{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,9]],"date-time":"2026-06-09T22:10:42Z","timestamp":1781043042755,"version":"3.54.1"},"reference-count":49,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2025,3,7]],"date-time":"2025-03-07T00:00:00Z","timestamp":1741305600000},"content-version":"vor","delay-in-days":35,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Poland [grant Preludium","award":["2020\/37\/N\/ST6\/04070"],"award-info":[{"award-number":["2020\/37\/N\/ST6\/04070"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,3,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Bottom-up mass spectrometry-based proteomics studies changes in protein abundance and structure across conditions. Since the currency of these experiments are peptides, i.e. subsets of protein sequences that carry the quantitative information, conclusions at a different level must be computationally inferred. The inference is particularly challenging in situations where the peptides are shared by multiple proteins or post-translational modifications. While many approaches infer the underlying abundances from unique peptides, there is a need to distinguish the quantitative patterns when peptides are shared.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>We propose a statistical approach for estimating protein abundances, as well as site occupancies of post-translational modifications, based on quantitative information from shared peptides. The approach treats the quantitative patterns of shared peptides as convex combinations of abundances of individual proteins or modification sites, and estimates the abundance of each source in a sample together with the weights of the combination. In simulation-based evaluations, the proposed approach improved the precision of estimated fold changes between conditions. We further demonstrated the practical utility of the approach in experiments with diverse biological objectives, ranging from protein degradation and thermal proteome stability, to changes in protein post-translational modifications.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The approach is implemented in an open-source R package MSstatsWeightedSummary. The package is currently available at https:\/\/github.com\/Vitek-Lab\/MSstatsWeightedSummary (doi: 10.5281\/zenodo.14662989). Code required to reproduce the results presented in this article can be found in a repository https:\/\/github.com\/mstaniak\/MWS_reproduction (doi: 10.5281\/zenodo.14656053).<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btaf046","type":"journal-article","created":{"date-parts":[[2025,1,31]],"date-time":"2025-01-31T18:22:51Z","timestamp":1738347771000},"source":"Crossref","is-referenced-by-count":2,"title":["Relative quantification of proteins and post-translational modifications in proteomic experiments with shared peptides: a weight-based approach"],"prefix":"10.1093","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4453-2178","authenticated-orcid":false,"given":"Mateusz","family":"Staniak","sequence":"first","affiliation":[{"name":"Faculty of Mathematics and Computer Science, University of Wroc\u0142aw , Wroc\u0142aw, 50-383,","place":["Poland"]},{"name":"Centre for Statistics, Hasselt University , Diepenbeek, 3590,","place":["Belgium"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ting","family":"Huang","sequence":"additional","affiliation":[{"name":"Khoury College of Computer Sciences, Northeastern University , Boston, MA, 02115,","place":["United States"]},{"name":"Barnett Institute of Chemical and Biological Analysis, Northeastern University , Boston, MA, 02115,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amanda M","family":"Figueroa-Navedo","sequence":"additional","affiliation":[{"name":"Barnett Institute of Chemical and Biological Analysis, Northeastern University , Boston, MA, 02115,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7301-2596","authenticated-orcid":false,"given":"Devon","family":"Kohler","sequence":"additional","affiliation":[{"name":"Khoury College of Computer Sciences, Northeastern University , Boston, MA, 02115,","place":["United 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CA, 94080,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Robert","family":"Blake","sequence":"additional","affiliation":[{"name":"Department of Biochemical and Cellular Pharmacology, Genentech, Inc. , South San Francisco, CA, 94080,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher M","family":"Rose","sequence":"additional","affiliation":[{"name":"Department of Microchemistry, Proteomics, and Lipidomics, Genentech, Inc. , South San Francisco, CA, 94080,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yingrong","family":"Xu","sequence":"additional","affiliation":[{"name":"Discovery Sciences, Pfizer Inc. , Groton, CT, 06340,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pierre M","family":"Jean Beltran","sequence":"additional","affiliation":[{"name":"Machine Learning and Computational Sciences, Pfizer 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