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Bioinformatics. 2017 Jan 17. pii: btw774. doi: 10.1093/bioinformatics/btw774. [Epub ahead of print]

Improved orthology inference with Hieranoid 2.

Author information

  • 1Department of Biochemistry and Biophysics, Stockholm University.
  • 2Science for Life Laboratory (SciLifeLab), Tomtebodavagen 23, Solna, Sweden.



The initial step in many orthology inference methods is the computationally demanding establishment of all pairwise protein similarities across all analysed proteomes. The quadratic scaling with proteomes has become a major bottleneck. A remedy is offered by the Hieranoid algorithm which reduces the complexity to linear by hierarchically aggregating ortholog groups from InParanoid along a species tree.


We have further developed the Hieranoid algorithm in many ways. Major improvements have been made to the construction of multiple sequence alignments and consensus sequences. Hieranoid version 2 was evaluated with standard benchmarks that reveal a dramatic increase in the coverage/accuracy tradeoff over version 1, such that it now compares favourably with the best methods. The new parallelized cluster mode allows Hieranoid to be run on large data sets in a much shorter timespan than InParanoid, yet at similar accuracy.


mateusz.kaduk@scilifelab.seAvailability and Implementation: Perl code freely available at information: Supplementary data are available at Bioinformatics online.

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