HaploBlocks: efficient detection of positive selection in large population genomic datasets
Kirsch-Gerweck B, Bohnenkämper L, Henrichs MT, Alanko JN, Bannai H, Cazaux B, Peterlongo P, Burger J, Stoye J, Diekmann Y (2023)
Molecular Biology and Evolution 40(3): msad027.
Zeitschriftenaufsatz
| Veröffentlicht | Englisch
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Autor*in
Kirsch-Gerweck, Benedikt;
Bohnenkämper, LeonardUniBi
;
Henrichs, Michel TheodorUniBi;
Alanko, Jarno N;
Bannai, Hideo;
Cazaux, Bastien;
Peterlongo, Pierre;
Burger, Joachim;
Stoye, JensUniBi
;
Diekmann, Yoan
![](https://pub.uni-bielefeld.de/images/icon_orcid.png)
![](https://pub.uni-bielefeld.de/images/icon_orcid.png)
Einrichtung
Abstract / Bemerkung
Genomic regions under positive selection harbour variation linked for example to adaptation. Most tools for detecting positively selected variants have computational resource requirements rendering them impractical on population genomic datasets with hundreds of thousands of individuals or more. We have developed and implemented an efficient haplotype-based approach able to scan large datasets and accurately detect positive selection. We achieve this by combining a pattern matching approach based on the positional Burrows-Wheeler transform with model-based inference which only requires the evaluation of closed-form expressions. We evaluate our approach with simulations, and find it to be both sensitive and specific. The computational resource requirements quantified using UK Biobank data indicate that our implementation is scalable to population genomic datasets with millions of individuals. Our approach may serve as an algorithmic blueprint for the era of 'big data' genomics: a combinatorial core coupled with statistical inference in closed form. © The Author(s) 2023. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.
Erscheinungsjahr
2023
Zeitschriftentitel
Molecular Biology and Evolution
Band
40
Ausgabe
3
Art.-Nr.
msad027
eISSN
1537-1719
Page URI
https://pub.uni-bielefeld.de/record/2969065
Zitieren
Kirsch-Gerweck B, Bohnenkämper L, Henrichs MT, et al. HaploBlocks: efficient detection of positive selection in large population genomic datasets. Molecular Biology and Evolution. 2023;40(3): msad027.
Kirsch-Gerweck, B., Bohnenkämper, L., Henrichs, M. T., Alanko, J. N., Bannai, H., Cazaux, B., Peterlongo, P., et al. (2023). HaploBlocks: efficient detection of positive selection in large population genomic datasets. Molecular Biology and Evolution, 40(3), msad027. https://doi.org/10.1093/molbev/msad027
Kirsch-Gerweck, Benedikt, Bohnenkämper, Leonard, Henrichs, Michel Theodor, Alanko, Jarno N, Bannai, Hideo, Cazaux, Bastien, Peterlongo, Pierre, Burger, Joachim, Stoye, Jens, and Diekmann, Yoan. 2023. “HaploBlocks: efficient detection of positive selection in large population genomic datasets”. Molecular Biology and Evolution 40 (3): msad027.
Kirsch-Gerweck, B., Bohnenkämper, L., Henrichs, M. T., Alanko, J. N., Bannai, H., Cazaux, B., Peterlongo, P., Burger, J., Stoye, J., and Diekmann, Y. (2023). HaploBlocks: efficient detection of positive selection in large population genomic datasets. Molecular Biology and Evolution 40:msad027.
Kirsch-Gerweck, B., et al., 2023. HaploBlocks: efficient detection of positive selection in large population genomic datasets. Molecular Biology and Evolution, 40(3): msad027.
B. Kirsch-Gerweck, et al., “HaploBlocks: efficient detection of positive selection in large population genomic datasets”, Molecular Biology and Evolution, vol. 40, 2023, : msad027.
Kirsch-Gerweck, B., Bohnenkämper, L., Henrichs, M.T., Alanko, J.N., Bannai, H., Cazaux, B., Peterlongo, P., Burger, J., Stoye, J., Diekmann, Y.: HaploBlocks: efficient detection of positive selection in large population genomic datasets. Molecular Biology and Evolution. 40, : msad027 (2023).
Kirsch-Gerweck, Benedikt, Bohnenkämper, Leonard, Henrichs, Michel Theodor, Alanko, Jarno N, Bannai, Hideo, Cazaux, Bastien, Peterlongo, Pierre, Burger, Joachim, Stoye, Jens, and Diekmann, Yoan. “HaploBlocks: efficient detection of positive selection in large population genomic datasets”. Molecular Biology and Evolution 40.3 (2023): msad027.
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