FABIA: factor analysis for bicluster acquisition.

ABSTRACT:

Motivation

Biclustering of transcriptomic data groups genes and samples simultaneously. It is emerging as a standard tool for extracting knowledge from gene expression measurements. We propose a novel generative approach for biclustering called 'FABIA: Factor Analysis for Bicluster Acquisition'. FABIA is based on a multiplicative model, which accounts for linear dependencies between gene expression and conditions, and also captures heavy-tailed distributions as observed in real-world transcriptomic data. The generative framework allows to utilize well-founded model selection methods and to apply Bayesian techniques.

Results

On 100 simulated datasets with known true, artificially implanted biclusters, FABIA clearly outperformed all 11 competitors. On these datasets, FABIA was

SUBMITTER: Hochreiter S 

PROVIDER: S-EPMC2881408 | biostudies-literature | 2010 Jun

REPOSITORIES: biostudies-literature