Efficient taxa identification using a pangenome index

Author:

Ahmed Omar,Rossi Massimiliano,Boucher Christina,Langmead BenORCID

Abstract

Tools that classify sequencing reads against a database of reference sequences require efficient index data-structures. Ther-index is a compressed full-text index that answers substring presence/absence, count, and locate queries in space proportional to the amount of distinct sequence in the database:O(r)space, whereris the number of Burrows–Wheeler runs. To date, ther-index has lacked the ability to quickly classify matches according to which reference sequences (or sequence groupings, i.e., taxa) a match overlaps. We present new algorithms and methods for solving this problem. Specifically, given a collection D ofddocuments,D={T1,T2,,Td}over an alphabet of size σ, we extend ther-index withO(rd)additional words to support document listing queries for a patternS[1..m]that occurs inndocdocuments in D inO(mloglogw(σ+n/r)+ndoc)time andO(rd)space, wherewis the machine word size. Applied in a bacterial mock community experiment, our method is up to three times faster than a comparable method that uses the standardr-index locate queries. We show that our method classifies both simulated and real nanopore reads at the strain level with higher accuracy compared with other approaches. Finally, we present strategies for compacting this structure in applications in which read lengths or match lengths can be bounded.

Funder

National Science Foundation

National Institutes of Health

Publisher

Cold Spring Harbor Laboratory

Subject

Genetics (clinical),Genetics

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