Treetrimmer: a method for phylogenetic dataset size reduction
1 Department of Biochemistry & Molecular Biology, Dalhousie University, Halifax, NS, Canada
2 Centre for Comparative Genomics and Evolutionary Bioinformatics, Dalhousie University, Halifax, NS, Canada
3 Integrated Microbial Biodiversity Program, Canadian Institute for Advanced Research, Montreal, QC H3A 1A4, Canada
4 McGill University and Génome Québec, 740 Docteur-Penfield Ave, Montreal, QC H3A 1A4, Canada
Citation and License
BMC Research Notes 2013, 6:145 doi:10.1186/1756-0500-6-145Published: 12 April 2013
With rapid advances in genome sequencing and bioinformatics, it is now possible to generate phylogenetic trees containing thousands of operational taxonomic units (OTUs) from a wide range of organisms. However, use of rigorous tree-building methods on such large datasets is prohibitive and manual ‘pruning’ of sequence alignments is time consuming and raises concerns over reproducibility. There is a need for bioinformatic tools with which to objectively carry out such pruning procedures.
Here we present ‘TreeTrimmer’, a bioinformatics procedure that removes unnecessary redundancy in large phylogenetic datasets, alleviating the size effect on more rigorous downstream analyses. The method identifies and removes user-defined ‘redundant’ sequences, e.g., orthologous sequences from closely related organisms and ‘recently’ evolved lineage-specific paralogs. Representative OTUs are retained for more rigorous re-analysis.
TreeTrimmer reduces the OTU density of phylogenetic trees without sacrificing taxonomic diversity while retaining the original tree topology, thereby speeding up downstream computer-intensive analyses, e.g., Bayesian and maximum likelihood tree reconstructions, in a reproducible fashion.