Exploring the transcription factor activity in high-throughput gene expression data using RLQ analysis.

ABSTRACT:

Background

Interpretation of gene expression microarray data in the light of external information on both columns and rows (experimental variables and gene annotations) facilitates the extraction of pertinent information hidden in these complex data. Biologists classically interpret genes of interest after retrieving functional information from a subset of genes of interest. Transcription factors play an important role in orchestrating the regulation of gene expression. Their activity can be deduced by examining the presence of putative transcription factors binding sites in the gene promoter regions.

Results

In this paper we present the multivariate statistical method RLQ which aims to analyze microarray data where additional information is available on both genes and sampl

SUBMITTER: Baty F 

PROVIDER: S-EPMC3686578 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature