Asteroid: a new algorithm to infer species trees from gene trees under high proportions of missing data.
other · Level V
Where this comes from
- Record sourced from PubMed, PMID 36576010.
- Also identified by DOI 10.1093/bioinformatics/btac832 and PMC identifier 9838317.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Missing data and incomplete lineage sorting (ILS) are two major obstacles to accurate species tree inference. Gene tree summary methods such as ASTRAL and ASTRID have been developed to account for ILS. However, they can be severely affected by high levels of missing data. We present Asteroid, a novel algorithm that infers an unrooted species tree from a set of unrooted gene trees. We show on both empirical and simulated datasets that Asteroid is substantially more accurate than ASTRAL and ASTRID for very high proportions (>80%) of missing data. Asteroid is several orders of magnitude faster than ASTRAL for datasets that contain thousands of genes. It offers advanced features such as parallelization, support value computation and support for multi-copy and multifurcating gene trees. Asteroid is freely available at https://github.com/BenoitMorel/Asteroid. Supplementary data are available at Bioinformatics online.
Medical subject headings
- Genomics
- Genetic Speciation