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GenRisk: a tool for comprehensive genetic risk modeling

SUMMARY: The genetic architecture of complex traits can be influenced by both many common regulatory variants with small effect sizes and rare deleterious variants in coding regions with larger effect sizes. However, the two kinds of genetic contributions are typically analyzed independently. Here,...

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Autores principales: Aldisi, Rana, Hassanin, Emadeldin, Sivalingam, Sugirthan, Buness, Andreas, Klinkhammer, Hannah, Mayr, Andreas, Fröhlich, Holger, Krawitz, Peter, Maj, Carlo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9048672/
https://www.ncbi.nlm.nih.gov/pubmed/35266528
http://dx.doi.org/10.1093/bioinformatics/btac152
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author Aldisi, Rana
Hassanin, Emadeldin
Sivalingam, Sugirthan
Buness, Andreas
Klinkhammer, Hannah
Mayr, Andreas
Fröhlich, Holger
Krawitz, Peter
Maj, Carlo
author_facet Aldisi, Rana
Hassanin, Emadeldin
Sivalingam, Sugirthan
Buness, Andreas
Klinkhammer, Hannah
Mayr, Andreas
Fröhlich, Holger
Krawitz, Peter
Maj, Carlo
author_sort Aldisi, Rana
collection PubMed
description SUMMARY: The genetic architecture of complex traits can be influenced by both many common regulatory variants with small effect sizes and rare deleterious variants in coding regions with larger effect sizes. However, the two kinds of genetic contributions are typically analyzed independently. Here, we present GenRisk, a python package for the computation and the integration of gene scores based on the burden of rare deleterious variants and common-variants-based polygenic risk scores. The derived scores can be analyzed within GenRisk to perform association tests or to derive phenotype prediction models by testing multiple classification and regression approaches. GenRisk is compatible with VCF input file formats. AVAILABILITY AND IMPLEMENTATION: GenRisk is an open source publicly available python package that can be downloaded or installed from Github (https://github.com/AldisiRana/GenRisk). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-90486722022-04-29 GenRisk: a tool for comprehensive genetic risk modeling Aldisi, Rana Hassanin, Emadeldin Sivalingam, Sugirthan Buness, Andreas Klinkhammer, Hannah Mayr, Andreas Fröhlich, Holger Krawitz, Peter Maj, Carlo Bioinformatics Applications Notes SUMMARY: The genetic architecture of complex traits can be influenced by both many common regulatory variants with small effect sizes and rare deleterious variants in coding regions with larger effect sizes. However, the two kinds of genetic contributions are typically analyzed independently. Here, we present GenRisk, a python package for the computation and the integration of gene scores based on the burden of rare deleterious variants and common-variants-based polygenic risk scores. The derived scores can be analyzed within GenRisk to perform association tests or to derive phenotype prediction models by testing multiple classification and regression approaches. GenRisk is compatible with VCF input file formats. AVAILABILITY AND IMPLEMENTATION: GenRisk is an open source publicly available python package that can be downloaded or installed from Github (https://github.com/AldisiRana/GenRisk). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2022-03-10 /pmc/articles/PMC9048672/ /pubmed/35266528 http://dx.doi.org/10.1093/bioinformatics/btac152 Text en © The Author(s) 2022. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Applications Notes
Aldisi, Rana
Hassanin, Emadeldin
Sivalingam, Sugirthan
Buness, Andreas
Klinkhammer, Hannah
Mayr, Andreas
Fröhlich, Holger
Krawitz, Peter
Maj, Carlo
GenRisk: a tool for comprehensive genetic risk modeling
title GenRisk: a tool for comprehensive genetic risk modeling
title_full GenRisk: a tool for comprehensive genetic risk modeling
title_fullStr GenRisk: a tool for comprehensive genetic risk modeling
title_full_unstemmed GenRisk: a tool for comprehensive genetic risk modeling
title_short GenRisk: a tool for comprehensive genetic risk modeling
title_sort genrisk: a tool for comprehensive genetic risk modeling
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9048672/
https://www.ncbi.nlm.nih.gov/pubmed/35266528
http://dx.doi.org/10.1093/bioinformatics/btac152
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