Taxallnomy: an extension of NCBI Taxonomy that produces a hierarchically complete taxonomic tree

BACKGROUND: NCBI Taxonomy is the main taxonomic source for several bioinformatics tools and databases since all organisms with sequence accessions deposited on INSDC are organized in its hierarchical structure. Despite the extensive use and application of this data source, an alternative representation of data as a table would facilitate the use of information for processing bioinformatics data. To do so, since some taxonomic-ranks are missing in some lineages, an algorithm might propose provisional names for all taxonomic-ranks. RESULTS: To address this issue, we developed an algorithm that takes the tree structure from NCBI Taxonomy and generates a hierarchically complete taxonomic table, maintaining its compatibility with the original tree. The procedures performed by the algorithm consist of attempting to assign a taxonomic-rank to an existing clade or “no rank” node when possible, using its name as part of the created taxonomic-rank name (e.g. Ord_Ornithischia) or interpolating parent nodes when needed (e.g. Cla_of_Ornithischia), both examples given for the dinosaur Brachylophosaurus lineage. The new hierarchical structure was named Taxallnomy because it contains names for all taxonomic-ranks, and it contains 41 hierarchical levels corresponding to the 41 taxonomic-ranks currently found in the NCBI Taxonomy database. From Taxallnomy, users can obtain the complete taxonomic lineage with 41 nodes of all taxa available in the NCBI Taxonomy database, without any hazard to the original tree information. In this work, we demonstrate its applicability by embedding taxonomic information of a specified rank into a phylogenetic tree and by producing metagenomics profiles. CONCLUSION: Taxallnomy applies to any bioinformatics analyses that depend on the information from NCBI Taxonomy. Taxallnomy is updated periodically but with a distributed PERL script users can generate it locally using NCBI Taxonomy as input. All Taxallnomy resources are available at http://bioinfo.icb.ufmg.br/taxallnomy.