{"entity": "publication", "iuid": "aab16dd656aa430cb47450fac81f6274", "timestamp": "2026-08-20T20:57:29.638Z", "links": {"self": {"href": "https://publications-affiliated.scilifelab.se/publication/aab16dd656aa430cb47450fac81f6274.json"}, "display": {"href": "https://publications-affiliated.scilifelab.se/publication/aab16dd656aa430cb47450fac81f6274"}}, "title": "Triqler for Protein Summarization of Data from Data-Independent Acquisition Mass Spectrometry.", "authors": [{"family": "Truong", "given": "Patrick", "initials": "P"}, {"family": "The", "given": "Matthew", "initials": "M", "orcid": "0000-0002-5401-5553", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/9d8d7d850ed24f92b9506b203ca63ed1.json"}}, {"family": "K\u00e4ll", "given": "Lukas", "initials": "L", "orcid": "0000-0001-5689-9797", "researcher": {"href": "https://publications-affiliated.scilifelab.se/researcher/b4464f2bf868498fa6d149a4a6d60e8b.json"}}], "type": "journal article", "published": "2023-04-07", "journal": {"title": "J. Proteome Res.", "issn": "1535-3907", "volume": "22", "issue": "4", "pages": "1359-1366", "issn-l": "1535-3893"}, "abstract": "A frequent goal, or subgoal, when processing data from a quantitative shotgun proteomics experiment is a list of proteins that are differentially abundant under the examined experimental conditions. Unfortunately, obtaining such a list is a challenging process, as the mass spectrometer analyzes the proteolytic peptides of a protein rather than the proteins themselves. We have previously designed a Bayesian hierarchical probabilistic model, Triqler, for combining peptide identification and quantification errors into probabilities of proteins being differentially abundant. However, the model was developed for data from data-dependent acquisition. Here, we show that Triqler is also compatible with data-independent acquisition data after applying minor alterations for the missing value distribution. Furthermore, we find that it has better performance than a set of compared state-of-the-art protein summarization tools when evaluated on data-independent acquisition data.", "doi": "10.1021/acs.jproteome.2c00607", "pmid": "36988210", "labels": [], "xrefs": [{"db": "pmc", "key": "PMC10088044"}], "notes": [], "created": "2026-08-20T08:11:42.307Z", "modified": "2026-08-20T08:11:42.435Z"}