JustOrthologs: A fast, accurate and user-friendly ortholog identification algorithm

Justin B. Miller, Brandon D. Pickett, Perry G. Ridge

Research output: Contribution to journalArticlepeer-review

17 Scopus citations


Motivation: Orthologous gene identification is fundamental to all aspects of biology. For example, ortholog identification between species can provide functional insights for genes of unknown function and is a necessary step in phylogenetic inference. Currently, most ortholog identification algorithms require all-versus- A ll BLAST comparisons, which are time-consuming and memory intensive. Results: In contrast to existing approaches, JustOrthologs exploits the conservation of gene structure by using the lengths of coding sequence regions and dinucleotide percentages to identify orthologs. In comparison to OrthoMCL, OMA and OrthoFinder, JustOrthologs decreases ortholog identification runtime by more than 96% and achieves comparable precision and recall scores. The computational speedup allowed us to conduct pairwise comparisons of 1197 complete genomes (780 eukaryotes and 417 archaea). We confirmed gene annotations for 384 120 genes, grouped 1 675 415 genes in previously unreported ortholog groups, and identified 51 429 potentially mislabeled genes across 622 843 ortholog groups. Availability and implementation: JustOrthologs is an open source collaborative software package available in the GitHub repository: https://github.com/ridgelab/JustOrthologs/. All test FASTA files used for comparisons are freely available at https://github.com/ridgelab/JustOrthologs/ comparisonFastaFiles/. Reference genomes used in this work are available for download from the NCBI repository: ftp://ftp.ncbi.nih.gov/genomes/.

Original languageEnglish
Pages (from-to)546-552
Number of pages7
Issue number4
StatePublished - Feb 15 2019

Bibliographical note

Publisher Copyright:
© 2018. Published by Oxford University Press. All rights reserved.

ASJC Scopus subject areas

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


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