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

Motyer, Allan J.; McKendry, Chris; Galbraith, Sally; Wilson, Susan R.

Description

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.

CollectionsANU Research Publications
Date published: 2011-11-29
Type: Journal article
URI: http://hdl.handle.net/1885/95379
Source: BMC Proceedings
DOI: 10.1186/1753-6561-5-S9-S24

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