Mirage 2.0: fast and memory-efficient reconstruction of gene-content evolution considering heterogeneous evolutionary patterns among gene families

SUMMARY: We present Mirage 2.0, which accurately estimates gene-content evolutionary history by considering heterogeneous evolutionary patterns among gene families. Notably, we introduce a deterministic pattern mixture model, which makes Mirage substantially faster and more memory-efficient to be ap...

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Detalles Bibliográficos
Autores principales: Fukunaga, Tsukasa, Iwasaki, Wataru
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Applications Notes
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9364385/
https://www.ncbi.nlm.nih.gov/pubmed/35771653
http://dx.doi.org/10.1093/bioinformatics/btac433
Descripción
Sumario:SUMMARY: We present Mirage 2.0, which accurately estimates gene-content evolutionary history by considering heterogeneous evolutionary patterns among gene families. Notably, we introduce a deterministic pattern mixture model, which makes Mirage substantially faster and more memory-efficient to be applicable to large datasets with thousands of genomes. AVAILABILITY AND IMPLEMENTATION: The source code is freely available at https://github.com/fukunagatsu/Mirage. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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