Identification of metagenes and their interactions through large-scale analysis of Arabidopsis gene expression data.

ABSTRACT:

Background

Many plant genes have been identified through whole genome and deep transcriptome sequencing and other methods; yet our knowledge on the function of many of these genes remains limited. The integration and analysis of large gene-expression datasets gives researchers the ability to formalize hypotheses concerning the functionality and interaction between different groups of correlated genes.

Results

We applied the non-negative matrix factorization (NMF) algorithm to the AtGenExpress dataset which consists of 783 microarray samples (29 separate experimental series) conducted on the model plant Arabidopsis thaliana. We identified 15 metagenes, which are groups of genes with correlated expression. Functional roles of these metagenes are established by observing the en

SUBMITTER: Wilson TJ 

PROVIDER: S-EPMC3536586 | biostudies-literature | 2012 Jun

REPOSITORIES: biostudies-literature