{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,6,20]],"date-time":"2024-06-20T16:40:04Z","timestamp":1718901604500},"reference-count":74,"publisher":"The Royal Society of Chemistry","isbn-type":[{"value":"9781782624288","type":"print"},{"value":"9781782624288","type":"print"},{"value":"9781782629573","type":"electronic"},{"value":"9781782626732","type":"electronic"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,11,23]]},"abstract":"Identification and quantification of proteins by shotgun proteomics experiments is underpinned by the use of accurate masses and fragmentation patterns generated by tandem mass spectrometry. Assigning peptide sequences to tandem MS data is supported by a plethora of informatics tools. The majority of spectral identification software report arbitrary fitness scores reflecting the quality of a match, however, valid statistical metrics must be used to make sense of these scores and attribute a confidence to the peptide identifications. Accurately estimating the error and devising filtering routines to minimise incorrect and random identifications is essential for making valid and reproducible conclusions about the biology of the sample being analysed. This chapter discusses the statistical approaches used to evaluate and validate shotgun proteomics peptide to spectrum matches and provides a summary of software available for this purpose.<\/jats:p>","DOI":"10.1039\/9781782626732-00069","type":"book-chapter","created":{"date-parts":[[2016,11,15]],"date-time":"2016-11-15T11:00:18Z","timestamp":1479207618000},"page":"69-92","source":"Crossref","is-referenced-by-count":1,"title":["PSM Scoring and Validation"],"prefix":"10.1039","author":[{"given":"James C.","family":"Wright","sequence":"first","affiliation":[{"name":"Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus Hinxton, Cambridge UK jc4@sanger.ac.uk"}]},{"given":"Jyoti S.","family":"Choudhary","sequence":"additional","affiliation":[{"name":"Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus Hinxton, Cambridge UK jc4@sanger.ac.uk"}]}],"member":"292","reference":[{"issue":"3","key":"2023051920233370200_BK9781782624288-00069-cit1","doi-asserted-by":"crossref","first-page":"732","DOI":"10.1021\/acs.jproteome.5b00861","article-title":"Application of de novo sequencing to large-scale complex proteomics datasets","volume":"15","author":"Devabhaktuni","year":"2016","journal-title":"J. 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