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

Fukunaga, Tsukasa; Iwasaki, Wataru · Bioinformatics · 2022

Where this comes from

Abstract

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. The source code is freely available at https://github.com/fukunagatsu/Mirage. Supplementary data are available at Bioinformatics online.

Medical subject headings