FARVAT: a family-based rare variant association test
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Choi, Sungkyoung | - |
dc.contributor.author | Lee, Sungyoung | - |
dc.contributor.author | Cichon, Sven | - |
dc.contributor.author | Noethen, Markus M. | - |
dc.contributor.author | Lange, Christoph | - |
dc.contributor.author | Park, Taesung | - |
dc.contributor.author | Won, Sungho | - |
dc.date.accessioned | 2021-06-22T22:05:12Z | - |
dc.date.available | 2021-06-22T22:05:12Z | - |
dc.date.created | 2021-01-21 | - |
dc.date.issued | 2014-11 | - |
dc.identifier.issn | 1367-4803 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/21131 | - |
dc.description.abstract | Motivation: Individuals in each family are genetically more homogeneous than unrelated individuals, and family-based designs are often recommended for the analysis of rare variants. However, despite the importance of family-based samples analysis, few statistical methods for rare variant association analysis are available. Results: In this report, we propose a FAmily-based Rare Variant Association Test (FARVAT). FARVAT is based on the quasi-likelihood of whole families, and is statistically and computationally efficient for the extended families. FARVAT assumed that families were ascertained with the disease status of family members, and incorporation of the estimated genetic relationship matrix to the proposed method provided robustness under the presence of the population substructure. Depending on the choice of working matrix, our method could be a burden test or a variance component test, and could be extended to the SKAT-O-type statistic. FARVAT was implemented in C+ +, and application of the proposed method to schizophrenia data and simulated data for GAW17 illustrated its practical importance. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Oxford University Press | - |
dc.title | FARVAT: a family-based rare variant association test | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Choi, Sungkyoung | - |
dc.identifier.doi | 10.1093/bioinformatics/btu496 | - |
dc.identifier.scopusid | 2-s2.0-84911432159 | - |
dc.identifier.wosid | 000344774600008 | - |
dc.identifier.bibliographicCitation | Bioinformatics, v.30, no.22, pp.3197 - 3205 | - |
dc.relation.isPartOf | Bioinformatics | - |
dc.citation.title | Bioinformatics | - |
dc.citation.volume | 30 | - |
dc.citation.number | 22 | - |
dc.citation.startPage | 3197 | - |
dc.citation.endPage | 3205 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Biochemistry & Molecular Biology | - |
dc.relation.journalResearchArea | Biotechnology & Applied Microbiology | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Mathematical & Computational Biology | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalWebOfScienceCategory | Biochemical Research Methods | - |
dc.relation.journalWebOfScienceCategory | Biotechnology & Applied Microbiology | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Interdisciplinary Applications | - |
dc.relation.journalWebOfScienceCategory | Mathematical & Computational Biology | - |
dc.relation.journalWebOfScienceCategory | Statistics & Probability | - |
dc.subject.keywordPlus | SEQUENCE DATA | - |
dc.subject.keywordPlus | UNIFIED APPROACH | - |
dc.subject.keywordPlus | GENOME | - |
dc.subject.keywordPlus | DISEQUILIBRIUM | - |
dc.subject.keywordPlus | INDIVIDUALS | - |
dc.subject.keywordPlus | DISEASES | - |
dc.subject.keywordPlus | TRAITS | - |
dc.subject.keywordPlus | POWER | - |
dc.subject.keywordPlus | SNPS | - |
dc.identifier.url | https://academic.oup.com/bioinformatics/article/30/22/3197/2389885 | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
55 Hanyangdeahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, Korea+82-31-400-4269 sweetbrain@hanyang.ac.kr
COPYRIGHT © 2021 HANYANG UNIVERSITY. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.