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XWAS: A Software Toolset for Genetic Data Analysis and Association Studies of the X Chromosome

XWAS is a new software suite for the analysis of the X chromosome in association studies and similar genetic studies. The X chromosome plays an important role in human disease and traits of many species, especially those with sexually dimorphic characteristics. Special attention needs to be given to...

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Autores principales: Gao, Feng, Chang, Diana, Biddanda, Arjun, Ma, Li, Guo, Yingjie, Zhou, Zilu, Keinan, Alon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4567842/
https://www.ncbi.nlm.nih.gov/pubmed/26268243
http://dx.doi.org/10.1093/jhered/esv059
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author Gao, Feng
Chang, Diana
Biddanda, Arjun
Ma, Li
Guo, Yingjie
Zhou, Zilu
Keinan, Alon
author_facet Gao, Feng
Chang, Diana
Biddanda, Arjun
Ma, Li
Guo, Yingjie
Zhou, Zilu
Keinan, Alon
author_sort Gao, Feng
collection PubMed
description XWAS is a new software suite for the analysis of the X chromosome in association studies and similar genetic studies. The X chromosome plays an important role in human disease and traits of many species, especially those with sexually dimorphic characteristics. Special attention needs to be given to its analysis due to the unique inheritance pattern, which leads to analytical complications that have resulted in the majority of genome-wide association studies (GWAS) either not considering X or mishandling it with toolsets that had been designed for non-sex chromosomes. We hence developed XWAS to fill the need for tools that are specially designed for analysis of X. Following extensive, stringent, and X-specific quality control, XWAS offers an array of statistical tests of association, including: 1) the standard test between a SNP (single nucleotide polymorphism) and disease risk, including after first stratifying individuals by sex, 2) a test for a differential effect of a SNP on disease between males and females, 3) motivated by X-inactivation, a test for higher variance of a trait in heterozygous females as compared with homozygous females, and 4) for all tests, a version that allows for combining evidence from all SNPs across a gene. We applied the toolset analysis pipeline to 16 GWAS datasets of immune-related disorders and 7 risk factors of coronary artery disease, and discovered several new X-linked genetic associations. XWAS will provide the tools and incentive for others to incorporate the X chromosome into GWAS and similar studies in any species with an XX/XY system, hence enabling discoveries of novel loci implicated in many diseases and in their sexual dimorphism.
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spelling pubmed-45678422015-09-14 XWAS: A Software Toolset for Genetic Data Analysis and Association Studies of the X Chromosome Gao, Feng Chang, Diana Biddanda, Arjun Ma, Li Guo, Yingjie Zhou, Zilu Keinan, Alon J Hered Computer Note XWAS is a new software suite for the analysis of the X chromosome in association studies and similar genetic studies. The X chromosome plays an important role in human disease and traits of many species, especially those with sexually dimorphic characteristics. Special attention needs to be given to its analysis due to the unique inheritance pattern, which leads to analytical complications that have resulted in the majority of genome-wide association studies (GWAS) either not considering X or mishandling it with toolsets that had been designed for non-sex chromosomes. We hence developed XWAS to fill the need for tools that are specially designed for analysis of X. Following extensive, stringent, and X-specific quality control, XWAS offers an array of statistical tests of association, including: 1) the standard test between a SNP (single nucleotide polymorphism) and disease risk, including after first stratifying individuals by sex, 2) a test for a differential effect of a SNP on disease between males and females, 3) motivated by X-inactivation, a test for higher variance of a trait in heterozygous females as compared with homozygous females, and 4) for all tests, a version that allows for combining evidence from all SNPs across a gene. We applied the toolset analysis pipeline to 16 GWAS datasets of immune-related disorders and 7 risk factors of coronary artery disease, and discovered several new X-linked genetic associations. XWAS will provide the tools and incentive for others to incorporate the X chromosome into GWAS and similar studies in any species with an XX/XY system, hence enabling discoveries of novel loci implicated in many diseases and in their sexual dimorphism. Oxford University Press 2015 2015-08-12 /pmc/articles/PMC4567842/ /pubmed/26268243 http://dx.doi.org/10.1093/jhered/esv059 Text en © The American Genetic Association. 2015. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Computer Note
Gao, Feng
Chang, Diana
Biddanda, Arjun
Ma, Li
Guo, Yingjie
Zhou, Zilu
Keinan, Alon
XWAS: A Software Toolset for Genetic Data Analysis and Association Studies of the X Chromosome
title XWAS: A Software Toolset for Genetic Data Analysis and Association Studies of the X Chromosome
title_full XWAS: A Software Toolset for Genetic Data Analysis and Association Studies of the X Chromosome
title_fullStr XWAS: A Software Toolset for Genetic Data Analysis and Association Studies of the X Chromosome
title_full_unstemmed XWAS: A Software Toolset for Genetic Data Analysis and Association Studies of the X Chromosome
title_short XWAS: A Software Toolset for Genetic Data Analysis and Association Studies of the X Chromosome
title_sort xwas: a software toolset for genetic data analysis and association studies of the x chromosome
topic Computer Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4567842/
https://www.ncbi.nlm.nih.gov/pubmed/26268243
http://dx.doi.org/10.1093/jhered/esv059
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