Abstract
Background: Estimation of species trees from multiple genes is complicated by processes such as incomplete lineage sorting, gene duplication and loss, and horizontal gene transfer, that result in gene trees that differ from each other and from the species phylogeny. Methods to estimate species trees in the presence of gene tree discord due to incomplete lineage sorting have been developed and proved to be statistically consistent when gene tree discord is due only to incomplete lineage sorting and every gene tree includes the full set of species. Results: We establish statistical consistency of certain coalescent-based species tree estimation methods under some models of taxon deletion from genes. We also evaluate the impact of missing data on four species tree estimation methods (ASTRAL-II, ASTRID, MP-EST, and SVDquartets) using simulated datasets with varying levels of incomplete lineage sorting, gene tree estimation error, and degrees/patterns of missing data. Conclusions: All the species tree estimation methods improved in accuracy as the number of genes increased and often produced highly accurate species trees even when the amount of missing data was large. These results together indicate that accurate species tree estimation is possible under a variety of conditions, even when there are substantial amounts of missing data.
| Original language | English (US) |
|---|---|
| Article number | 286 |
| Journal | BMC genomics |
| Volume | 19 |
| DOIs | |
| State | Published - May 8 2018 |
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Keywords
- ASTRAL
- ASTRID
- Incomplete lineage sorting
- MP-EST
- Missing data
- Multi-species coalescent
- SVDquartets
- Species tree
ASJC Scopus subject areas
- Biotechnology
- Genetics
Cite this
The performance of coalescent-based species tree estimation methods under models of missing data. / Nute, Michael; Chou, Jed; Molloy, Erin K.; Warnow, Tandy.
In: BMC genomics, Vol. 19, 286, 08.05.2018.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - The performance of coalescent-based species tree estimation methods under models of missing data
AU - Nute, Michael
AU - Chou, Jed
AU - Molloy, Erin K.
AU - Warnow, Tandy
PY - 2018/5/8
Y1 - 2018/5/8
N2 - Background: Estimation of species trees from multiple genes is complicated by processes such as incomplete lineage sorting, gene duplication and loss, and horizontal gene transfer, that result in gene trees that differ from each other and from the species phylogeny. Methods to estimate species trees in the presence of gene tree discord due to incomplete lineage sorting have been developed and proved to be statistically consistent when gene tree discord is due only to incomplete lineage sorting and every gene tree includes the full set of species. Results: We establish statistical consistency of certain coalescent-based species tree estimation methods under some models of taxon deletion from genes. We also evaluate the impact of missing data on four species tree estimation methods (ASTRAL-II, ASTRID, MP-EST, and SVDquartets) using simulated datasets with varying levels of incomplete lineage sorting, gene tree estimation error, and degrees/patterns of missing data. Conclusions: All the species tree estimation methods improved in accuracy as the number of genes increased and often produced highly accurate species trees even when the amount of missing data was large. These results together indicate that accurate species tree estimation is possible under a variety of conditions, even when there are substantial amounts of missing data.
AB - Background: Estimation of species trees from multiple genes is complicated by processes such as incomplete lineage sorting, gene duplication and loss, and horizontal gene transfer, that result in gene trees that differ from each other and from the species phylogeny. Methods to estimate species trees in the presence of gene tree discord due to incomplete lineage sorting have been developed and proved to be statistically consistent when gene tree discord is due only to incomplete lineage sorting and every gene tree includes the full set of species. Results: We establish statistical consistency of certain coalescent-based species tree estimation methods under some models of taxon deletion from genes. We also evaluate the impact of missing data on four species tree estimation methods (ASTRAL-II, ASTRID, MP-EST, and SVDquartets) using simulated datasets with varying levels of incomplete lineage sorting, gene tree estimation error, and degrees/patterns of missing data. Conclusions: All the species tree estimation methods improved in accuracy as the number of genes increased and often produced highly accurate species trees even when the amount of missing data was large. These results together indicate that accurate species tree estimation is possible under a variety of conditions, even when there are substantial amounts of missing data.
KW - ASTRAL
KW - ASTRID
KW - Incomplete lineage sorting
KW - MP-EST
KW - Missing data
KW - Multi-species coalescent
KW - SVDquartets
KW - Species tree
UR - http://www.scopus.com/inward/record.url?scp=85046675009&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85046675009&partnerID=8YFLogxK
U2 - 10.1186/s12864-018-4619-8
DO - 10.1186/s12864-018-4619-8
M3 - Article
C2 - 29745854
AN - SCOPUS:85046675009
VL - 19
JO - BMC Genomics
JF - BMC Genomics
SN - 1471-2164
M1 - 286
ER -