{"doi":"10.1109/bibm55620.2022.9995401","title":"FineFDR: Fine-grained Taxonomy-specific False Discovery Rates Control in Metaproteomics","abstract":null,"journal":"2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","year":2022,"id":632711,"datarank":0.29188652235829704,"base_score":1.9459101490553132,"endowment":1.9459101490553132,"self_citation_contribution":0.29188652235829704,"citation_network_contribution":0.0,"self_endowment_contribution":0.29188652235829704,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":6,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":717415,"name":"Shichao Feng","orcid":null,"position":1,"is_corresponding":false},{"id":49492,"name":"Chongle Pan","orcid":"0000-0003-2860-0334","position":2,"is_corresponding":false},{"id":869677,"name":"Xuan Guo","orcid":"0000-0001-5168-6311","position":3,"is_corresponding":false},{"id":1640156,"name":"Shengze Wang","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"FineFDR: Fine-grained Taxonomy-specific False Discovery Rates Control in Metaproteomics","abstract":"Microbial community proteomics, also termed metaproteomics, investigates all proteins expressed by a microbiota. Tandem mass spectrometry (MS/MS) is the typical method for identifying proteins in metaproteomics, which involves searching the mass spectra against a protein sequence database. A major post-analysis step is controlling the false discovery rate (FDR), i.e., the ratio of false positives to the total number of annotations. The current popular target-decoy FDR estimation method treats all the peptides and proteins equally and overlooks that they could have varied probabilities of being identified. In this study, we report FineFDR, a framework for FDR assessment at fine-grained levels with taxonomy information considered. FineFDR groups the identified peptide-spectrum matches, peptides, and proteins from different taxonomic units and estimates the FDR in each group separately. Empirical experiments on the simulated and real-world data sets demonstrate that our FineFDR achieved higher precision and more peptide and protein identifications when compared to the state-of-the-art methods, such as Comet, Percolator, TIDD, and Tailor. FineFDR is freely available under the GNU GPL license at https://github.com/Biocomputing-Research-Group/FDR.","is_dataset_classified":null,"base_score":1.9459101490553132,"endowment":1.9459101490553132,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"36910011","pmcid":"PMC9998077","openalex_id":"https://openalex.org/W4313413356","authors":[],"funders":[{"funder_name":"NLM NIH HHS","grant_id":"R15 LM013460","title":null},{"funder_name":"NCCIH NIH HHS","grant_id":"R01 AT011618","title":null}],"total_grants":2,"fwci":14.3511,"citation_percentile":0.99183976,"influential_citations":0,"citation_trend":[{"year":2023,"count":1},{"year":2024,"count":5}],"oa_status":"green","license":"https://doi.org/10.15223/policy-029","oa_locations":[{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9998077","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9998077","host_type":"repository"},{"url":"http://xplorestaging.ieee.org/ielx7/9994793/9994847/09995401.pdf?arnumber=9995401","host_type":"publisher"},{"url":"https://doi.org/10.1109/bibm55620.2022.9995401","host_type":"conference"},{"url":"https://pubmed.ncbi.nlm.nih.gov/36910011","host_type":"repository"}],"fields_of_study":["Advanced Proteomics Techniques and Applications","Identification and Quantification in Food","Mass Spectrometry Techniques and Applications"],"mesh_terms":[],"keywords":["False discovery rate","Metaproteomics","False positive paradox","Proteogenomics","Computer science","Computational biology","Database search engine","False positives and false negatives","Data mining","Tandem mass spectrometry","Proteomics","Mass spectrometry","Biology","Artificial intelligence","Information retrieval","Chemistry","Search engine","Chromatography","Genomics","Genome","Biochemistry","Target-decoy Search","Taxonomy-Specific Fdr Control"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Partnerships for the goals"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[{"name":"pxd"}],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-06T10:13:42.335853Z","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":[]}