The Library
Accurate reconstruction of microbial strains from metagenomic sequencing using representative reference genomes
Tools
Tools
Tools
Zhou, Zhemin, Luhmann, Nina, Alikhan, Nabil-Fareed, Quince, Christopher and Achtman, Mark (2018) Accurate reconstruction of microbial strains from metagenomic sequencing using representative reference genomes. In: RECOMB 2018 : International Conference on Research in Computational Molecular Biology, Paris, 21-24 Apr 2018. Published in: Lecture Notes in Computer Science, 10812 pp. 225-240. ISBN 9783319899299. ISSN 0302-9743. doi:10.1007/978-3-319-89929-9_15
|
PDF
WRAP-Accurate-reconstruction-of-microbial-strains-Zhou-2018.pdf - Accepted Version - Requires a PDF viewer. Download (2360Kb) | Preview |
Official URL: http://dx.doi.org/10.1007/978-3-319-89929-9_15
Abstract
Exploring the genetic diversity of microbes within the environment through metagenomic sequencing first requires classifying these reads into taxonomic groups. Current methods compare these sequencing data with existing biased and limited reference databases. Several recent evaluation studies demonstrate that current methods either lack sufficient sensitivity for species-level assignments or suffer from false positives, overestimating the number of species in the metagenome. Both are especially problematic for the identification of low-abundance microbial species, e. g. detecting pathogens in ancient metagenomic samples. We present a new method, SPARSE, which improves taxonomic assignments of metagenomic reads. SPARSE balances existing biased reference databases by grouping reference genomes into similarity-based hierarchical clusters, implemented as an efficient incremental data structure. SPARSE assigns reads to these clusters using a probabilistic model, which specifically penalizes non-specific mappings of reads from unknown sources and hence reduces false-positive assignments. Our evaluation on simulated datasets from two recent evaluation studies demonstrated the improved precision of SPARSE in comparison to other methods for species-level classification. In a third simulation, our method successfully differentiated multiple co-existing Escherichia coli strains from the same sample. In real archaeological datasets, SPARSE identified ancient pathogens with ≤0.02% abundance, consistent with published findings that required additional sequencing data. In these datasets, other methods either missed targeted pathogens or reported non-existent ones.
| Item Type: | Conference Item (Paper) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Subjects: | Q Science > QH Natural history > QH426 Genetics | |||||||||
| Divisions: | Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School > Biomedical Sciences Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School > Biomedical Sciences > Microbiology & Infection Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School |
|||||||||
| Library of Congress Subject Headings (LCSH): | Metagenomics -- Software, Escherichia coli -- Genetic aspects | |||||||||
| Series Name: | Lecture Notes in Computer Science | |||||||||
| Journal or Publication Title: | Lecture Notes in Computer Science | |||||||||
| Publisher: | Springer | |||||||||
| ISBN: | 9783319899299 | |||||||||
| ISSN: | 0302-9743 | |||||||||
| Book Title: | Research in Computational Molecular Biology | |||||||||
| Official Date: | 18 April 2018 | |||||||||
| Dates: |
|
|||||||||
| Volume: | 10812 | |||||||||
| Page Range: | pp. 225-240 | |||||||||
| DOI: | 10.1007/978-3-319-89929-9_15 | |||||||||
| Status: | Peer Reviewed | |||||||||
| Publication Status: | Published | |||||||||
| Access rights to Published version: | Restricted or Subscription Access | |||||||||
| RIOXX Funder/Project Grant: |
|
|||||||||
| Conference Paper Type: | Paper | |||||||||
| Title of Event: | RECOMB 2018 : International Conference on Research in Computational Molecular Biology | |||||||||
| Type of Event: | Conference | |||||||||
| Location of Event: | Paris | |||||||||
| Date(s) of Event: | 21-24 Apr 2018 | |||||||||
| Related URLs: |
Request changes or add full text files to a record
Repository staff actions (login required)
 |
View Item |
Downloads
Downloads per month over past year
