Tejaas: reverse regression increases power for detecting trans-eQTLs

Autores
Banerjee, Saikat; Simonetti, Franco Lucio; Detrois, Kira E.; Kaphle, Anubhav; Mitra, Raktim; Nagial, Rahul; Söding, Johannes
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Trans-acting expression quantitative trait loci (trans-eQTLs) account for ≥70% expression heritability and could therefore facilitate uncovering mechanisms underlying the origination of complex diseases. Identifying trans-eQTLs is challenging because of small effect sizes, tissue specificity, and a severe multiple-testing burden. Tejaas predicts trans-eQTLs by performing L2-regularized “reverse” multiple regression of each SNP on all genes, aggregating evidence from many small trans-effects while being unaffected by the strong expression correlations. Combined with a novel unsupervised k-nearest neighbor method to remove confounders, Tejaas predicts 18851 unique trans-eQTLs across 49 tissues from GTEx. They are enriched in open chromatin, enhancers, and other regulatory regions. Many overlap with disease-associated SNPs, pointing to tissue-specific transcriptional regulation mechanisms.
Fil: Banerjee, Saikat. Max Planck Institute For Biophysical Chemistry; Alemania
Fil: Simonetti, Franco Lucio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentina. Max Planck Institute For Biophysical Chemistry; Alemania
Fil: Detrois, Kira E.. Max Planck Institute For Biophysical Chemistry; Alemania. Universität Göttingen; Alemania
Fil: Kaphle, Anubhav. Universität Göttingen; Alemania. Max Planck Institute For Biophysical Chemistry; Alemania
Fil: Mitra, Raktim. Indian Institute of Technology; India
Fil: Nagial, Rahul. Indian Institute of Technology; India
Fil: Söding, Johannes. Max Planck Institute For Biophysical Chemistry; Alemania. University of Göttingen; Alemania
Materia
Trans-eQTLs
Multiple linear regression
GTEx
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/167151
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Tejaas: reverse regression increases power for detecting trans-eQTLsBanerjee, SaikatSimonetti, Franco LucioDetrois, Kira E.Kaphle, AnubhavMitra, RaktimNagial, RahulSöding, JohannesTrans-eQTLsMultiple linear regressionGTExhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Trans-acting expression quantitative trait loci (trans-eQTLs) account for ≥70% expression heritability and could therefore facilitate uncovering mechanisms underlying the origination of complex diseases. Identifying trans-eQTLs is challenging because of small effect sizes, tissue specificity, and a severe multiple-testing burden. Tejaas predicts trans-eQTLs by performing L2-regularized “reverse” multiple regression of each SNP on all genes, aggregating evidence from many small trans-effects while being unaffected by the strong expression correlations. Combined with a novel unsupervised k-nearest neighbor method to remove confounders, Tejaas predicts 18851 unique trans-eQTLs across 49 tissues from GTEx. They are enriched in open chromatin, enhancers, and other regulatory regions. Many overlap with disease-associated SNPs, pointing to tissue-specific transcriptional regulation mechanisms.Fil: Banerjee, Saikat. Max Planck Institute For Biophysical Chemistry; AlemaniaFil: Simonetti, Franco Lucio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentina. Max Planck Institute For Biophysical Chemistry; AlemaniaFil: Detrois, Kira E.. Max Planck Institute For Biophysical Chemistry; Alemania. Universität Göttingen; AlemaniaFil: Kaphle, Anubhav. Universität Göttingen; Alemania. Max Planck Institute For Biophysical Chemistry; AlemaniaFil: Mitra, Raktim. Indian Institute of Technology; IndiaFil: Nagial, Rahul. Indian Institute of Technology; IndiaFil: Söding, Johannes. Max Planck Institute For Biophysical Chemistry; Alemania. University of Göttingen; AlemaniaBioMed Central Ltd2021-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/167151Banerjee, Saikat; Simonetti, Franco Lucio; Detrois, Kira E.; Kaphle, Anubhav; Mitra, Raktim; et al.; Tejaas: reverse regression increases power for detecting trans-eQTLs; BioMed Central Ltd; Genome Biology; 22; 1; 12-2021; 1-161474-760XCONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02361-8info:eu-repo/semantics/altIdentifier/doi/10.1186/s13059-021-02361-8info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-11-05T09:34:43Zoai:ri.conicet.gov.ar:11336/167151instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-11-05 09:34:43.389CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Tejaas: reverse regression increases power for detecting trans-eQTLs
title Tejaas: reverse regression increases power for detecting trans-eQTLs
spellingShingle Tejaas: reverse regression increases power for detecting trans-eQTLs
Banerjee, Saikat
Trans-eQTLs
Multiple linear regression
GTEx
title_short Tejaas: reverse regression increases power for detecting trans-eQTLs
title_full Tejaas: reverse regression increases power for detecting trans-eQTLs
title_fullStr Tejaas: reverse regression increases power for detecting trans-eQTLs
title_full_unstemmed Tejaas: reverse regression increases power for detecting trans-eQTLs
title_sort Tejaas: reverse regression increases power for detecting trans-eQTLs
dc.creator.none.fl_str_mv Banerjee, Saikat
Simonetti, Franco Lucio
Detrois, Kira E.
