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Comparing Methods for Species Tree Estimation With Gene Duplication and Loss
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AbstractSpecies 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 trees with multiple copies of the same gene. 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 very good accuracy, nearly the same under many conditions, ASTRAL-Pro and ASTRID-multi are more reliably accurate than FastMuLRFS, and that ASTRID-multi is often faster than ASTRAL-Pro. The datasets generated for this study are freely available in the Illinois Data Bank athttps://databank.illinois.edu/datasets/IDB-2418574
Title: Comparing Methods for Species Tree Estimation With Gene Duplication and Loss
Description:
AbstractSpecies 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 trees with multiple copies of the same gene.
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 very good accuracy, nearly the same under many conditions, ASTRAL-Pro and ASTRID-multi are more reliably accurate than FastMuLRFS, and that ASTRID-multi is often faster than ASTRAL-Pro.
The datasets generated for this study are freely available in the Illinois Data Bank athttps://databank.
illinois.
edu/datasets/IDB-2418574.
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