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The open targets post-GWAS analysis pipeline
MOTIVATION: Genome-wide association studies (GWAS) are a powerful method to detect even weak associations between variants and phenotypes; however, many of the identified associated variants are in non-coding regions, and presumably influence gene expression regulation. Identifying potential drug ta...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7203748/ https://www.ncbi.nlm.nih.gov/pubmed/31930349 http://dx.doi.org/10.1093/bioinformatics/btaa020 |
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author | Peat, Gareth Jones, William Nuhn, Michael Marugán, José Carlos Newell, William Dunham, Ian Zerbino, Daniel |
author_facet | Peat, Gareth Jones, William Nuhn, Michael Marugán, José Carlos Newell, William Dunham, Ian Zerbino, Daniel |
author_sort | Peat, Gareth |
collection | PubMed |
description | MOTIVATION: Genome-wide association studies (GWAS) are a powerful method to detect even weak associations between variants and phenotypes; however, many of the identified associated variants are in non-coding regions, and presumably influence gene expression regulation. Identifying potential drug targets, i.e. causal protein-coding genes, therefore, requires crossing the genetics results with functional data. RESULTS: We present a novel data integration pipeline that analyses GWAS results in the light of experimental epigenetic and cis-regulatory datasets, such as ChIP-Seq, Promoter-Capture Hi-C or eQTL, and presents them in a single report, which can be used for inferring likely causal genes. This pipeline was then fed into an interactive data resource. AVAILABILITY AND IMPLEMENTATION: The analysis code is available at www.github.com/Ensembl/postgap and the interactive data browser at postgwas.opentargets.io. |
format | Online Article Text |
id | pubmed-7203748 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-72037482020-05-11 The open targets post-GWAS analysis pipeline Peat, Gareth Jones, William Nuhn, Michael Marugán, José Carlos Newell, William Dunham, Ian Zerbino, Daniel Bioinformatics Applications Notes MOTIVATION: Genome-wide association studies (GWAS) are a powerful method to detect even weak associations between variants and phenotypes; however, many of the identified associated variants are in non-coding regions, and presumably influence gene expression regulation. Identifying potential drug targets, i.e. causal protein-coding genes, therefore, requires crossing the genetics results with functional data. RESULTS: We present a novel data integration pipeline that analyses GWAS results in the light of experimental epigenetic and cis-regulatory datasets, such as ChIP-Seq, Promoter-Capture Hi-C or eQTL, and presents them in a single report, which can be used for inferring likely causal genes. This pipeline was then fed into an interactive data resource. AVAILABILITY AND IMPLEMENTATION: The analysis code is available at www.github.com/Ensembl/postgap and the interactive data browser at postgwas.opentargets.io. Oxford University Press 2020-05-01 2020-01-13 /pmc/articles/PMC7203748/ /pubmed/31930349 http://dx.doi.org/10.1093/bioinformatics/btaa020 Text en © The Author(s) 2020. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Notes Peat, Gareth Jones, William Nuhn, Michael Marugán, José Carlos Newell, William Dunham, Ian Zerbino, Daniel The open targets post-GWAS analysis pipeline |
title | The open targets post-GWAS analysis pipeline |
title_full | The open targets post-GWAS analysis pipeline |
title_fullStr | The open targets post-GWAS analysis pipeline |
title_full_unstemmed | The open targets post-GWAS analysis pipeline |
title_short | The open targets post-GWAS analysis pipeline |
title_sort | open targets post-gwas analysis pipeline |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7203748/ https://www.ncbi.nlm.nih.gov/pubmed/31930349 http://dx.doi.org/10.1093/bioinformatics/btaa020 |
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