICA decomposition obtained on genomics data

Bioconductor version: Release (2.14)

The goal of MineICA is to perform Independent Component Analysis (ICA) on multiple transcriptome datasets, integrating additional data (e.g molecular, clinical and pathological). This Integrative ICA helps the biological interpretation of the components by studying their association with variables (e.g sample annotations) and gene sets, and enables the comparison of components from different datasets using correlation-based graph.

Author: Anne Biton

Maintainer: Anne Biton <anne.biton at gmail.com>

To install this package, start R and enter:

source("http://bioconductor.org/biocLite.R")
biocLite("MineICA")

Citation (from within R, enter citation("MineICA")):

Documentation

PDF R Script MineICA: Independent component analysis of genomic data
PDF   Reference Manual

Details

biocViews MultipleComparison, Software, Visualizations
Version 1.4.0
In Bioconductor since BioC 2.12 (R-3.0)
License GPL-2
Depends R (>= 2.10), Biobase, plyr, ggplot2, scales, foreach, xtable, biomaRt, gtools, GOstats, cluster, marray, mclust, RColorBrewer, colorspace, igraph, Rgraphviz, graph, annotate, Hmisc, fastICA, JADE, methods
Imports AnnotationDbi, lumi, fpc, lumiHumanAll.db
Suggests biomaRt, GOstats, cluster, hgu133a.db, mclust, igraph, breastCancerMAINZ, breastCancerTRANSBIG, breastCancerUPP, breastCancerVDX
System Requirements
URL
Depends On Me
Imports Me
Suggests Me

Package Downloads

Package Source MineICA_1.4.0.tar.gz
Windows Binary MineICA_1.4.0.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard) MineICA_1.4.0.tgz
Mac OS X 10.9 (Mavericks) MineICA_1.4.0.tgz
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