Intertwining threshold settings, biological data and database knowledge to optimize the selection of differentially expressed genes from microarray.

ABSTRACT:

Background

Many tools used to analyze microarrays in different conditions have been described. However, the integration of deregulated genes within coherent metabolic pathways is lacking. Currently no objective selection criterion based on biological functions exists to determine a threshold demonstrating that a gene is indeed differentially expressed.

Methodology/principal findings

To improve transcriptomic analysis of microarrays, we propose a new statistical approach that takes into account biological parameters. We present an iterative method to optimise the selection of differentially expressed genes in two experimental conditions. The stringency level of gene selection was associated simultaneously with the p-value of expression variation and the occurrence rate parame

SUBMITTER: Chuchana P 

PROVIDER: S-EPMC2958130 | biostudies-literature | 2010 Oct

REPOSITORIES: biostudies-literature