Authors: Tapia, Elizabeth; Bulacio, Pilar; Angelone, Laura.
Title: Microarray signal-to-noise ratio vs. false genes selection with SVM-RFE: A Simulation Study.
Resumen: We present the results of a simulation study about SVM-RFE gene selection onmicroarray datasets with different signal-to-noise ratios (S2Ns). It is shown thatthe extent to which SVM-RFE gene selection is affected by noise depends on theactual S2N and the policy of gene removal. For less expensive SVM-RFE implemen-tations removing a constant fraction of remaining genes per step, low S2N leads tothe selection of handy and repetitive sets of genes with low rates of false discover-ies. Conversely, for native SVM-RFE implementations removing a single gene perstep, a handful -but non-repetitive- set of genes with null rates of false discoveriesare selected. Furthermore, optimum classification performance requires an adaptedpolicy of gene removal: the lower S2N, the better less expensive SVM-RFE imple-mentations of gene selection. These findings may explain recent results about thesuboptimal classification performance of native SVM-RFE gene selection on somereal microarray datasets.We conclude that one should be very careful when drawingconclusions from microarray studies based on SVM-RFE gene selection.
Meeting type: Simposio.
Type of job: Otro.
Production: Microarray signal-to-noise ratio vs. false genes selection with SVM-RFE: A Simulation Study.
Scientific meeting: Quinta Reunión de la Red Iberoamericana de Bioinformática, 2008.
Meeting place: Santiago de Chile.
Organizing Institution: Pontificia Universidad Catlica de Chile.
It's published?: Yes
Publication place: Santiago de Chile
Meeting month: 12