Coriolis: enabling metagenomic classification on lightweight mobile devices

Abstract Motivation The introduction of portable DNA sequencers such as the Oxford Nanopore Technologies MinION has enabled real-time and in the field DNA sequencing. However, in the field sequencing is actionable only when coupled with in the field DNA classification. This poses new challenges for...

Full description

Saved in:
Bibliographic Details
Published in:Bioinformatics (Oxford, England) England), 2023-06, Vol.39 (Supplement_1), p.i66-i75
Main Authors: Mikalsen, Andrew J, Zola, Jaroslaw
Format: Article
Language:English
Subjects:
Algorithms
Bioinformatics of Microbes and Microbiomes
Computers, Handheld
Databases, Nucleic Acid
Metagenome
Metagenomics
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Abstract Motivation The introduction of portable DNA sequencers such as the Oxford Nanopore Technologies MinION has enabled real-time and in the field DNA sequencing. However, in the field sequencing is actionable only when coupled with in the field DNA classification. This poses new challenges for metagenomic software since mobile deployments are typically in remote locations with limited network connectivity and without access to capable computing devices. Results We propose new strategies to enable in the field metagenomic classification on mobile devices. We first introduce a programming model for expressing metagenomic classifiers that decomposes the classification process into well-defined and manageable abstractions. The model simplifies resource management in mobile setups and enables rapid prototyping of classification algorithms. Next, we introduce the compact string B-tree, a practical data structure for indexing text in external storage, and we demonstrate its viability as a strategy to deploy massive DNA databases on memory-constrained devices. Finally, we combine both solutions into Coriolis, a metagenomic classifier designed specifically to operate on lightweight mobile devices. Through experiments with actual MinION metagenomic reads and a portable supercomputer-on-a-chip, we show that compared with the state-of-the-art solutions Coriolis offers higher throughput and lower resource consumption without sacrificing quality of classification. Availability and implementation Source code and test data are available from http://score-group.org/?id=smarten.
ISSN:1367-4803
1367-4811
DOI:10.1093/bioinformatics/btad243