A SUPER powerful method for genome wide association study.

Genome-Wide Association Studies shed light on the identification of genes underlying human diseases and agriculturally important traits. This potential has been shadowed by false positive findings. The Mixed Linear Model (MLM) method is flexible enough to simultaneously incorporate population struct...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Qishan Wang, Feng Tian, Yuchun Pan, Edward S Buckler, Zhiwu Zhang
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/a61d335cbab042e5a605128026822fd5
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:a61d335cbab042e5a605128026822fd5
record_format	dspace
spelling	oai:doaj.org-article:a61d335cbab042e5a605128026822fd52021-11-25T05:59:42ZA SUPER powerful method for genome wide association study.1932-620310.1371/journal.pone.0107684https://doaj.org/article/a61d335cbab042e5a605128026822fd52014-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0107684https://doaj.org/toc/1932-6203Genome-Wide Association Studies shed light on the identification of genes underlying human diseases and agriculturally important traits. This potential has been shadowed by false positive findings. The Mixed Linear Model (MLM) method is flexible enough to simultaneously incorporate population structure and cryptic relationships to reduce false positives. However, its intensive computational burden is prohibitive in practice, especially for large samples. The newly developed algorithm, FaST-LMM, solved the computational problem, but requires that the number of SNPs be less than the number of individuals to derive a rank-reduced relationship. This restriction potentially leads to less statistical power when compared to using all SNPs. We developed a method to extract a small subset of SNPs and use them in FaST-LMM. This method not only retains the computational advantage of FaST-LMM, but also remarkably increases statistical power even when compared to using the entire set of SNPs. We named the method SUPER (Settlement of MLM Under Progressively Exclusive Relationship) and made it available within an implementation of the GAPIT software package.Qishan WangFeng TianYuchun PanEdward S BucklerZhiwu ZhangPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 9, p e107684 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Qishan Wang Feng Tian Yuchun Pan Edward S Buckler Zhiwu Zhang A SUPER powerful method for genome wide association study.
description	Genome-Wide Association Studies shed light on the identification of genes underlying human diseases and agriculturally important traits. This potential has been shadowed by false positive findings. The Mixed Linear Model (MLM) method is flexible enough to simultaneously incorporate population structure and cryptic relationships to reduce false positives. However, its intensive computational burden is prohibitive in practice, especially for large samples. The newly developed algorithm, FaST-LMM, solved the computational problem, but requires that the number of SNPs be less than the number of individuals to derive a rank-reduced relationship. This restriction potentially leads to less statistical power when compared to using all SNPs. We developed a method to extract a small subset of SNPs and use them in FaST-LMM. This method not only retains the computational advantage of FaST-LMM, but also remarkably increases statistical power even when compared to using the entire set of SNPs. We named the method SUPER (Settlement of MLM Under Progressively Exclusive Relationship) and made it available within an implementation of the GAPIT software package.
format	article
author	Qishan Wang Feng Tian Yuchun Pan Edward S Buckler Zhiwu Zhang
author_facet	Qishan Wang Feng Tian Yuchun Pan Edward S Buckler Zhiwu Zhang
author_sort	Qishan Wang
title	A SUPER powerful method for genome wide association study.
title_short	A SUPER powerful method for genome wide association study.
title_full	A SUPER powerful method for genome wide association study.
title_fullStr	A SUPER powerful method for genome wide association study.
title_full_unstemmed	A SUPER powerful method for genome wide association study.
title_sort	super powerful method for genome wide association study.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/a61d335cbab042e5a605128026822fd5
work_keys_str_mv	AT qishanwang asuperpowerfulmethodforgenomewideassociationstudy AT fengtian asuperpowerfulmethodforgenomewideassociationstudy AT yuchunpan asuperpowerfulmethodforgenomewideassociationstudy AT edwardsbuckler asuperpowerfulmethodforgenomewideassociationstudy AT zhiwuzhang asuperpowerfulmethodforgenomewideassociationstudy AT qishanwang superpowerfulmethodforgenomewideassociationstudy AT fengtian superpowerfulmethodforgenomewideassociationstudy AT yuchunpan superpowerfulmethodforgenomewideassociationstudy AT edwardsbuckler superpowerfulmethodforgenomewideassociationstudy AT zhiwuzhang superpowerfulmethodforgenomewideassociationstudy
_version_	1718414299236401152

A SUPER powerful method for genome wide association study.

Ejemplares similares