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Polympact: exploring functional relations among common human genetic variants

In the last years, many studies were able to identify associations between common genetic variants and complex diseases. However, the mechanistic biological links explaining these associations are still mostly unknown. Common variants are usually associated with a relatively small effect size, sugge...

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Autores principales: Valentini, Samuel, Gandolfi, Francesco, Carolo, Mattia, Dalfovo, Davide, Pozza, Lara, Romanel, Alessandro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8860573/
https://www.ncbi.nlm.nih.gov/pubmed/35061909
http://dx.doi.org/10.1093/nar/gkac024
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author Valentini, Samuel
Gandolfi, Francesco
Carolo, Mattia
Dalfovo, Davide
Pozza, Lara
Romanel, Alessandro
author_facet Valentini, Samuel
Gandolfi, Francesco
Carolo, Mattia
Dalfovo, Davide
Pozza, Lara
Romanel, Alessandro
author_sort Valentini, Samuel
collection PubMed
description In the last years, many studies were able to identify associations between common genetic variants and complex diseases. However, the mechanistic biological links explaining these associations are still mostly unknown. Common variants are usually associated with a relatively small effect size, suggesting that interactions among multiple variants might be a major genetic component of complex diseases. Hence, elucidating the presence of functional relations among variants may be fundamental to identify putative variants’ interactions. To this aim, we developed Polympact, a web-based resource that allows to explore functional relations among human common variants by exploiting variants’ functional element landscape, their impact on transcription factor binding motifs, and their effect on transcript levels of protein-coding genes. Polympact characterizes over 18 million common variants and allows to explore putative relations by combining clustering analysis and innovative similarity and interaction network models. The properties of the network models were studied and the utility of Polympact was demonstrated by analysing the rich sets of Breast Cancer and Alzheimer's GWAS variants. We identified relations among multiple variants, suggesting putative interactions. Polympact is freely available at bcglab.cibio.unitn.it/polympact.
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spelling pubmed-88605732022-02-22 Polympact: exploring functional relations among common human genetic variants Valentini, Samuel Gandolfi, Francesco Carolo, Mattia Dalfovo, Davide Pozza, Lara Romanel, Alessandro Nucleic Acids Res Data Resources and Analyses In the last years, many studies were able to identify associations between common genetic variants and complex diseases. However, the mechanistic biological links explaining these associations are still mostly unknown. Common variants are usually associated with a relatively small effect size, suggesting that interactions among multiple variants might be a major genetic component of complex diseases. Hence, elucidating the presence of functional relations among variants may be fundamental to identify putative variants’ interactions. To this aim, we developed Polympact, a web-based resource that allows to explore functional relations among human common variants by exploiting variants’ functional element landscape, their impact on transcription factor binding motifs, and their effect on transcript levels of protein-coding genes. Polympact characterizes over 18 million common variants and allows to explore putative relations by combining clustering analysis and innovative similarity and interaction network models. The properties of the network models were studied and the utility of Polympact was demonstrated by analysing the rich sets of Breast Cancer and Alzheimer's GWAS variants. We identified relations among multiple variants, suggesting putative interactions. Polympact is freely available at bcglab.cibio.unitn.it/polympact. Oxford University Press 2022-01-21 /pmc/articles/PMC8860573/ /pubmed/35061909 http://dx.doi.org/10.1093/nar/gkac024 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Data Resources and Analyses
Valentini, Samuel
Gandolfi, Francesco
Carolo, Mattia
Dalfovo, Davide
Pozza, Lara
Romanel, Alessandro
Polympact: exploring functional relations among common human genetic variants
title Polympact: exploring functional relations among common human genetic variants
title_full Polympact: exploring functional relations among common human genetic variants
title_fullStr Polympact: exploring functional relations among common human genetic variants
title_full_unstemmed Polympact: exploring functional relations among common human genetic variants
title_short Polympact: exploring functional relations among common human genetic variants
title_sort polympact: exploring functional relations among common human genetic variants
topic Data Resources and Analyses
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8860573/
https://www.ncbi.nlm.nih.gov/pubmed/35061909
http://dx.doi.org/10.1093/nar/gkac024
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