JSON
Kaduk M, Sonnhammer E
Bioinformatics 33 (8) 1154-1159 [2017-04-15; online 2017-01-18]
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.se. Perl code freely available at http://hieranoid.sbc.su.se/ . Supplementary data are available at Bioinformatics online.
PubMed 28096085
DOI 10.1093/bioinformatics/btw774
Crossref 10.1093/bioinformatics/btw774
pii: btw774