Comprehensive detection of cancer gene expression profiles and gene networks are impacted by the choice of pre-processing algorithm and gene-selection method. (1st January 2013)

• Record Type: Journal Article
• Authors: Baskaran, N.; Kwoh, Chee Keong; Hui, Kam M.
• Is Part Of: International journal of data mining and bioinformatics. Volume 7:Number 4(2013)
• Page Start: 416
• Page End: 435
• Publication Date: 2013-01-01
• Subjects: bioinformatics -- cancer -- data-mining -- differentially expressed genes -- gene-selection methods -- gene-networks -- interactome -- microarray -- pre-processing algorithms; Data mining -- Periodicals; Bioinformatics -- Periodicals; 006.312
• Languages: English
• ISSNs: 1748-5673

Abstract

Pre-processing algorithms (PPA) and gene-selection methods (GSM) are commonly employed to select Differentially Expressed Genes (DEGs) from microarray data. Previous studies established that different combinations of PPAs and GSMs are intrinsically different in their performance to select biologically relevant DEGs. In this study, we evaluated eight combinations of PPAs and GSMs for their ability to select DEGs for prioritising gene-networks. Although the different combinations yielded dissimilar DEG-lists, all DEG-lists selected could segregate tumour from normal. Nevertheless, the DEG-list selected significantly impacted the prioritisation of cancer-associated genenetworks; hence the initial choice of PPA and GSM is crucial for subsequent interactome investigations.