Differential Expression Analysis for Pathways

• DOI: 10.1371/journal.pcbi.1002967
• Publication Date: 2013-03-14T23:40:29Z
• Authors: Winston A. Haynes; Roger Higdon; Larissa Stanberry; Dwayne Collins; Eugene Kolker
• Keywords: Biological pathway; Expression (computer science)

Life science technologies generate a deluge of data that hold the keys to unlocking secrets important biological functions and disease mechanisms. We present DEAP, Differential Expression Analysis for Pathways, which capitalizes on information about pathways identify regulatory patterns from differential expression data. DEAP makes significant improvements over existing approaches by including pathway structure discovering most differentially expressed portion pathway. On simulated data, significantly outperformed traditional methods: with high expression, increased power two orders magnitude; very low doubled power. performance was illustrated different gene protein studies. discovered fourteen related chronic obstructive pulmonary interferon treatment omitted. study, guided focus towards four path within 26 Notch signalling