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

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-...

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Detalles Bibliográficos
Autores principales: Motyer, Allan J, McKendry, Chris, Galbraith, Sally, Wilson, Susan R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Proceedings
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287859/
https://www.ncbi.nlm.nih.gov/pubmed/22373266
http://dx.doi.org/10.1186/1753-6561-5-S9-S24
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author Motyer, Allan J
McKendry, Chris
Galbraith, Sally
Wilson, Susan R
author_facet Motyer, Allan J
McKendry, Chris
Galbraith, Sally
Wilson, Susan R
author_sort Motyer, Allan J
collection PubMed
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.
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spelling pubmed-32878592012-02-28 LASSO model selection with post-processing for a genome-wide association study data set Motyer, Allan J McKendry, Chris Galbraith, Sally Wilson, Susan R BMC Proc Proceedings 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. BioMed Central 2011-11-29 /pmc/articles/PMC3287859/ /pubmed/22373266 http://dx.doi.org/10.1186/1753-6561-5-S9-S24 Text en Copyright ©2011 Motyer et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Proceedings
Motyer, Allan J
McKendry, Chris
Galbraith, Sally
Wilson, Susan R
LASSO model selection with post-processing for a genome-wide association study data set
title LASSO model selection with post-processing for a genome-wide association study data set
title_full LASSO model selection with post-processing for a genome-wide association study data set
title_fullStr LASSO model selection with post-processing for a genome-wide association study data set
title_full_unstemmed LASSO model selection with post-processing for a genome-wide association study data set
title_short LASSO model selection with post-processing for a genome-wide association study data set
title_sort lasso model selection with post-processing for a genome-wide association study data set
topic Proceedings
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287859/
https://www.ncbi.nlm.nih.gov/pubmed/22373266
http://dx.doi.org/10.1186/1753-6561-5-S9-S24
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AT wilsonsusanr lassomodelselectionwithpostprocessingforagenomewideassociationstudydataset

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