Title: Comprehensive detection of cancer gene expression profiles and gene networks are impacted by the choice of pre-processing algorithm and gene-selection method

Authors: N. Baskaran; Chee Keong Kwoh; Kam M. Hui

Addresses: Bek Chai Heah Laboratory of Cancer Genomics, Division of Cellular and Molecular Research, Humphrey Oei Institute of Cancer Research, National Cancer Centre, 11 Hospital Drive, Singapore 169610, Singapore ' Division of Information Systems, School of Computer Engineering, Nanyang Technological University, Nanyang Avenue 639798, Singapore ' Bek Chai Heah Laboratory of Cancer Genomics, Division of Cellular and Molecular Research, Humphrey Oei Institute of Cancer Research, National Cancer Centre, 11 Hospital Drive, Singapore 169610, Singapore

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 gene-networks; hence the initial choice of PPA and GSM is crucial for subsequent interactome investigations.

Keywords: bioinformatics; cancer detection; cancer gene expression profiles; data mining; differentially expressed genes; gene selection; gene networks; interactome; microarrays; pre-processing algorithms; tumor segregation.

DOI: 10.1504/IJDMB.2013.054228

International Journal of Data Mining and Bioinformatics, 2013 Vol.7 No.4, pp.416 - 435

Received: 13 Oct 2011
Accepted: 13 Oct 2011
Published online: 20 Oct 2014 *

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