Pathway-based approach using hierarchical components of collapsed rare variants
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Sungyoung | - |
dc.contributor.author | Choi, Sungkyoung | - |
dc.contributor.author | Kim, Young Jin | - |
dc.contributor.author | Kim, Bong-Jo | - |
dc.contributor.author | Hwang, Heungsun | - |
dc.contributor.author | Park, Taesung | - |
dc.date.accessioned | 2021-06-22T16:21:56Z | - |
dc.date.available | 2021-06-22T16:21:56Z | - |
dc.date.created | 2021-01-21 | - |
dc.date.issued | 2016-09 | - |
dc.identifier.issn | 1367-4803 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/13055 | - |
dc.description.abstract | Motivation: To address 'missing heritability' issue, many statistical methods for pathway-based analyses using rare variants have been proposed to analyze pathways individually. However, neglecting correlations between multiple pathways can result in misleading solutions, and pathway-based analyses of large-scale genetic datasets require massive computational burden. We propose a Pathway-based approach using HierArchical components of collapsed RAre variants Of High-throughput sequencing data (PHARAOH) for the analysis of rare variants by constructing a single hierarchical model that consists of collapsed gene-level summaries and pathways and analyzes entire pathways simultaneously by imposing ridge-type penalties on both gene and pathway coefficient estimates; hence our method considers the correlation of pathways without constraint by a multiple testing problem. Results: Through simulation studies, the proposed method was shown to have higher statistical power than the existing pathway-based methods. In addition, our method was applied to the large-scale whole-exome sequencing data with levels of a liver enzyme using two well-known pathway databases Biocarta and KEGG. This application demonstrated that our method not only identified associated pathways but also successfully detected biologically plausible pathways for a phenotype of interest. These findings were successfully replicated by an independent large-scale exome chip study. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Oxford University Press | - |
dc.title | Pathway-based approach using hierarchical components of collapsed rare variants | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Choi, Sungkyoung | - |
dc.identifier.doi | 10.1093/bioinformatics/btw425 | - |
dc.identifier.scopusid | 2-s2.0-84990895461 | - |
dc.identifier.wosid | 000384666800025 | - |
dc.identifier.bibliographicCitation | Bioinformatics, v.32, no.17, pp.586 - 594 | - |
dc.relation.isPartOf | Bioinformatics | - |
dc.citation.title | Bioinformatics | - |
dc.citation.volume | 32 | - |
dc.citation.number | 17 | - |
dc.citation.startPage | 586 | - |
dc.citation.endPage | 594 | - |
dc.type.rims | ART | - |
dc.type.docType | Article; Proceedings Paper | - |
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 | GENOME-WIDE ASSOCIATION | - |
dc.subject.keywordPlus | ASPARTATE-AMINOTRANSFERASE | - |
dc.subject.keywordPlus | VARIABLE SELECTION | - |
dc.subject.keywordPlus | LIVER-FUNCTION | - |
dc.subject.keywordPlus | GENE | - |
dc.subject.keywordPlus | DISEASE | - |
dc.subject.keywordPlus | REGRESSION | - |
dc.subject.keywordPlus | CONTRIBUTE | - |
dc.subject.keywordPlus | STEATOSIS | - |
dc.subject.keywordPlus | ALANINE | - |
dc.identifier.url | https://academic.oup.com/bioinformatics/article/32/17/i586/2450755 | - |
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.