FastMulRFS: fast and accurate species tree estimation under generic gene duplication and loss models.
Bioinformatics
; 36(Suppl_1): i57-i65, 2020 07 01.
Article
em En
| MEDLINE
| ID: mdl-32657396
ABSTRACT
MOTIVATION Species tree estimation is a basic part of biological research but can be challenging because of gene duplication and loss (GDL), which results in genes that can appear more than once in a given genome. All common approaches in phylogenomic studies either reduce available data or are error-prone, and thus, scalable methods that do not discard data and have high accuracy on large heterogeneous datasets are needed. RESULTS:
We present FastMulRFS, a polynomial-time method for estimating species trees without knowledge of orthology. We prove that FastMulRFS is statistically consistent under a generic model of GDL when adversarial GDL does not occur. Our extensive simulation study shows that FastMulRFS matches the accuracy of MulRF (which tries to solve the same optimization problem) and has better accuracy than prior methods, including ASTRAL-multi (the only method to date that has been proven statistically consistent under GDL), while being much faster than both methods. AVAILABILITY AND IMPEMENTATION FastMulRFS is available on Github (https//github.com/ekmolloy/fastmulrfs). SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Texto completo:
1
Bases de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Duplicação Gênica
Idioma:
En
Revista:
Bioinformatics
Assunto da revista:
INFORMATICA MEDICA
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
Estados Unidos