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      Universal database search tool for proteomics

      research-article
      1 , 1
      Nature communications

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          Abstract

          Mass spectrometry (MS) instruments and experimental protocols are rapidly advancing, but the software tools to analyze tandem mass spectra are lagging behind. We present a database search tool MS-GF+ that is sensitive (it identifies more peptides than most other database search tools) and universal (it works well for diverse types of spectra, different configurations of MS instruments and different experimental protocols). We benchmark MS-GF+ using diverse spectral datasets: (i) spectra of varying fragmentation methods; (ii) spectra of multiple enzyme digests; (iii) spectra of phosphorylated peptides; (iv) spectra of peptides with unusual fragmentation propensities produced by a novel alpha-lytic protease. For all these datasets, MS-GF+ significantly increases the number of identified peptides compared to commonly used methods for peptide identifications. We emphasize that while MS-GF+ is not specifically designed for any particular experimental set-up, it improves upon the performance of tools specifically designed for these applications (e.g., specialized tools for phosphoproteomics).

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          Most cited references47

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          Is Open Access

          Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences

          Increased reliance on computational approaches in the life sciences has revealed grave concerns about how accessible and reproducible computation-reliant results truly are. Galaxy http://usegalaxy.org, an open web-based platform for genomic research, addresses these problems. Galaxy automatically tracks and manages data provenance and provides support for capturing the context and intent of computational methods. Galaxy Pages are interactive, web-based documents that provide users with a medium to communicate a complete computational analysis.
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            Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search.

            We present a statistical model to estimate the accuracy of peptide assignments to tandem mass (MS/MS) spectra made by database search applications such as SEQUEST. Employing the expectation maximization algorithm, the analysis learns to distinguish correct from incorrect database search results, computing probabilities that peptide assignments to spectra are correct based upon database search scores and the number of tryptic termini of peptides. Using SEQUEST search results for spectra generated from a sample of known protein components, we demonstrate that the computed probabilities are accurate and have high power to discriminate between correctly and incorrectly assigned peptides. This analysis makes it possible to filter large volumes of MS/MS database search results with predictable false identification error rates and can serve as a common standard by which the results of different research groups are compared.
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              TANDEM: matching proteins with tandem mass spectra.

              Tandem mass spectra obtained from fragmenting peptide ions contain some peptide sequence specific information, but often there is not enough information to sequence the original peptide completely. Several proprietary software applications have been developed to attempt to match the spectra with a list of protein sequences that may contain the sequence of the peptide. The application TANDEM was written to provide the proteomics research community with a set of components that can be used to test new methods and algorithms for performing this type of sequence-to-data matching. The source code and binaries for this software are available at http://www.proteome.ca/opensource.html, for Windows, Linux and Macintosh OSX. The source code is made available under the Artistic License, from the authors.
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                Author and article information

                Journal
                101528555
                37539
                Nat Commun
                Nat Commun
                Nature communications
                2041-1723
                25 August 2015
                31 October 2014
                2014
                26 September 2016
                : 5
                : 5277
                Affiliations
                [1 ]Department of Computer Science and Engineering, University of California San Diego, La Jolla 92093, USA
                Author notes
                Corresponding author: Pavel A. Pevzner, EBU3b 4236 9500 Gilman Drive La Jolla, CA 92093, ppevzner@ 123456eng.ucsd.edu

                Addresses: Sangtae Kim, 3335 Innovation Blvd, Richland, WA 99354

                Article
                NIHMS629163
                10.1038/ncomms6277
                5036525
                25358478
                d65615df-a989-480d-bdf0-871a09401ff9

                Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms

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