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Over the past two decades, target-decoy approaches (TDAs) and decoy-free approaches (DFAs) have been widely used to estimate FDR. TDAs use a database of decoy species to faithfully model score distributions of incorrect peptide-spectrum matches (PSMs). DFAs, on the other hand, fit two-component mixture models to learn the parameters of correct and incorrect PSM score distributions. While conceptually straightforward, both approaches lead to problems in practice, particularly in experiments that push instrumentation to the limit and generate low fragmentation-efficiency and low signal-to-noise-ratio spectra.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We introduce a new decoy-free framework for FDR estimation that generalizes present DFAs while exploiting more search data in a manner similar to TDAs. Our approach relies on multi-component mixtures, in which score distributions corresponding to the correct PSMs, best incorrect PSMs and second-best incorrect PSMs are modeled by the skew normal family. We derive EM algorithms to estimate parameters of these distributions from the scores of best and second-best PSMs associated with each experimental spectrum. We evaluate our models on multiple proteomics datasets and a HeLa cell digest case study consisting of more than a million spectra in total. We provide evidence of improved performance over existing DFAs and improved stability and speed over TDAs without any performance degradation. We propose that the new strategy has the potential to extend beyond peptide identification and reduce the need for TDA on all analytical platforms.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availabilityand implementation<\/jats:title><jats:p>https:\/\/github.com\/shawn-peng\/FDR-estimation.<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btaa807","type":"journal-article","created":{"date-parts":[[2020,9,8]],"date-time":"2020-09-08T11:11:23Z","timestamp":1599563483000},"page":"i745-i753","source":"Crossref","is-referenced-by-count":12,"title":["New mixture models for decoy-free false discovery rate estimation in mass spectrometry proteomics"],"prefix":"10.1093","volume":"36","author":[{"given":"Yisu","family":"Peng","sequence":"first","affiliation":[{"name":"Khoury College of Computer Sciences, Northeastern University , Boston, MA 02115, USA"}]},{"given":"Shantanu","family":"Jain","sequence":"additional","affiliation":[{"name":"Khoury College of Computer Sciences, Northeastern University , Boston, MA 02115, USA"}]},{"given":"Yong Fuga","family":"Li","sequence":"additional","affiliation":[{"name":"Illumina Inc. , San Diego, CA 92122, USA"}]},{"given":"Michal","family":"Gregu\u0161","sequence":"additional","affiliation":[{"name":"Department of Chemistry and Chemical Biology, Northeastern University , Boston, MA 02115, USA"},{"name":"Barnett Institute of Chemical and Biological Analysis, Northeastern University , Boston, MA 02115, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4691-8488","authenticated-orcid":false,"given":"Alexander R.","family":"Ivanov","sequence":"additional","affiliation":[{"name":"Department of Chemistry and Chemical Biology, Northeastern University , Boston, MA 02115, USA"},{"name":"Barnett Institute of Chemical and Biological Analysis, Northeastern University , Boston, MA 02115, USA"}]},{"given":"Olga","family":"Vitek","sequence":"additional","affiliation":[{"name":"Khoury College of Computer Sciences, Northeastern University , Boston, MA 02115, USA"},{"name":"Barnett Institute of Chemical and Biological Analysis, Northeastern University , Boston, MA 02115, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6769-0793","authenticated-orcid":false,"given":"Predrag","family":"Radivojac","sequence":"additional","affiliation":[{"name":"Khoury College of Computer Sciences, Northeastern University , Boston, MA 02115, USA"},{"name":"Department of Chemistry and Chemical Biology, Northeastern University , Boston, MA 02115, USA"},{"name":"Barnett Institute of Chemical and Biological Analysis, Northeastern University , Boston, MA 02115, USA"}]}],"member":"286","published-online":{"date-parts":[[2020,12,29]]},"reference":[{"key":"2023062409330182400_btaa807-B1","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1038\/nature01511","article-title":"Mass spectrometry-based proteomics","volume":"422","author":"Aebersold","year":"2003","journal-title":"Nature"},{"key":"2023062409330182400_btaa807-B2","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1007\/978-1-4939-3106-4_7","article-title":"False discovery rate estimation in proteomics","volume":"1362","author":"Aggarwal","year":"2016","journal-title":"Methods Mol. 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