Qscore: an algorithm for evaluating SEQUEST database search results
A scoring procedure is described for measuring the quality of the results for protein identifications obtained from spectral matching of MS/MS data using the Sequest database search program. The scoring system is essentially probabilistic and operates by estimating the probability that a protein ide...
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Veröffentlicht in: | Journal of the American Society for Mass Spectrometry 2002-04, Vol.13 (4), p.378-386 |
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creator | Moore, Roger E. Young, Mary K. Lee, Terry D. |
description | A scoring procedure is described for measuring the quality of the results for protein identifications obtained from spectral matching of MS/MS data using the Sequest database search program. The scoring system is essentially probabilistic and operates by estimating the probability that a protein identification has come about by chance. The probability is based on the number of identified peptides from the protein, the total number of identified peptides, and the fraction of distinct tryptic peptides from the database that are present in the identified protein. The score is not strictly a probability, as it also incorporates information about the quality of the individual peptide matches. The result of using Qscore on a large test set of data was similar to that achieved using approaches that validate individual spectral matches, with only a narrow overlap in scores between identified proteins and false positive matches. In direct comparison with a published method of evaluating Sequest results, Qscore was able to identify an equivalent number of proteins without any identifiable false positive assignments. Qscore greatly reduces the number of Sequest protein identifications that have to be validated manually. |
doi_str_mv | 10.1016/S1044-0305(02)00352-5 |
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The scoring system is essentially probabilistic and operates by estimating the probability that a protein identification has come about by chance. The probability is based on the number of identified peptides from the protein, the total number of identified peptides, and the fraction of distinct tryptic peptides from the database that are present in the identified protein. The score is not strictly a probability, as it also incorporates information about the quality of the individual peptide matches. The result of using Qscore on a large test set of data was similar to that achieved using approaches that validate individual spectral matches, with only a narrow overlap in scores between identified proteins and false positive matches. In direct comparison with a published method of evaluating Sequest results, Qscore was able to identify an equivalent number of proteins without any identifiable false positive assignments. 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The scoring system is essentially probabilistic and operates by estimating the probability that a protein identification has come about by chance. The probability is based on the number of identified peptides from the protein, the total number of identified peptides, and the fraction of distinct tryptic peptides from the database that are present in the identified protein. The score is not strictly a probability, as it also incorporates information about the quality of the individual peptide matches. The result of using Qscore on a large test set of data was similar to that achieved using approaches that validate individual spectral matches, with only a narrow overlap in scores between identified proteins and false positive matches. In direct comparison with a published method of evaluating Sequest results, Qscore was able to identify an equivalent number of proteins without any identifiable false positive assignments. 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Psychology</topic><topic>General aspects, investigation methods</topic><topic>Mass Spectrometry</topic><topic>Molecular Sequence Data</topic><topic>Peptides</topic><topic>Peptides - chemistry</topic><topic>Proteins</topic><topic>Proteins - chemistry</topic><topic>Software</topic><topic>Spectrometry, Mass, Electrospray Ionization</topic><topic>Statistical analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Moore, Roger E.</creatorcontrib><creatorcontrib>Young, Mary K.</creatorcontrib><creatorcontrib>Lee, Terry D.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Research Library (Corporate)</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of the American Society for Mass Spectrometry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Moore, Roger E.</au><au>Young, Mary K.</au><au>Lee, Terry D.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Qscore: an algorithm for evaluating SEQUEST database search results</atitle><jtitle>Journal of the American Society for Mass Spectrometry</jtitle><addtitle>J Am Soc Mass Spectrom</addtitle><date>2002-04-01</date><risdate>2002</risdate><volume>13</volume><issue>4</issue><spage>378</spage><epage>386</epage><pages>378-386</pages><issn>1044-0305</issn><eissn>1879-1123</eissn><abstract>A scoring procedure is described for measuring the quality of the results for protein identifications obtained from spectral matching of MS/MS data using the Sequest database search program. 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subjects | Algorithms Amino Acid Sequence Analytical, structural and metabolic biochemistry Biological and medical sciences Chromatography, High Pressure Liquid Databases, Factual Fundamental and applied biological sciences. Psychology General aspects, investigation methods Mass Spectrometry Molecular Sequence Data Peptides Peptides - chemistry Proteins Proteins - chemistry Software Spectrometry, Mass, Electrospray Ionization Statistical analysis |
title | Qscore: an algorithm for evaluating SEQUEST database search results |
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