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pgainsim: an R-package to assess the mode of inheritance for quantitative trait loci in GWAS
MOTIVATION: When performing genome-wide association studies conventionally the additive genetic model is used to explore whether a single nucleotide polymorphism (SNP) is associated with a quantitative trait. But for variants, which do not follow an intermediate mode of inheritance (MOI), the recess...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8479659/ https://www.ncbi.nlm.nih.gov/pubmed/33738486 http://dx.doi.org/10.1093/bioinformatics/btab150 |
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author | Scherer, Nora Sekula, Peggy Pfaffelhuber, Peter Schlosser, Pascal |
author_facet | Scherer, Nora Sekula, Peggy Pfaffelhuber, Peter Schlosser, Pascal |
author_sort | Scherer, Nora |
collection | PubMed |
description | MOTIVATION: When performing genome-wide association studies conventionally the additive genetic model is used to explore whether a single nucleotide polymorphism (SNP) is associated with a quantitative trait. But for variants, which do not follow an intermediate mode of inheritance (MOI), the recessive or the dominant genetic model can have more power to detect associations and furthermore the MOI is important for downstream analyses and clinical interpretation. When multiple MOIs are modelled the question arises, which describes the true underlying MOI best. RESULTS: We developed an R-package allowing for the first time to determine study specific critical values when one of the three models is more informative than the other ones for a quantitative trait locus. The package allows for user-friendly simulations to determine these critical values with predefined minor allele frequencies and study sizes. For application scenarios with extensive multiple testing we integrated an interpolation functionality to determine critical values already based on a moderate number of random draws. AVAILABILITY AND IMPLEMENTATION: The R-package pgainsim is freely available for download on Github at https://github.com/genepi-freiburg/pgainsim. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-8479659 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-84796592021-09-30 pgainsim: an R-package to assess the mode of inheritance for quantitative trait loci in GWAS Scherer, Nora Sekula, Peggy Pfaffelhuber, Peter Schlosser, Pascal Bioinformatics Applications Notes MOTIVATION: When performing genome-wide association studies conventionally the additive genetic model is used to explore whether a single nucleotide polymorphism (SNP) is associated with a quantitative trait. But for variants, which do not follow an intermediate mode of inheritance (MOI), the recessive or the dominant genetic model can have more power to detect associations and furthermore the MOI is important for downstream analyses and clinical interpretation. When multiple MOIs are modelled the question arises, which describes the true underlying MOI best. RESULTS: We developed an R-package allowing for the first time to determine study specific critical values when one of the three models is more informative than the other ones for a quantitative trait locus. The package allows for user-friendly simulations to determine these critical values with predefined minor allele frequencies and study sizes. For application scenarios with extensive multiple testing we integrated an interpolation functionality to determine critical values already based on a moderate number of random draws. AVAILABILITY AND IMPLEMENTATION: The R-package pgainsim is freely available for download on Github at https://github.com/genepi-freiburg/pgainsim. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2021-03-05 /pmc/articles/PMC8479659/ /pubmed/33738486 http://dx.doi.org/10.1093/bioinformatics/btab150 Text en © The Author(s) 2021. 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 Non-Commercial 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 Scherer, Nora Sekula, Peggy Pfaffelhuber, Peter Schlosser, Pascal pgainsim: an R-package to assess the mode of inheritance for quantitative trait loci in GWAS |
title | pgainsim: an R-package to assess the mode of inheritance for quantitative trait loci in GWAS |
title_full | pgainsim: an R-package to assess the mode of inheritance for quantitative trait loci in GWAS |
title_fullStr | pgainsim: an R-package to assess the mode of inheritance for quantitative trait loci in GWAS |
title_full_unstemmed | pgainsim: an R-package to assess the mode of inheritance for quantitative trait loci in GWAS |
title_short | pgainsim: an R-package to assess the mode of inheritance for quantitative trait loci in GWAS |
title_sort | pgainsim: an r-package to assess the mode of inheritance for quantitative trait loci in gwas |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8479659/ https://www.ncbi.nlm.nih.gov/pubmed/33738486 http://dx.doi.org/10.1093/bioinformatics/btab150 |
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