Kaphle, Anubhav
Mitra, Raktim
Nagial, Rahul
Söding, Johannes
author Banerjee, Saikat
author_facet Banerjee, Saikat
Simonetti, Franco Lucio
Detrois, Kira E.
Kaphle, Anubhav
Mitra, Raktim
Nagial, Rahul
Söding, Johannes
author_role author
author2 Simonetti, Franco Lucio
Detrois, Kira E.
Kaphle, Anubhav
Mitra, Raktim
Nagial, Rahul
Söding, Johannes
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Trans-eQTLs
Multiple linear regression
GTEx
topic Trans-eQTLs
Multiple linear regression
GTEx
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Trans-acting expression quantitative trait loci (trans-eQTLs) account for ≥70% expression heritability and could therefore facilitate uncovering mechanisms underlying the origination of complex diseases. Identifying trans-eQTLs is challenging because of small effect sizes, tissue specificity, and a severe multiple-testing burden. Tejaas predicts trans-eQTLs by performing L2-regularized “reverse” multiple regression of each SNP on all genes, aggregating evidence from many small trans-effects while being unaffected by the strong expression correlations. Combined with a novel unsupervised k-nearest neighbor method to remove confounders, Tejaas predicts 18851 unique trans-eQTLs across 49 tissues from GTEx. They are enriched in open chromatin, enhancers, and other regulatory regions. Many overlap with disease-associated SNPs, pointing to tissue-specific transcriptional regulation mechanisms.
Fil: Banerjee, Saikat. Max Planck Institute For Biophysical Chemistry; Alemania
Fil: Simonetti, Franco Lucio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquímicas de Buenos Aires. Fundación Instituto Leloir. Instituto de Investigaciones Bioquímicas de Buenos Aires; Argentina. Max Planck Institute For Biophysical Chemistry; Alemania
Fil: Detrois, Kira E.. Max Planck Institute For Biophysical Chemistry; Alemania. Universität Göttingen; Alemania
Fil: Kaphle, Anubhav. Universität Göttingen; Alemania. Max Planck Institute For Biophysical Chemistry; Alemania
Fil: Mitra, Raktim. Indian Institute of Technology; India
Fil: Nagial, Rahul. Indian Institute of Technology; India
Fil: Söding, Johannes. Max Planck Institute For Biophysical Chemistry; Alemania. University of Göttingen; Alemania
description Trans-acting expression quantitative trait loci (trans-eQTLs) account for ≥70% expression heritability and could therefore facilitate uncovering mechanisms underlying the origination of complex diseases. Identifying trans-eQTLs is challenging because of small effect sizes, tissue specificity, and a severe multiple-testing burden. Tejaas predicts trans-eQTLs by performing L2-regularized “reverse” multiple regression of each SNP on all genes, aggregating evidence from many small trans-effects while being unaffected by the strong expression correlations. Combined with a novel unsupervised k-nearest neighbor method to remove confounders, Tejaas predicts 18851 unique trans-eQTLs across 49 tissues from GTEx. They are enriched in open chromatin, enhancers, and other regulatory regions. Many overlap with disease-associated SNPs, pointing to tissue-specific transcriptional regulation mechanisms.
publishDate 2021
dc.date.none.fl_str_mv 2021-12
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/167151
Banerjee, Saikat; Simonetti, Franco Lucio; Detrois, Kira E.; Kaphle, Anubhav; Mitra, Raktim; et al.; Tejaas: reverse regression increases power for detecting trans-eQTLs; BioMed Central Ltd; Genome Biology; 22; 1; 12-2021; 1-16
1474-760X
CONICET Digital
CONICET
url http://hdl.handle.net/11336/167151
identifier_str_mv Banerjee, Saikat; Simonetti, Franco Lucio; Detrois, Kira E.; Kaphle, Anubhav; Mitra, Raktim; et al.; Tejaas: reverse regression increases power for detecting trans-eQTLs; BioMed Central Ltd; Genome Biology; 22; 1; 12-2021; 1-16
1474-760X
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02361-8
info:eu-repo/semantics/altIdentifier/doi/10.1186/s13059-021-02361-8
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv BioMed Central Ltd
publisher.none.fl_str_mv BioMed Central Ltd
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.087074

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