Comparing Methods for Species Tree Estimation with Gene Duplication and Loss

James Willson; Mrinmoy Saha Roddur; Tandy Warnow

doi:10.1007/978-3-030-74432-8_8

Comparing Methods for Species Tree Estimation with Gene Duplication and Loss

James Willson, Mrinmoy Saha Roddur, Tandy Warnow

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Species tree inference from gene trees is an important part of biological research. One confounding factor in estimating species trees is gene duplication and loss, which can lead to gene family trees with multiple copies of the same species. In recent years there have been several new methods developed to address this problem that have substantially improved on earlier methods; however, the best performing methods (ASTRAL-Pro, ASTRID-multi, and FastMulRFS) have not yet been directly compared. In this study, we compare ASTRAL-Pro, ASTRID-multi, and FastMulRFS under a wide variety of conditions. Our study shows that while all three have nearly the same accuracy under most conditions, ASTRAL-Pro and ASTRID-multi are more reliably accurate than FastMuLRFS (with a small advantage to ASTRID-multi), and that ASTRID-multi is often faster than ASTRAL-Pro.

Original language	English (US)
Title of host publication	Algorithms for Computational Biology - 8th International Conference, AlCoB 2021, Proceedings
Editors	Carlos Martín-Vide, Miguel A. Vega-Rodríguez, Travis Wheeler
Publisher	Springer
Pages	106-117
Number of pages	12
ISBN (Print)	9783030744311
DOIs	https://doi.org/10.1007/978-3-030-74432-8_8
State	Published - 2021
Externally published	Yes
Event	8th International Conference on Algorithms for Computational Biology, AlCoB 2021 - Missoula, United States Duration: Jun 7 2021 → Jun 11 2021

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12715 LNBI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th International Conference on Algorithms for Computational Biology, AlCoB 2021
Country/Territory	United States
City	Missoula
Period	6/7/21 → 6/11/21

Keywords

Gene duplication and loss
Species-tree inference

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Online availability

10.1007/978-3-030-74432-8_8

Library availability

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Cite this

Willson, J., Roddur, M. S., & Warnow, T. (2021). Comparing Methods for Species Tree Estimation with Gene Duplication and Loss. In C. Martín-Vide, M. A. Vega-Rodríguez, & T. Wheeler (Eds.), Algorithms for Computational Biology - 8th International Conference, AlCoB 2021, Proceedings (pp. 106-117). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12715 LNBI). Springer. https://doi.org/10.1007/978-3-030-74432-8_8

Comparing Methods for Species Tree Estimation with Gene Duplication and Loss. / Willson, James; Roddur, Mrinmoy Saha; Warnow, Tandy.
Algorithms for Computational Biology - 8th International Conference, AlCoB 2021, Proceedings. ed. / Carlos Martín-Vide; Miguel A. Vega-Rodríguez; Travis Wheeler. Springer, 2021. p. 106-117 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12715 LNBI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Willson, J, Roddur, MS & Warnow, T 2021, Comparing Methods for Species Tree Estimation with Gene Duplication and Loss. in C Martín-Vide, MA Vega-Rodríguez & T Wheeler (eds), Algorithms for Computational Biology - 8th International Conference, AlCoB 2021, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12715 LNBI, Springer, pp. 106-117, 8th International Conference on Algorithms for Computational Biology, AlCoB 2021, Missoula, United States, 6/7/21. https://doi.org/10.1007/978-3-030-74432-8_8

Willson J, Roddur MS, Warnow T. Comparing Methods for Species Tree Estimation with Gene Duplication and Loss. In Martín-Vide C, Vega-Rodríguez MA, Wheeler T, editors, Algorithms for Computational Biology - 8th International Conference, AlCoB 2021, Proceedings. Springer. 2021. p. 106-117. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-74432-8_8

Willson, James ; Roddur, Mrinmoy Saha ; Warnow, Tandy. / Comparing Methods for Species Tree Estimation with Gene Duplication and Loss. Algorithms for Computational Biology - 8th International Conference, AlCoB 2021, Proceedings. editor / Carlos Martín-Vide ; Miguel A. Vega-Rodríguez ; Travis Wheeler. Springer, 2021. pp. 106-117 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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AB - Species tree inference from gene trees is an important part of biological research. One confounding factor in estimating species trees is gene duplication and loss, which can lead to gene family trees with multiple copies of the same species. In recent years there have been several new methods developed to address this problem that have substantially improved on earlier methods; however, the best performing methods (ASTRAL-Pro, ASTRID-multi, and FastMulRFS) have not yet been directly compared. In this study, we compare ASTRAL-Pro, ASTRID-multi, and FastMulRFS under a wide variety of conditions. Our study shows that while all three have nearly the same accuracy under most conditions, ASTRAL-Pro and ASTRID-multi are more reliably accurate than FastMuLRFS (with a small advantage to ASTRID-multi), and that ASTRID-multi is often faster than ASTRAL-Pro.

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Comparing Methods for Species Tree Estimation with Gene Duplication and Loss

Abstract

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