Hierarchically Labeled Database Indexing Allows Scalable Characterization of Microbiomes.

ABSTRACT: Increasingly available microbial reference data allow interpreting the composition and function of previously uncharacterized microbial communities in detail, via high-throughput sequencing analysis. However, efficient methods for read classification are required when the best database matches for short sequence reads are often shared among multiple reference sequences. Here, we take advantage of the fact that microbial sequences can be annotated relative to established tree structures, and we develop a highly scalable read classifier, PRROMenade, by enhancing the generalized Burrows-Wheeler transform with a labeling step to directly assign reads to the corresponding lowest taxonomic unit in an annotation tree. PRROMenade solves the multi-matching problem while allowing fast variable-size

SUBMITTER: Utro F 

PROVIDER: S-EPMC7125348 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature