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Bioinformatics. 2018 Mar 1;34(5):795-802. doi: 10.1093/bioinformatics/btx601.

Sipros Ensemble improves database searching and filtering for complex metaproteomics.

Author information

1
Graduate School of Genome Science and Technology, University of Tennessee, Knoxville, TN 37996, USA.
2
Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA.
3
Department of Computer Science and Engineering, University of North Texas, Denton, TX 76203, USA.
4
Department of Microbiology, Oregon State University, Corvallis, OR 97331, USA.
5
Proteomics Resource, University of Washington, Seattle, WA 98195, USA.
6
DST/NRF Centre of Excellence for Biomedical Tuberculosis Research, SAMRC Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town 7505, South Africa.
7
Naval Research Laboratory, Center for Bio/Molecular Science & Engineering (Code 6910), Washington, DC, 20375, USA.

Abstract

Motivation:

Complex microbial communities can be characterized by metagenomics and metaproteomics. However, metagenome assemblies often generate enormous, and yet incomplete, protein databases, which undermines the identification of peptides and proteins in metaproteomics. This challenge calls for increased discrimination of true identifications from false identifications by database searching and filtering algorithms in metaproteomics.

Results:

Sipros Ensemble was developed here for metaproteomics using an ensemble approach. Three diverse scoring functions from MyriMatch, Comet and the original Sipros were incorporated within a single database searching engine. Supervised classification with logistic regression was used to filter database searching results. Benchmarking with soil and marine microbial communities demonstrated a higher number of peptide and protein identifications by Sipros Ensemble than MyriMatch/Percolator, Comet/Percolator, MS-GF+/Percolator, Comet & MyriMatch/iProphet and Comet & MyriMatch & MS-GF+/iProphet. Sipros Ensemble was computationally efficient and scalable on supercomputers.

Availability and implementation:

Freely available under the GNU GPL license at http://sipros.omicsbio.org.

Contact:

cpan@utk.edu.

Supplementary information:

Supplementary data are available at Bioinformatics online.

PMID:
29028897
PMCID:
PMC6192206
[Available on 2019-03-01]
DOI:
10.1093/bioinformatics/btx601
[Indexed for MEDLINE]

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