To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("eisa")
In most cases, you don't need to download the package archive at all.
eisa
Expression data analysis via the Iterative Signature Algorithm
Bioconductor version: 3.0
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:
source("http://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")
| R Script | The eisa and the biclust packages | |
| R Script | The Iterative Signature Algorithm for Gene Expression Data | |
| Reference Manual |
Details
| biocViews | Classification, GeneExpression, Microarray, Software, Visualization |
| Version | 1.18.0 |
| In Bioconductor since | BioC 2.6 (R-2.11) |
| 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_1.18.0.tar.gz |
| Windows Binary | eisa_1.18.0.zip |
| Mac OS X 10.6 (Snow Leopard) | eisa_1.18.0.tgz |
| Mac OS X 10.9 (Mavericks) | eisa_1.18.0.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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