To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("eisa")

In most cases, you don't need to download the package archive at all.

eisa

This package is for version 3.4 of Bioconductor; for the stable, up-to-date release version, see eisa.

Expression data analysis via the Iterative Signature Algorithm

Bioconductor version: 3.4

The Iterative Signature Algorithm (ISA) is a biclustering method; it finds correlated blocks (transcription modules) in gene expression (or other tabular) data. The ISA is capable of finding overlapping modules and it is resilient to noise. This package provides a convenient interface to the ISA, using standard BioConductor data structures; and also contains various visualization tools that can be used with other biclustering algorithms.

Author: Gabor Csardi <csardi.gabor at gmail.com>

Maintainer: Gabor Csardi <csardi.gabor at gmail.com>

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

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("eisa")

Documentation

To view documentation for the version of this package installed in your system, start R and enter: 

browseVignettes("eisa")
PDF R Script The Iterative Signature Algorithm for Gene Expression Data
PDF Reference Manual

Details

biocViews Classification, GeneExpression, Microarray, Software, Visualization
Version 1.26.0
In Bioconductor since BioC 2.6 (R-2.11) (7 years)
License GPL (>= 2)
Depends isa2, Biobase(>= 2.17.8), AnnotationDbi, methods
Imports BiocGenerics, Category, genefilter, DBI
LinkingTo
Suggests igraph (>= 0.6), Matrix, GOstats, GO.db, KEGG.db, biclust, MASS, xtable, ALL, hgu95av2.db, targetscan.Hs.eg.db, org.Hs.eg.db
SystemRequirements
Enhances
URL
Depends On Me ExpressionView
Imports Me ExpressionView
Suggests Me
Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Package Source eisa_1.26.0.tar.gz
Windows Binary eisa_1.26.0.zip
Mac OS X 10.9 (Mavericks) eisa_1.26.0.tgz
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/eisa/tree/release-3.4
Package Short Url http://bioconductor.org/packages/eisa/
Package Downloads Report Download Stats

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