Human gene correlation analysis (HGCA): a tool for the identification of transcriptionally co-expressed genes.

ABSTRACT:

Background

Bioinformatics and high-throughput technologies such as microarray studies allow the measure of the expression levels of large numbers of genes simultaneously, thus helping us to understand the molecular mechanisms of various biological processes in a cell.

Findings

We calculate the Pearson Correlation Coefficient (r-value) between probe set signal values from Affymetrix Human Genome Microarray samples and cluster the human genes according to the r-value correlation matrix using the Neighbour Joining (NJ) clustering method. A hyper-geometric distribution is applied on the text annotations of the probe sets to quantify the term overrepresentations. The aim of the tool is the identification of closely correlated genes for a given gene of interest and/or the predicti

SUBMITTER: Michalopoulos I 

PROVIDER: S-EPMC3441226 | biostudies-literature | 2012 Jun

REPOSITORIES: biostudies-literature