A powerful and efficient set test for genetic markers that handles confounders

Motivation: Approaches for testing sets of variants, such as a set of rare or common variants within a gene or pathway, for association with complex traits are important. In particular, set tests allow for aggregation of weak signal within a set, can capture interplay among variants and reduce the b...

Full description

Bibliographic Details
Main Authors:	Listgarten, Jennifer, Lippert, Christoph, Kang, Eun Yong, Xiang, Jing, Kadie, Carl M., Heckerman, David
Format:	Online
Language:	English
Published:	Oxford University Press 2013
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3673214/

id	pubmed-3673214
recordtype	oai_dc
spelling	pubmed-36732142013-06-05 A powerful and efficient set test for genetic markers that handles confounders Listgarten, Jennifer Lippert, Christoph Kang, Eun Yong Xiang, Jing Kadie, Carl M. Heckerman, David Original Papers Motivation: Approaches for testing sets of variants, such as a set of rare or common variants within a gene or pathway, for association with complex traits are important. In particular, set tests allow for aggregation of weak signal within a set, can capture interplay among variants and reduce the burden of multiple hypothesis testing. Until now, these approaches did not address confounding by family relatedness and population structure, a problem that is becoming more important as larger datasets are used to increase power. Oxford University Press 2013-06-15 2013-04-18 /pmc/articles/PMC3673214/ /pubmed/23599503 http://dx.doi.org/10.1093/bioinformatics/btt177 Text en © The Author 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Listgarten, Jennifer Lippert, Christoph Kang, Eun Yong Xiang, Jing Kadie, Carl M. Heckerman, David
spellingShingle	Listgarten, Jennifer Lippert, Christoph Kang, Eun Yong Xiang, Jing Kadie, Carl M. Heckerman, David A powerful and efficient set test for genetic markers that handles confounders
author_facet	Listgarten, Jennifer Lippert, Christoph Kang, Eun Yong Xiang, Jing Kadie, Carl M. Heckerman, David
author_sort	Listgarten, Jennifer
title	A powerful and efficient set test for genetic markers that handles confounders
title_short	A powerful and efficient set test for genetic markers that handles confounders
title_full	A powerful and efficient set test for genetic markers that handles confounders
title_fullStr	A powerful and efficient set test for genetic markers that handles confounders
title_full_unstemmed	A powerful and efficient set test for genetic markers that handles confounders
title_sort	powerful and efficient set test for genetic markers that handles confounders
description	Motivation: Approaches for testing sets of variants, such as a set of rare or common variants within a gene or pathway, for association with complex traits are important. In particular, set tests allow for aggregation of weak signal within a set, can capture interplay among variants and reduce the burden of multiple hypothesis testing. Until now, these approaches did not address confounding by family relatedness and population structure, a problem that is becoming more important as larger datasets are used to increase power.
publisher	Oxford University Press
publishDate	2013
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3673214/
_version_	1611983891415957504

A powerful and efficient set test for genetic markers that handles confounders

Similar Items