title: Improved orthology inference with Hieranoid 2.
abstract: 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.
authors.affiliation: Department of Biochemistry and Biophysics, Stockholm University.|Science for Life Laboratory (SciLifeLab), Tomtebodavagen 23, Solna, Sweden.
authors.forename: Mateusz
authors.initials: M
authors.lastname: Kaduk
authors.affiliation: Department of Biochemistry and Biophysics, Stockholm University.|Science for Life Laboratory (SciLifeLab), Tomtebodavagen 23, Solna, Sweden.
authors.forename: Erik
authors.initials: E
authors.lastname: Sonnhammer
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D016415:Sequence Alignment; D017385:Sequence Homology; D012984:Software