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FARVATX: Family-Based Rare Variant Association Test for X-Linked Genes

Authors
Choi, SungkyoungLee, SungyoungQiao, DandiHardin, MeganCho, Michael H.Silverman, Edwin K.Park, TaesungWon, Sungho
Issue Date
Sep-2016
Publisher
John Wiley & Sons Inc.
Keywords
X chromosome; X chromosome inactivation; extended families; rare variants; genetic association analysis
Citation
Genetic Epidemiology, v.40, no.6, pp.475 - 485
Indexed
SCIE
SCOPUS
Journal Title
Genetic Epidemiology
Volume
40
Number
6
Start Page
475
End Page
485
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/13084
DOI
10.1002/gepi.21979
ISSN
0741-0395
Abstract
Although the X chromosome has many genes that are functionally related to human diseases, the complicated biological properties of the X chromosome have prevented efficient genetic association analyses, and only a few significantly associated X-linked variants have been reported for complex traits. For instance, dosage compensation of X-linked genes is often achieved via the inactivation of one allele in each X-linked variant in females; however, some X-linked variants can escape this X chromosome inactivation. Efficient genetic analyses cannot be conducted without prior knowledge about the gene expression process of X-linked variants, and misspecified information can lead to power loss. In this report, we propose new statistical methods for rare X-linked variant genetic association analysis of dichotomous phenotypes with family-based samples. The proposed methods are computationally efficient and can complete X-linked analyses within a few hours. Simulation studies demonstrate the statistical efficiency of the proposed methods, which were then applied to rare-variant association analysis of the X chromosome in chronic obstructive pulmonary disease. Some promising significant X-linked genes were identified, illustrating the practical importance of the proposed methods. (C) 2016 Wiley Periodicals, Inc.
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ERICA 과학기술융합대학 (ERICA 수리데이터사이언스학과)
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