Gene- and pathway-based association tests for multiple traits with GWAS summary statistics
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kwak, I.-Y. | - |
dc.contributor.author | Pan, W. | - |
dc.date.accessioned | 2023-03-08T16:12:11Z | - |
dc.date.available | 2023-03-08T16:12:11Z | - |
dc.date.issued | 2017 | - |
dc.identifier.issn | 1367-4803 | - |
dc.identifier.issn | 1367-4811 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/64066 | - |
dc.description.abstract | To identify novel genetic variants associated with complex traits and to shed new insights on underlying biology, in addition to the most popular single SNP-single trait association analysis, it would be useful to explore multiple correlated (intermediate) traits at the gene- or pathway-level by mining existing single GWAS or meta-analyzed GWAS data. For this purpose, we present an adaptive gene-based test and a pathway-based test for association analysis of multiple traits with GWAS summary statistics. The proposed tests are adaptive at both the SNP- and trait-levels; that is, they account for possibly varying association patterns (e.g. signal sparsity levels) across SNPs and traits, thus maintaining high power across a wide range of situations. Furthermore, the proposed methods are general: they can be applied to mixed types of traits, and to Z-statistics or P-values as summary statistics obtained from either a single GWAS or a meta-analysis of multiple GWAS. Our numerical studies with simulated and real data demonstrated the promising performance of the proposed methods. © The Author 2016. Published by Oxford University Press. All rights reserved. | - |
dc.format.extent | 8 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Oxford University Press | - |
dc.title | Gene- and pathway-based association tests for multiple traits with GWAS summary statistics | - |
dc.type | Article | - |
dc.identifier.doi | 10.1093/bioinformatics/btw577 | - |
dc.identifier.bibliographicCitation | Bioinformatics, v.33, no.1, pp 64 - 71 | - |
dc.description.isOpenAccess | Y | - |
dc.identifier.scopusid | 2-s2.0-85014858664 | - |
dc.citation.endPage | 71 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 64 | - |
dc.citation.title | Bioinformatics | - |
dc.citation.volume | 33 | - |
dc.type.docType | Article | - |
dc.publisher.location | 영국 | - |
dc.description.journalRegisteredClass | sci | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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