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Bioinformatics. 2017 Apr 15;33(8):1154-1159. doi: 10.1093/bioinformatics/btw774.

Improved orthology inference with Hieranoid 2.

Author information

1
Department of Biochemistry and Biophysics, Stockholm University.
2
Science 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.se.

Availability 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
[Indexed for MEDLINE]

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