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Haplotype based testing for a better understanding of the selective architecture

BACKGROUND: The identification of genomic regions affected by selection is one of the most important goals in population genetics. If temporal data are available, allele frequency changes at SNP positions are often used for this purpose. Here we provide a new testing approach that uses haplotype fre...

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Autores principales: Chen, Haoyu, Pelizzola, Marta, Futschik, Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10463365/
https://www.ncbi.nlm.nih.gov/pubmed/37633901
http://dx.doi.org/10.1186/s12859-023-05437-3
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author Chen, Haoyu
Pelizzola, Marta
Futschik, Andreas
author_facet Chen, Haoyu
Pelizzola, Marta
Futschik, Andreas
author_sort Chen, Haoyu
collection PubMed
description BACKGROUND: The identification of genomic regions affected by selection is one of the most important goals in population genetics. If temporal data are available, allele frequency changes at SNP positions are often used for this purpose. Here we provide a new testing approach that uses haplotype frequencies instead of allele frequencies. RESULTS: Using simulated data, we show that compared to SNP based test, our approach has higher power, especially when the number of candidate haplotypes is small or moderate. To improve power when the number of haplotypes is large, we investigate methods to combine them with a moderate number of haplotype subsets. Haplotype frequencies can often be recovered with less noise than SNP frequencies, especially under pool sequencing, giving our test an additional advantage. Furthermore, spurious outlier SNPs may lead to false positives, a problem usually not encountered when working with haplotypes. Post hoc tests for the number of selected haplotypes and for differences between their selection coefficients are also provided for a better understanding of the underlying selection dynamics. An application on a real data set further illustrates the performance benefits. CONCLUSIONS: Due to less multiple testing correction and noise reduction, haplotype based testing is able to outperform SNP based tests in terms of power in most scenarios. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05437-3.
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spelling pubmed-104633652023-08-30 Haplotype based testing for a better understanding of the selective architecture Chen, Haoyu Pelizzola, Marta Futschik, Andreas BMC Bioinformatics Research BACKGROUND: The identification of genomic regions affected by selection is one of the most important goals in population genetics. If temporal data are available, allele frequency changes at SNP positions are often used for this purpose. Here we provide a new testing approach that uses haplotype frequencies instead of allele frequencies. RESULTS: Using simulated data, we show that compared to SNP based test, our approach has higher power, especially when the number of candidate haplotypes is small or moderate. To improve power when the number of haplotypes is large, we investigate methods to combine them with a moderate number of haplotype subsets. Haplotype frequencies can often be recovered with less noise than SNP frequencies, especially under pool sequencing, giving our test an additional advantage. Furthermore, spurious outlier SNPs may lead to false positives, a problem usually not encountered when working with haplotypes. Post hoc tests for the number of selected haplotypes and for differences between their selection coefficients are also provided for a better understanding of the underlying selection dynamics. An application on a real data set further illustrates the performance benefits. CONCLUSIONS: Due to less multiple testing correction and noise reduction, haplotype based testing is able to outperform SNP based tests in terms of power in most scenarios. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05437-3. BioMed Central 2023-08-26 /pmc/articles/PMC10463365/ /pubmed/37633901 http://dx.doi.org/10.1186/s12859-023-05437-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Chen, Haoyu
Pelizzola, Marta
Futschik, Andreas
Haplotype based testing for a better understanding of the selective architecture
title Haplotype based testing for a better understanding of the selective architecture
title_full Haplotype based testing for a better understanding of the selective architecture
title_fullStr Haplotype based testing for a better understanding of the selective architecture
title_full_unstemmed Haplotype based testing for a better understanding of the selective architecture
title_short Haplotype based testing for a better understanding of the selective architecture
title_sort haplotype based testing for a better understanding of the selective architecture
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10463365/
https://www.ncbi.nlm.nih.gov/pubmed/37633901
http://dx.doi.org/10.1186/s12859-023-05437-3
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