Email updates

Keep up to date with the latest news and content from BMC Proceedings and BioMed Central.

This article is part of the supplement: Genetic Analysis Workshop 17: Unraveling Human Exome Data

Open Access Proceedings

LASSO model selection with post-processing for a genome-wide association study data set

Allan J Motyer1*, Chris McKendry1, Sally Galbraith12 and Susan R Wilson12

Author Affiliations

1 Prince of Wales Clinical School, University of New South Wales, New South Wales 2052, Australia

2 School of Mathematics and Statistics, University of New South Wales, New South Wales 2052, Australia

For all author emails, please log on.

BMC Proceedings 2011, 5(Suppl 9):S24  doi:10.1186/1753-6561-5-S9-S24

Published: 29 November 2011

Abstract

Model selection procedures for simultaneous analysis of all single-nucleotide polymorphisms in genome-wide association studies are most suitable for making full use of the data for a complex disease study. In this paper we consider a penalized regression using the LASSO procedure and show that post-processing of the penalized-regression results with subsequent stepwise selection may lead to improved identification of causal single-nucleotide polymorphisms.