DiffCoEx: a simple and sensitive method to find differentially coexpressed gene modules

Large microarray datasets have enabled gene regulation to be studied through coexpression analysis. While numerous methods have been developed for identifying differentially expressed genes between two conditions, the field of differential coexpression analysis is still relatively new. More specific...

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Bibliographic Details
Published in:BMC bioinformatics 2010-10, Vol.11 (1), p.497-497, Article 497
Main Authors: Tesson, Bruno M, Breitling, Rainer, Jansen, Ritsert C
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Animals
Clusters (Chemistry)
DNA microarrays
Gene expression
Gene Expression Profiling - methods
Gene Regulatory Networks - genetics
Genetic screening
Life sciences
Methodology
Methods
Oligonucleotide Array Sequence Analysis - methods
Pattern Recognition, Automated
Rats
Sensitivity and Specificity
Software
Studies
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Summary:Large microarray datasets have enabled gene regulation to be studied through coexpression analysis. While numerous methods have been developed for identifying differentially expressed genes between two conditions, the field of differential coexpression analysis is still relatively new. More specifically, there is so far no sensitive and untargeted method to identify gene modules (also known as gene sets or clusters) that are differentially coexpressed between two conditions. Here, sensitive and untargeted means that the method should be able to construct de novo modules by grouping genes based on shared, but subtle, differential correlation patterns. We present DiffCoEx, a novel method for identifying correlation pattern changes, which builds on the commonly used Weighted Gene Coexpression Network Analysis (WGCNA) framework for coexpression analysis. We demonstrate its usefulness by identifying biologically relevant, differentially coexpressed modules in a rat cancer dataset. DiffCoEx is a simple and sensitive method to identify gene coexpression differences between multiple conditions.
ISSN:1471-2105
1471-2105
DOI:10.1186/1471-2105-11-497