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

Tsukasa Fukunaga*, Wataru Iwasaki

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)4039-4041
Number of pages3
JournalBioinformatics
Volume38
Issue number16
DOIs
Publication statusPublished - 2022 Aug 15

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

Fingerprint

Dive into the research topics of 'Mirage 2.0: fast and memory-efficient reconstruction of gene-content evolution considering heterogeneous evolutionary patterns among gene families'. Together they form a unique fingerprint.

Cite this