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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.

Abstract

MOTIVATION:

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.

RESULTS:

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.

CONTACT:

mateusz.kaduk@scilifelab.seAvailability and Implementation: Perl code freely available at http://hieranoid.sbc.su.se/Supplementary information: Supplementary data are available at Bioinformatics online.

PMID:
28096085
DOI:
10.1093/bioinformatics/btw774
[PubMed - as supplied by publisher]
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