Sipros Ensemble improves database searching and filtering for complex metaproteomics
Journal Article
·
· Bioinformatics
- Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States); Univ. of North Texas, Denton, TX (United States); DOE/OSTI
- Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Oregon State Univ., Corvallis, OR (United States)
- Univ. of Washington, Seattle, WA (United States)
- Stellenbosch University (South Africa)
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. 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. Freely available under the GNU GPL license at http://sipros.omicsbio.org.
- Research Organization:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- Gordon and Betty Moore Foundation (GBMF); USDOE Office of Science (SC), Biological and Environmental Research (BER)
- Grant/Contract Number:
- AC05-00OR22725; SC0010566
- OSTI ID:
- 1625293
- Journal Information:
- Bioinformatics, Journal Name: Bioinformatics Journal Issue: 5 Vol. 34; ISSN 1367-4803
- Publisher:
- Oxford University PressCopyright Statement
- Country of Publication:
- United States
- Language:
- English
Similar Records
Fast and accurate database searches with MS-GF+Percolator
Optimizing metaproteomics database construction: lessons from a study of the vaginal microbiome
Metaproteomics: extracting and mining proteome information to characterize metabolic activities in microbial communities
Journal Article
·
Thu Feb 27 23:00:00 EST 2014
· Journal of Proteome Research, 13(2):890-897
·
OSTI ID:1126323
Optimizing metaproteomics database construction: lessons from a study of the vaginal microbiome
Journal Article
·
Thu Jun 22 20:00:00 EDT 2023
· mSystems
·
OSTI ID:2229120
Metaproteomics: extracting and mining proteome information to characterize metabolic activities in microbial communities
Journal Article
·
Tue Dec 31 23:00:00 EST 2013
· Current Protocols in Bioinformatics
·
OSTI ID:1149761