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A Boolean algebra for genetic variants
MOTIVATION: Beyond identifying genetic variants, we introduce a set of Boolean relations, which allows for a comprehensive classification of the relations of every pair of variants by taking all minimal alignments into account. We present an efficient algorithm to compute these relations, including...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9879725/ https://www.ncbi.nlm.nih.gov/pubmed/36594541 http://dx.doi.org/10.1093/bioinformatics/btad001 |
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author | Vis, Jonathan K Santcroos, Mark A Kosters, Walter A Laros, Jeroen F J |
author_facet | Vis, Jonathan K Santcroos, Mark A Kosters, Walter A Laros, Jeroen F J |
author_sort | Vis, Jonathan K |
collection | PubMed |
description | MOTIVATION: Beyond identifying genetic variants, we introduce a set of Boolean relations, which allows for a comprehensive classification of the relations of every pair of variants by taking all minimal alignments into account. We present an efficient algorithm to compute these relations, including a novel way of efficiently computing all minimal alignments within the best theoretical complexity bounds. RESULTS: We show that these relations are common, and many non-trivial, for variants of the CFTR gene in dbSNP. Ultimately, we present an approach for the storing and indexing of variants in the context of a database that enables efficient querying for all these relations. AVAILABILITY AND IMPLEMENTATION: A Python implementation is available at https://github.com/mutalyzer/algebra/tree/v0.2.0 as well as an interface at https://mutalyzer.nl/algebra. |
format | Online Article Text |
id | pubmed-9879725 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-98797252023-01-31 A Boolean algebra for genetic variants Vis, Jonathan K Santcroos, Mark A Kosters, Walter A Laros, Jeroen F J Bioinformatics Original Paper MOTIVATION: Beyond identifying genetic variants, we introduce a set of Boolean relations, which allows for a comprehensive classification of the relations of every pair of variants by taking all minimal alignments into account. We present an efficient algorithm to compute these relations, including a novel way of efficiently computing all minimal alignments within the best theoretical complexity bounds. RESULTS: We show that these relations are common, and many non-trivial, for variants of the CFTR gene in dbSNP. Ultimately, we present an approach for the storing and indexing of variants in the context of a database that enables efficient querying for all these relations. AVAILABILITY AND IMPLEMENTATION: A Python implementation is available at https://github.com/mutalyzer/algebra/tree/v0.2.0 as well as an interface at https://mutalyzer.nl/algebra. Oxford University Press 2023-01-03 /pmc/articles/PMC9879725/ /pubmed/36594541 http://dx.doi.org/10.1093/bioinformatics/btad001 Text en © The Author(s) 2023. Published by Oxford University Press. 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 | Original Paper Vis, Jonathan K Santcroos, Mark A Kosters, Walter A Laros, Jeroen F J A Boolean algebra for genetic variants |
title | A Boolean algebra for genetic variants |
title_full | A Boolean algebra for genetic variants |
title_fullStr | A Boolean algebra for genetic variants |
title_full_unstemmed | A Boolean algebra for genetic variants |
title_short | A Boolean algebra for genetic variants |
title_sort | boolean algebra for genetic variants |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9879725/ https://www.ncbi.nlm.nih.gov/pubmed/36594541 http://dx.doi.org/10.1093/bioinformatics/btad001 |
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