IBBiG: iterative binary bi-clustering of gene sets.

ABSTRACT:

Motivation

Meta-analysis of genomics data seeks to identify genes associated with a biological phenotype across multiple datasets; however, merging data from different platforms by their features (genes) is challenging. Meta-analysis using functionally or biologically characterized gene sets simplifies data integration is biologically intuitive and is seen as having great potential, but is an emerging field with few established statistical methods.

Results

We transform gene expression profiles into binary gene set profiles by discretizing results of gene set enrichment analyses and apply a new iterative bi-clustering algorithm (iBBiG) to identify groups of gene sets that are coordinately associated with groups of phenotypes across multiple studies. iBBiG is optimized for met

SUBMITTER: Gusenleitner D 

PROVIDER: S-EPMC3463116 | biostudies-literature | 2012 Oct

REPOSITORIES: biostudies-literature