{"doi":"10.1021/acs.jproteome.2c00075","title":"Sensitive and Specific Spectral Library Searching with CompOmics Spectral Library Searching Tool and Percolator","abstract":"Maintaining high sensitivity while limiting false positives is a key challenge in peptide identification from mass spectrometry data. Here, we investigate the effects of integrating the machine learning-based postprocessor Percolator into our spectral library searching tool COSS (CompOmics Spectral library Searching tool). To evaluate the effects of this postprocessing, we have used 40 data sets from 2 different projects and have searched these against the NIST and MassIVE spectral libraries. The searching is carried out using 2 spectral library search tools, COSS and MSPepSearch with and without Percolator postprocessing, and using sequence database search engine MS-GF+ as a baseline comparator. The addition of the Percolator rescoring step to COSS is effective and results in a substantial improvement in sensitivity and specificity of the identifications. COSS is freely available as open source under the permissive Apache2 license, and binaries and source code are found at https://github.com/compomics/COSS.","journal":"Journal of Proteome Research","year":2022,"id":281288,"datarank":0.5136267741598242,"base_score":2.1972245773362196,"endowment":2.1972245773362196,"self_citation_contribution":0.32958368660043297,"citation_network_contribution":0.18404308755939122,"self_endowment_contribution":0.32958368660043297,"citer_contribution":0.18404308755939122,"corpus_percentile":null,"corpus_rank":null,"citation_count":8,"citer_count":7,"citers_with_citation_signal":5,"citers_with_endowment":5,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9178,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":499569,"name":"Ralf Gabriels","orcid":"0000-0002-1679-1711","position":1,"is_corresponding":false},{"id":679764,"name":"Robbin Bouwmeester","orcid":"0000-0001-6807-7029","position":2,"is_corresponding":false},{"id":557230,"name":"Tim Van Den Bossche","orcid":"0000-0002-5916-2587","position":3,"is_corresponding":false},{"id":318370,"name":"Elien Vandermarliere","orcid":"0000-0001-5514-1060","position":4,"is_corresponding":false},{"id":44560,"name":"Lennart Martens","orcid":"0000-0003-4277-658X","position":5,"is_corresponding":false},{"id":228804,"name":"Pieter‐Jan Volders","orcid":"0000-0002-2685-2637","position":6,"is_corresponding":false},{"id":499567,"name":"Genet Abay Shiferaw","orcid":"0000-0001-9956-417X","position":0,"is_corresponding":true}],"reference_count":32,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T00:29:07.472902Z","pmid":"35446579","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}