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

ABSTRACT: Background: Many tools used to analyze microarrays in different conditions have been described. However, the integration of the 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, which takes into account biological parameters. We present an iterative method to optimise the selection of differentially expressed gene in two experimental conditions. The stringency level of gene selection was associated simultaneously with the p-value of expression variation and the occurrence rate parameter, w

ORGANISM(S): Homo sapiens

SUBMITTER: Paul Chuchana 

PROVIDER: E-GEOD-22858 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress