{"doi":"10.1093/bioinformatics/btad595","title":"compleasm: a faster and more accurate reimplementation of BUSCO","abstract":"<h4>Motivation</h4>Evaluating the gene completeness is critical to measuring the quality of a genome assembly. An incomplete assembly can lead to errors in gene predictions, annotation, and other downstream analyses. Benchmarking Universal Single-Copy Orthologs (BUSCO) is a widely used tool for assessing the completeness of genome assembly by testing the presence of a set of single-copy orthologs conserved across a wide range of taxa. However, BUSCO is slow particularly for large genome assemblies. It is cumbersome to apply BUSCO to a large number of assemblies.<h4>Results</h4>Here, we present compleasm, an efficient tool for assessing the completeness of genome assemblies. Compleasm utilizes the miniprot protein-to-genome aligner and the conserved orthologous genes from BUSCO. It is 14 times faster than BUSCO for human assemblies and reports a more accurate completeness of 99.6% than BUSCO's 95.7%, which is in close agreement with the annotation completeness of 99.5% for T2T-CHM13.<h4>Availability and implementation</h4>https://github.com/huangnengCSU/compleasm.","journal":"Bioinformatics","year":2023,"id":12648,"datarank":0.8725666739944807,"base_score":5.817111159963204,"endowment":5.817111159963204,"self_citation_contribution":0.8725666739944807,"citation_network_contribution":0.0,"self_endowment_contribution":0.8725666739944807,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":335,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.0422,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-09-27","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":30887,"name":"Alexandra P. Lewis","orcid":"0000-0002-6195-4786","position":1,"is_corresponding":false},{"id":24483,"name":"Neng Huang","orcid":"0000-0001-7187-0749","position":0,"is_corresponding":true}],"reference_count":13,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-03-01T18:20:47.508186Z","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":[]}