A genome-wide scan statistic framework for whole-genome sequence data analysis

Whole-genome sequencing data reveals a large number of variants for testing their associations with phenotypic traits and diseases. Here, the authors develop WGScan, a statistical method for detecting the existence and estimating the locations of the association signal at genome-wide scale.

Saved in:

Bibliographic Details
Main Authors:	Zihuai He, Bin Xu, Joseph Buxbaum, Iuliana Ionita-Laza
Format:	article
Language:	EN
Published:	Nature Portfolio 2019
Subjects:	Science Q
Online Access:	https://doaj.org/article/cfcd75a1d56442cbae3938a44f874184
Tags:	Add Tag No Tags, Be the first to tag this record!

id	oai:doaj.org-article:cfcd75a1d56442cbae3938a44f874184
record_format	dspace
spelling	oai:doaj.org-article:cfcd75a1d56442cbae3938a44f8741842021-12-02T17:33:10ZA genome-wide scan statistic framework for whole-genome sequence data analysis10.1038/s41467-019-11023-02041-1723https://doaj.org/article/cfcd75a1d56442cbae3938a44f8741842019-07-01T00:00:00Zhttps://doi.org/10.1038/s41467-019-11023-0https://doaj.org/toc/2041-1723Whole-genome sequencing data reveals a large number of variants for testing their associations with phenotypic traits and diseases. Here, the authors develop WGScan, a statistical method for detecting the existence and estimating the locations of the association signal at genome-wide scale.Zihuai HeBin XuJoseph BuxbaumIuliana Ionita-LazaNature PortfolioarticleScienceQENNature Communications, Vol 10, Iss 1, Pp 1-11 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Zihuai He Bin Xu Joseph Buxbaum Iuliana Ionita-Laza A genome-wide scan statistic framework for whole-genome sequence data analysis
description	Whole-genome sequencing data reveals a large number of variants for testing their associations with phenotypic traits and diseases. Here, the authors develop WGScan, a statistical method for detecting the existence and estimating the locations of the association signal at genome-wide scale.
format	article
author	Zihuai He Bin Xu Joseph Buxbaum Iuliana Ionita-Laza
author_facet	Zihuai He Bin Xu Joseph Buxbaum Iuliana Ionita-Laza
author_sort	Zihuai He
title	A genome-wide scan statistic framework for whole-genome sequence data analysis
title_short	A genome-wide scan statistic framework for whole-genome sequence data analysis
title_full	A genome-wide scan statistic framework for whole-genome sequence data analysis
title_fullStr	A genome-wide scan statistic framework for whole-genome sequence data analysis
title_full_unstemmed	A genome-wide scan statistic framework for whole-genome sequence data analysis
title_sort	genome-wide scan statistic framework for whole-genome sequence data analysis
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/cfcd75a1d56442cbae3938a44f874184
work_keys_str_mv	AT zihuaihe agenomewidescanstatisticframeworkforwholegenomesequencedataanalysis AT binxu agenomewidescanstatisticframeworkforwholegenomesequencedataanalysis AT josephbuxbaum agenomewidescanstatisticframeworkforwholegenomesequencedataanalysis AT iulianaionitalaza agenomewidescanstatisticframeworkforwholegenomesequencedataanalysis AT zihuaihe genomewidescanstatisticframeworkforwholegenomesequencedataanalysis AT binxu genomewidescanstatisticframeworkforwholegenomesequencedataanalysis AT josephbuxbaum genomewidescanstatisticframeworkforwholegenomesequencedataanalysis AT iulianaionitalaza genomewidescanstatisticframeworkforwholegenomesequencedataanalysis
_version_	1718380090250756096

A genome-wide scan statistic framework for whole-genome sequence data analysis

Similar Items