Modular analysis of gene expression data with R.

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Serval ID
serval:BIB_2D3E82E26A25
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Modular analysis of gene expression data with R.
Journal
Bioinformatics
Author(s)
Csárdi G., Kutalik Z., Bergmann S.
ISSN
1367-4811[electronic], 1367-4803[linking]
Publication state
Published
Issued date
2010
Volume
26
Number
10
Pages
1376-1377
Language
english
Notes
Publication types: Journal Article ; Research Support, Non-U.S. Gov't Publication Status: ppublish
Abstract
SUMMARY: Large sets of data, such as expression profiles from many samples, require analytic tools to reduce their complexity. The Iterative Signature Algorithm (ISA) is a biclustering algorithm. It was designed to decompose a large set of data into so-called 'modules'. In the context of gene expression data, these modules consist of subsets of genes that exhibit a coherent expression profile only over a subset of microarray experiments. Genes and arrays may be attributed to multiple modules and the level of required coherence can be varied resulting in different 'resolutions' of the modular mapping. In this short note, we introduce two BioConductor software packages written in GNU R: The isa2 package includes an optimized implementation of the ISA and the eisa package provides a convenient interface to run the ISA, visualize its output and put the biclusters into biological context. Potential users of these packages are all R and BioConductor users dealing with tabular (e.g. gene expression) data. AVAILABILITY: http://www.unil.ch/cbg/ISA CONTACT: sven.bergmann@unil.ch
Keywords
Microarray Data
Pubmed
Web of science
Open Access
Yes
Create date
28/05/2010 11:00
Last modification date
25/09/2019 6:08
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