CREAL. Centre de Recerca en Epidemiologia Ambiental


Portada > Cercador de publicacions

TornarCercador de publicacions

De Lobel, L., Geurts, P., Baele, G., Castro-Giner, F., Kogevinas, M., Van Steen, K

A screening methodology based on Random Forests to improve the detection of gene-gene interactions

Eur.J.Hum.Genet., 2010, 18, 10, 1127, 32, IF: 3.925, PMID: 20461113

The search for susceptibility loci in gene-gene interactions imposes a methodological and computational challenge for statisticians because of the large dimensionality inherent to the modelling of gene-gene interactions or epistasis. In an era in which genome-wide scans have become relatively common, new powerful methods are required to handle the huge amount of feasible gene-gene interactions and to weed out false positives and negatives from these results. One solution to the dimensionality problem is to reduce data by preliminary screening of markers to select the best candidates for further analysis. Ideally, this screening step is statistically independent of the testing phase. Initially developed for small numbers of markers, the Multifactor Dimensionality Reduction (MDR) method is a nonparametric, model-free data reduction technique to associate sets of markers with optimal predictive properties to disease. In this study, we examine the power of MDR in larger data sets and compare it with other approaches that are able to identify gene-gene interactions. Under various interaction models (purely and not purely epistatic), we use a Random Forest (RF)-based prescreening method, before executing MDR, to improve its performance. We find that the power of MDR increases when noisy SNPs are first removed, by creating a collection of candidate markers with RFs. We validate our technique by extensive simulation studies and by application to asthma data from the European Committee of Respiratory Health Study II.European Journal of Human Genetics advance online publication, 12 May 2010; doi:10.1038/ejhg.2010.48


Imatge ilustrativa

ISGlobal - Campus Mar · Doctor Aiguader, 88 · E-08003 Barcelona · Tel +34 93 214 73 00 · Fax +34 93 214 73 02 · e-mail: RSS

Una iniciativa de:

Context científic: