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Polymorphism-aware species trees with advanced mutation models, bootstrap and rate heterogeneity

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Polymorphism-aware species trees with advanced mutation models, bootstrap and rate heterogeneity. / Schrempf, Dominik; Minh, Bui Quang; von Haeseler, Arndt ; Kosiol, Carolin.

In: Molecular Biology and Evolution, Vol. 36, No. 6, 06.2019, p. 1294-1301.

Research output: Contribution to journalArticle

Harvard

Schrempf, D, Minh, BQ, von Haeseler, A & Kosiol, C 2019, 'Polymorphism-aware species trees with advanced mutation models, bootstrap and rate heterogeneity', Molecular Biology and Evolution, vol. 36, no. 6, pp. 1294-1301. https://doi.org/10.1093/molbev/msz043

APA

Schrempf, D., Minh, B. Q., von Haeseler, A., & Kosiol, C. (2019). Polymorphism-aware species trees with advanced mutation models, bootstrap and rate heterogeneity. Molecular Biology and Evolution, 36(6), 1294-1301. https://doi.org/10.1093/molbev/msz043

Vancouver

Schrempf D, Minh BQ, von Haeseler A, Kosiol C. Polymorphism-aware species trees with advanced mutation models, bootstrap and rate heterogeneity. Molecular Biology and Evolution. 2019 Jun;36(6):1294-1301. https://doi.org/10.1093/molbev/msz043

Author

Schrempf, Dominik ; Minh, Bui Quang ; von Haeseler, Arndt ; Kosiol, Carolin. / Polymorphism-aware species trees with advanced mutation models, bootstrap and rate heterogeneity. In: Molecular Biology and Evolution. 2019 ; Vol. 36, No. 6. pp. 1294-1301.

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@article{95ada2a4942642928d301424e160c3bb,
title = "Polymorphism-aware species trees with advanced mutation models, bootstrap and rate heterogeneity",
abstract = "Molecular phylogenetics has neglected polymorphisms within present and ancestral populations for a long time. Recently, multispecies coalescent based methods have increased in popularity, however, their application is limited to a small number of species and individuals. We introduced a polymorphism-aware phylogenetic model (PoMo), which overcomes this limitation and scales well with the increasing amount of sequence data while accounting for present and ancestral polymorphisms. PoMo circumvents handling of gene trees and directly infers species trees from allele frequency data. Here, we extend the PoMo implementation in IQ-TREE and integrate search for the statistically best-fit mutation model, the ability to infer mutation rate variation across sites, and assessment of branch support values. We exemplify an analysis of a hundred species with ten haploid individuals each, showing that PoMo can perform inference on large data sets. While PoMo is more accurate than standard substitution models applied to concatenated alignments, it is almost as fast. We also provide bmm-simulate, a software package that allows simulation of sequences evolving under PoMo. The new options consolidate the value of PoMo for phylogenetic analyses with population data.",
keywords = "Incomplete lineage sorting, Species tree, Phylogenetics, Polymorphism-aware, Phylogenetic model, Boundary mutation model",
author = "Dominik Schrempf and Minh, {Bui Quang} and {von Haeseler}, Arndt and Carolin Kosiol",
note = "This work was funded by the Vienna Science and Technology Fund (WWTF) through project MA16-061. DS was supported by the Austrian Science Fund [FWF-P24551, I-2805-B29] and received funding from the European Research Council under the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 741774. The computational results presented have been achieved in part using the Vienna Scientific Cluster (VSC) and the St Andrews Bioinformatics Unit (StABU) which is funded by a Wellcome Trust ISSF award (grant 105621/Z/14/Z). BQM was supported by the Australian National University Futures grant.",
year = "2019",
month = "6",
doi = "10.1093/molbev/msz043",
language = "English",
volume = "36",
pages = "1294--1301",
journal = "Molecular Biology and Evolution",
issn = "0737-4038",
publisher = "Oxford University Press",
number = "6",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Polymorphism-aware species trees with advanced mutation models, bootstrap and rate heterogeneity

AU - Schrempf, Dominik

AU - Minh, Bui Quang

AU - von Haeseler, Arndt

AU - Kosiol, Carolin

N1 - This work was funded by the Vienna Science and Technology Fund (WWTF) through project MA16-061. DS was supported by the Austrian Science Fund [FWF-P24551, I-2805-B29] and received funding from the European Research Council under the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 741774. The computational results presented have been achieved in part using the Vienna Scientific Cluster (VSC) and the St Andrews Bioinformatics Unit (StABU) which is funded by a Wellcome Trust ISSF award (grant 105621/Z/14/Z). BQM was supported by the Australian National University Futures grant.

PY - 2019/6

Y1 - 2019/6

N2 - Molecular phylogenetics has neglected polymorphisms within present and ancestral populations for a long time. Recently, multispecies coalescent based methods have increased in popularity, however, their application is limited to a small number of species and individuals. We introduced a polymorphism-aware phylogenetic model (PoMo), which overcomes this limitation and scales well with the increasing amount of sequence data while accounting for present and ancestral polymorphisms. PoMo circumvents handling of gene trees and directly infers species trees from allele frequency data. Here, we extend the PoMo implementation in IQ-TREE and integrate search for the statistically best-fit mutation model, the ability to infer mutation rate variation across sites, and assessment of branch support values. We exemplify an analysis of a hundred species with ten haploid individuals each, showing that PoMo can perform inference on large data sets. While PoMo is more accurate than standard substitution models applied to concatenated alignments, it is almost as fast. We also provide bmm-simulate, a software package that allows simulation of sequences evolving under PoMo. The new options consolidate the value of PoMo for phylogenetic analyses with population data.

AB - Molecular phylogenetics has neglected polymorphisms within present and ancestral populations for a long time. Recently, multispecies coalescent based methods have increased in popularity, however, their application is limited to a small number of species and individuals. We introduced a polymorphism-aware phylogenetic model (PoMo), which overcomes this limitation and scales well with the increasing amount of sequence data while accounting for present and ancestral polymorphisms. PoMo circumvents handling of gene trees and directly infers species trees from allele frequency data. Here, we extend the PoMo implementation in IQ-TREE and integrate search for the statistically best-fit mutation model, the ability to infer mutation rate variation across sites, and assessment of branch support values. We exemplify an analysis of a hundred species with ten haploid individuals each, showing that PoMo can perform inference on large data sets. While PoMo is more accurate than standard substitution models applied to concatenated alignments, it is almost as fast. We also provide bmm-simulate, a software package that allows simulation of sequences evolving under PoMo. The new options consolidate the value of PoMo for phylogenetic analyses with population data.

KW - Incomplete lineage sorting

KW - Species tree

KW - Phylogenetics

KW - Polymorphism-aware

KW - Phylogenetic model

KW - Boundary mutation model

U2 - 10.1093/molbev/msz043

DO - 10.1093/molbev/msz043

M3 - Article

VL - 36

SP - 1294

EP - 1301

JO - Molecular Biology and Evolution

JF - Molecular Biology and Evolution

SN - 0737-4038

IS - 6

ER -

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