Literature DB >> 28263070

Param-Medic: A Tool for Improving MS/MS Database Search Yield by Optimizing Parameter Settings.

Damon H May1, Kaipo Tamura1, William S Noble1,2.   

Abstract

In shotgun proteomics analysis, user-specified parameters are critical to database search performance and therefore to the yield of confident peptide-spectrum matches (PSMs). Two of the most important parameters are related to the accuracy of the mass spectrometer. Precursor mass tolerance defines the peptide candidates considered for each spectrum. Fragment mass tolerance or bin size determines how close observed and theoretical fragments must be to be considered a match. For either of these two parameters, too wide a setting yields randomly high-scoring false PSMs, whereas too narrow a setting erroneously excludes true PSMs, in both cases, lowering the yield of peptides detected at a given false discovery rate. We describe a strategy for inferring optimal search parameters by assembling and analyzing pairs of spectra that are likely to have been generated by the same peptide ion to infer precursor and fragment mass error. This strategy does not rely on a database search, making it usable in a wide variety of settings. In our experiments on data from a variety of instruments including Orbitrap and Q-TOF acquisitions, this strategy yields more high-confidence PSMs than using settings based on instrument defaults or determined by experts. Param-Medic is open-source and cross-platform. It is available as a standalone tool ( http://noble.gs.washington.edu/proj/param-medic/ ) and has been integrated into the Crux proteomics toolkit ( http://crux.ms ), providing automatic parameter selection for the Comet and Tide search engines.

Entities:  

Keywords:  database search; mass accuracy; tandem mass spectrometry

Mesh:

Substances:

Year:  2017        PMID: 28263070      PMCID: PMC5738039          DOI: 10.1021/acs.jproteome.7b00028

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  19 in total

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  6 in total

1.  Detecting Modifications in Proteomics Experiments with Param-Medic.

Authors:  Damon H May; Kaipo Tamura; William S Noble
Journal:  J Proteome Res       Date:  2019-03-05       Impact factor: 4.466

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