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Genotype Pattern Mining for Pairs of Interacting Variants Underlying Digenic Traits
Some genetic diseases (“digenic traits”) are due to the interaction between two DNA variants, which presumably reflects biochemical interactions. For example, certain forms of Retinitis Pigmentosa, a type of blindness, occur in the presence of two mutant variants, one each in the ROM1 and RDS genes,...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8391494/ https://www.ncbi.nlm.nih.gov/pubmed/34440333 http://dx.doi.org/10.3390/genes12081160 |
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author | Okazaki, Atsuko Horpaopan, Sukanya Zhang, Qingrun Randesi, Matthew Ott, Jurg |
author_facet | Okazaki, Atsuko Horpaopan, Sukanya Zhang, Qingrun Randesi, Matthew Ott, Jurg |
author_sort | Okazaki, Atsuko |
collection | PubMed |
description | Some genetic diseases (“digenic traits”) are due to the interaction between two DNA variants, which presumably reflects biochemical interactions. For example, certain forms of Retinitis Pigmentosa, a type of blindness, occur in the presence of two mutant variants, one each in the ROM1 and RDS genes, while the occurrence of only one such variant results in a normal phenotype. Detecting variant pairs underlying digenic traits by standard genetic methods is difficult and is downright impossible when individual variants alone have minimal effects. Frequent pattern mining (FPM) methods are known to detect patterns of items. We make use of FPM approaches to find pairs of genotypes (from different variants) that can discriminate between cases and controls. Our method is based on genotype patterns of length two, and permutation testing allows assigning p-values to genotype patterns, where the null hypothesis refers to equal pattern frequencies in cases and controls. We compare different interaction search approaches and their properties on the basis of published datasets. Our implementation of FPM to case-control studies is freely available. |
format | Online Article Text |
id | pubmed-8391494 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-83914942021-08-28 Genotype Pattern Mining for Pairs of Interacting Variants Underlying Digenic Traits Okazaki, Atsuko Horpaopan, Sukanya Zhang, Qingrun Randesi, Matthew Ott, Jurg Genes (Basel) Article Some genetic diseases (“digenic traits”) are due to the interaction between two DNA variants, which presumably reflects biochemical interactions. For example, certain forms of Retinitis Pigmentosa, a type of blindness, occur in the presence of two mutant variants, one each in the ROM1 and RDS genes, while the occurrence of only one such variant results in a normal phenotype. Detecting variant pairs underlying digenic traits by standard genetic methods is difficult and is downright impossible when individual variants alone have minimal effects. Frequent pattern mining (FPM) methods are known to detect patterns of items. We make use of FPM approaches to find pairs of genotypes (from different variants) that can discriminate between cases and controls. Our method is based on genotype patterns of length two, and permutation testing allows assigning p-values to genotype patterns, where the null hypothesis refers to equal pattern frequencies in cases and controls. We compare different interaction search approaches and their properties on the basis of published datasets. Our implementation of FPM to case-control studies is freely available. MDPI 2021-07-28 /pmc/articles/PMC8391494/ /pubmed/34440333 http://dx.doi.org/10.3390/genes12081160 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Okazaki, Atsuko Horpaopan, Sukanya Zhang, Qingrun Randesi, Matthew Ott, Jurg Genotype Pattern Mining for Pairs of Interacting Variants Underlying Digenic Traits |
title | Genotype Pattern Mining for Pairs of Interacting Variants Underlying Digenic Traits |
title_full | Genotype Pattern Mining for Pairs of Interacting Variants Underlying Digenic Traits |
title_fullStr | Genotype Pattern Mining for Pairs of Interacting Variants Underlying Digenic Traits |
title_full_unstemmed | Genotype Pattern Mining for Pairs of Interacting Variants Underlying Digenic Traits |
title_short | Genotype Pattern Mining for Pairs of Interacting Variants Underlying Digenic Traits |
title_sort | genotype pattern mining for pairs of interacting variants underlying digenic traits |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8391494/ https://www.ncbi.nlm.nih.gov/pubmed/34440333 http://dx.doi.org/10.3390/genes12081160 |
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