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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("MineICA")
In most cases, you don't need to download the package archive at all.
MineICA
Analysis of an ICA decomposition obtained on genomics data
Bioconductor version: 3.0
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>
Citation (from within R,
enter citation("MineICA")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("MineICA")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("MineICA")
| R Script | MineICA: Independent component analysis of genomic data | |
| Reference Manual |
Details
| biocViews | MultipleComparison, Software, Visualization |
| Version | 1.6.0 |
| 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 |
| LinkingTo | |
| Suggests | biomaRt, GOstats, cluster, hgu133a.db, mclust, igraph, breastCancerMAINZ, breastCancerTRANSBIG, breastCancerUPP, breastCancerVDX |
| SystemRequirements | |
| Enhances | doMC |
| 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 | MineICA_1.6.0.tar.gz |
| Windows Binary | MineICA_1.6.0.zip |
| Mac OS X 10.6 (Snow Leopard) | MineICA_1.6.0.tgz |
| Mac OS X 10.9 (Mavericks) | MineICA_1.6.0.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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