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A computational approach for identification of core modules from a co-expression network and GWAS data

This protocol describes the application of the “omnigenic” model of the genetic architecture of complex traits to identify novel “core” genes influencing a disease-associated phenotype. Core genes are hypothesized to directly regulate disease and may serve as therapeutic targets. This protocol lever...

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Detalles Bibliográficos
Autores principales: Sabik, Olivia L., Ackert-Bicknell, Cheryl L., Farber, Charles R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8385446/
https://www.ncbi.nlm.nih.gov/pubmed/34467232
http://dx.doi.org/10.1016/j.xpro.2021.100768
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author Sabik, Olivia L.
Ackert-Bicknell, Cheryl L.
Farber, Charles R.
author_facet Sabik, Olivia L.
Ackert-Bicknell, Cheryl L.
Farber, Charles R.
author_sort Sabik, Olivia L.
collection PubMed
description This protocol describes the application of the “omnigenic” model of the genetic architecture of complex traits to identify novel “core” genes influencing a disease-associated phenotype. Core genes are hypothesized to directly regulate disease and may serve as therapeutic targets. This protocol leverages GWAS data, a co-expression network, and publicly available data, including the GTEx database and the International Mouse Phenotyping Consortium Database, to identify modules enriched for genes with “core-like” characteristics. For complete details on the use and execution of this protocol, please refer to Sabik et al. (2020).
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spelling pubmed-83854462021-08-30 A computational approach for identification of core modules from a co-expression network and GWAS data Sabik, Olivia L. Ackert-Bicknell, Cheryl L. Farber, Charles R. STAR Protoc Protocol This protocol describes the application of the “omnigenic” model of the genetic architecture of complex traits to identify novel “core” genes influencing a disease-associated phenotype. Core genes are hypothesized to directly regulate disease and may serve as therapeutic targets. This protocol leverages GWAS data, a co-expression network, and publicly available data, including the GTEx database and the International Mouse Phenotyping Consortium Database, to identify modules enriched for genes with “core-like” characteristics. For complete details on the use and execution of this protocol, please refer to Sabik et al. (2020). Elsevier 2021-08-21 /pmc/articles/PMC8385446/ /pubmed/34467232 http://dx.doi.org/10.1016/j.xpro.2021.100768 Text en © 2021 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Protocol
Sabik, Olivia L.
Ackert-Bicknell, Cheryl L.
Farber, Charles R.
A computational approach for identification of core modules from a co-expression network and GWAS data
title A computational approach for identification of core modules from a co-expression network and GWAS data
title_full A computational approach for identification of core modules from a co-expression network and GWAS data
title_fullStr A computational approach for identification of core modules from a co-expression network and GWAS data
title_full_unstemmed A computational approach for identification of core modules from a co-expression network and GWAS data
title_short A computational approach for identification of core modules from a co-expression network and GWAS data
title_sort computational approach for identification of core modules from a co-expression network and gwas data
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8385446/
https://www.ncbi.nlm.nih.gov/pubmed/34467232
http://dx.doi.org/10.1016/j.xpro.2021.100768
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