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https://hdl.handle.net/1959.11/51478
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ni, Guiyan | en |
dc.contributor.author | Van Der Werf, Julius | en |
dc.contributor.author | Zhou, Xuan | en |
dc.contributor.author | Hypponen, Elina | en |
dc.contributor.author | Wray, Naomi R | en |
dc.contributor.author | Lee, S Hong | en |
dc.date.accessioned | 2022-03-25T03:38:04Z | - |
dc.date.available | 2022-03-25T03:38:04Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Nature Communications, 10(1), p. 1-15 | en |
dc.identifier.issn | 2041-1723 | en |
dc.identifier.uri | https://hdl.handle.net/1959.11/51478 | - |
dc.description.abstract | <p> The genomics era has brought useful tools to dissect the genetic architecture of complex traits. Here we propose a multivariate reaction norm model (MRNM) to tackle genotype-covariate (G-C) correlation and interaction problems. We apply MRNM to the UK Biobank data in analysis of body mass index using smoking quantity as a covariate, finding a highly significant G-C correlation, but only weak evidence for G-C interaction. In contrast, G-C interaction estimates are inflated in existing methods. It is also notable that there is significant heterogeneity in the estimated residual variances (i.e., variances not attributable to factors in the model) across different covariate levels, i.e., residual-covariate (R-C) interaction. We also show that the residual variances estimated by standard additive models can be inflated in the presence of G-C and/or R-C interactions. We conclude that it is essential to correctly account for both interaction and correlation in complex trait analyses. </p> | en |
dc.language | en | en |
dc.publisher | Nature Publishing Group | en |
dc.relation.ispartof | Nature Communications | en |
dc.rights | Attribution 4.0 International | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | * |
dc.title | Genotype-covariate correlation and interaction disentangled by a whole-genome multivariate reaction norm model | en |
dc.type | Journal Article | en |
dc.identifier.doi | 10.1038/s41467-019-10128-w | en |
dc.identifier.pmid | 31110177 | en |
dcterms.accessRights | UNE Green | en |
dc.subject.keywords | Science & Technology - Other Topics | en |
dc.subject.keywords | Multidisciplinary Sciences | en |
local.contributor.firstname | Guiyan | en |
local.contributor.firstname | Julius | en |
local.contributor.firstname | Xuan | en |
local.contributor.firstname | Elina | en |
local.contributor.firstname | Naomi R | en |
local.contributor.firstname | S Hong | en |
local.relation.isfundedby | NHMRC | en |
local.profile.school | School of Environmental and Rural Science | en |
local.profile.school | School of Environmental and Rural Science | en |
local.profile.school | School of Environmental and Rural Science | en |
local.profile.email | gni@une.edu.au | en |
local.profile.email | jvanderw@une.edu.au | en |
local.profile.email | slee38@une.edu.au | en |
local.output.category | C1 | en |
local.grant.number | 1080157 | en |
local.grant.number | 1087889 | en |
local.grant.number | 1078901 | en |
local.grant.number | DP160102126 | en |
local.grant.number | FT160100229 | en |
local.record.place | au | en |
local.record.institution | University of New England | en |
local.publisher.place | United Kingdom | en |
local.identifier.runningnumber | 2239 | en |
local.format.startpage | 1 | en |
local.format.endpage | 15 | en |
local.identifier.scopusid | 85066043213 | en |
local.peerreviewed | Yes | en |
local.identifier.volume | 10 | en |
local.identifier.issue | 1 | en |
local.access.fulltext | Yes | en |
local.contributor.lastname | Ni | en |
local.contributor.lastname | Van Der Werf | en |
local.contributor.lastname | Zhou | en |
local.contributor.lastname | Hypponen | en |
local.contributor.lastname | Wray | en |
local.contributor.lastname | Lee | en |
dc.identifier.staff | une-id:gni | en |
dc.identifier.staff | une-id:jvanderw | en |
dc.identifier.staff | une-id:slee38 | en |
local.profile.orcid | 0000-0003-2512-1696 | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.profile.role | author | en |
local.identifier.unepublicationid | une:1959.11/51478 | en |
local.date.onlineversion | 2019-05-20 | - |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
dc.identifier.academiclevel | Academic | en |
local.title.maintitle | Genotype-covariate correlation and interaction disentangled by a whole-genome multivariate reaction norm model | en |
local.relation.fundingsourcenote | This research has been conducted using the UK Biobank Resource. UK Biobank Research Ethics Committee (REC) approval number is 11/NW/0382. Our reference number approved by UK Biobank is 14575. The Atherosclerosis Risk in Communities Study is carried out as a collaborative study supported by National Heart, Lung, and Blood Institute contracts (HHSN268201100005C, HHSN268201100006C, HHSN268201100007C, HHSN268201100008C, HHSN268201100009C, HHSN268201100010C, HHSN268201100011C, and HHSN268201100012C). We thank the staff and participants of the ARIC study for their important contributions. Funding for GENEVA was provided by National Human Genome Research Institute grant U01HG004402 (E. Boerwinkle). | en |
local.output.categorydescription | C1 Refereed Article in a Scholarly Journal | en |
local.relation.grantdescription | NHMRC/1080157 | en |
local.relation.grantdescription | NHMRC/1087889 | en |
local.relation.grantdescription | NHMRC/1078901 | en |
local.relation.grantdescription | ARC/DP160102126 | en |
local.relation.grantdescription | ARC/FT160100229 | en |
local.search.author | Ni, Guiyan | en |
local.search.author | Van Der Werf, Julius | en |
local.search.author | Zhou, Xuan | en |
local.search.author | Hypponen, Elina | en |
local.search.author | Wray, Naomi R | en |
local.search.author | Lee, S Hong | en |
local.open.fileurl | https://rune.une.edu.au/web/retrieve/4cd31515-ff7f-44aa-ba94-585cf52c85f1 | en |
local.uneassociation | Yes | en |
local.atsiresearch | No | en |
local.sensitive.cultural | No | en |
local.identifier.wosid | 000468275100004 | en |
local.year.available | 2019 | - |
local.year.published | 2019 | - |
local.fileurl.open | https://rune.une.edu.au/web/retrieve/4cd31515-ff7f-44aa-ba94-585cf52c85f1 | en |
local.fileurl.openpublished | https://rune.une.edu.au/web/retrieve/4cd31515-ff7f-44aa-ba94-585cf52c85f1 | en |
local.subject.for2020 | 310207 Statistical and quantitative genetics | en |
local.subject.seo2020 | 200104 Prevention of human diseases and conditions | en |
local.profile.affiliationtype | Unknown | en |
local.profile.affiliationtype | Unknown | en |
local.profile.affiliationtype | Unknown | en |
local.profile.affiliationtype | Unknown | en |
local.profile.affiliationtype | Unknown | en |
local.profile.affiliationtype | Unknown | en |
Appears in Collections: | Journal Article School of Environmental and Rural Science |
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File | Description | Size | Format | |
---|---|---|---|---|
openpublished/GenotypeCovariateGuiyanVanDerWerfLee2019JournalArticle.pdf | Published version | 1.87 MB | Adobe PDF Download Adobe | View/Open |
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