{"doi":"10.1101/2022.05.11.491571","title":"Improving peptide-level mass spectrometry analysis via double competition","abstract":"Abstract The analysis of shotgun proteomics data often involves generating lists of inferred peptide-spectrum matches (PSMs) and/or of peptides. The canonical approach for generating these discovery lists is by controlling the false discovery rate (FDR), most commonly through target-decoy competition (TDC). At the PSM level, TDC is implemented by competing each spectrum’s best-scoring target (real) peptide match with its best match against a decoy database. This PSM-level procedure can be adapted to the peptide level by selecting the top-scoring PSM per peptide prior to FDR estimation. Here we first highlight and empirically augment a little-known previous work by He et al., which showed that TDC-based PSM-level FDR estimates can be liberally biased. We thus propose that researchers instead focus on peptide-level analysis. We then investigate three ways to carry out peptide-level TDC and show that the most common method (“PSM-only”) offers the lowest statistical power in practice. An alternative approach that carries out a double competition, first at the PSM and then at the peptide level (“PSM-and-peptide”), is the most powerful method, yielding an average increase of 17% more discovered peptides at a 1% FDR threshold relative to the PSM-only method.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2022,"id":299197,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":4,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9615,"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":889807,"name":"Temana Short","orcid":null,"position":1,"is_corresponding":false},{"id":4958,"name":"William Stafford Noble","orcid":"0000-0001-7283-4715","position":2,"is_corresponding":false},{"id":584848,"name":"Uri Keich","orcid":"0000-0002-3209-5011","position":3,"is_corresponding":false},{"id":584846,"name":"Andy Lin","orcid":"0000-0003-0072-612X","position":0,"is_corresponding":true}],"reference_count":34,"raw_metadata":null,"created_at":"2026-07-19T00:31:40.528568Z","pmid":null,"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":[]}