SPANNER: taxonomic assignment of sequences using pyramid matching of similarity profiles
Author(s) -
Michael S. Porter,
Robert G. Beiko
Publication year - 2013
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btt313
Subject(s) - taxonomic rank , computer science , rank (graph theory) , similarity (geometry) , set (abstract data type) , biology , artificial intelligence , mathematics , ecology , combinatorics , taxon , image (mathematics) , programming language
Homology-based taxonomic assignment is impeded by differences between the unassigned read and reference database, forcing a rank-specific classification to the closest (and possibly incorrect) reference lineage. This assignment may be correct only to a general rank (e.g. order) and incorrect below that rank (e.g. family and genus). Algorithms like LCA avoid this by varying the predicted taxonomic rank based on matches to a set of taxonomic references. LCA and related approaches can be conservative, especially if best matches are taxonomically widespread because of events such as lateral gene transfer (LGT).
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