StrainGE

a toolkit to track and characterize low-abundance strains in complex microbial communities

Journal Article (2022)
Author(s)

L.R. van Dijk (TU Delft - Pattern Recognition and Bioinformatics, Broad Institute of MIT and Harvard)

BJ Walker (Broad Institute of MIT and Harvard, Applied Invention LLC)

Timothy J. Straub (Harvard T.H. Chan School of Public Health, Broad Institute of MIT and Harvard)

Colin J. Worby (Broad Institute of MIT and Harvard)

Alexandra Grote (Broad Institute of MIT and Harvard)

Henry L. Schreiber (Washington University School of Medicine)

C.A. Anyansi (TU Delft - Pattern Recognition and Bioinformatics)

A. Pickering (University of California, Tufts University)

Scott J. Hultgren (Washington University School of Medicine)

Abigail Manson (Broad Institute of MIT and Harvard)

T.E.P.M.F. Abeel (TU Delft - Pattern Recognition and Bioinformatics, Broad Institute of MIT and Harvard)

Ashlee M. Earl (Broad Institute of MIT and Harvard)

Research Group
Pattern Recognition and Bioinformatics
Copyright
© 2022 L.R. van Dijk, Bruce J. Walker, Timothy J. Straub, Colin J. Worby, Alexandra Grote, Henry L. Schreiber, C.A. Anyansi, Amy J. Pickering, Scott J. Hultgren, Abigail L. Manson, T.E.P.M.F. Abeel, Ashlee M. Earl
DOI related publication
https://doi.org/10.1186/s13059-022-02630-0
More Info
expand_more
Publication Year
2022
Language
English
Copyright
© 2022 L.R. van Dijk, Bruce J. Walker, Timothy J. Straub, Colin J. Worby, Alexandra Grote, Henry L. Schreiber, C.A. Anyansi, Amy J. Pickering, Scott J. Hultgren, Abigail L. Manson, T.E.P.M.F. Abeel, Ashlee M. Earl
Related content
Research Group
Pattern Recognition and Bioinformatics
Issue number
1
Volume number
23
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

Human-associated microbial communities comprise not only complex mixtures of bacterial species, but also mixtures of conspecific strains, the implications of which are mostly unknown since strain level dynamics are underexplored due to the difficulties of studying them. We introduce the Strain Genome Explorer (StrainGE) toolkit, which deconvolves strain mixtures and characterizes component strains at the nucleotide level from short-read metagenomic sequencing with higher sensitivity and resolution than other tools. StrainGE is able to identify strains at 0.1x coverage and detect variants for multiple conspecific strains within a sample from coverages as low as 0.5x.