{"doi":"10.1101/2022.01.15.476448","title":"RASCL: Rapid Assessment Of SARS-CoV-2 Clades Through Molecular Sequence Analysis","abstract":"An important component of efforts to manage the ongoing COVID19 pandemic is the R apid A ssessment of how natural selection contributes to the emergence and proliferation of potentially dangerous S ARS-CoV-2 lineages and CL ades (RASCL). The RASCL pipeline enables continuous comparative phylogenetics-based selection analyses of rapidly growing clade-focused genome surveillance datasets, such as those produced following the initial detection of potentially dangerous variants. From such datasets RASCL automatically generates down-sampled codon alignments of individual genes/ORFs containing contextualizing background reference sequences, analyzes these with a battery of selection tests, and outputs results as both machine readable JSON files, and interactive notebook-based visualizations. AVAILABILITY: RASCL is available from a dedicated repository at https://github.com/veg/RASCL and as a Galaxy workflow https://usegalaxy.eu/u/hyphy/w/rascl . Existing clade/variant analysis results are available here: https://observablehq.com/@aglucaci/rascl . CONTACT: Dr. Sergei L Kosakovsky Pond ( spond@temple.edu ). SUPPLEMENTARY INFORMATION: N/A.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2022,"id":299723,"datarank":0.20794415416798362,"base_score":1.3862943611198906,"endowment":1.3862943611198906,"self_citation_contribution":0.20794415416798362,"citation_network_contribution":0.0,"self_endowment_contribution":0.20794415416798362,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.8726,"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":813448,"name":"Jordan D. Zehr","orcid":"0000-0003-2099-4172","position":1,"is_corresponding":false},{"id":23978,"name":"Stephen D. Shank","orcid":"0000-0003-0734-9953","position":2,"is_corresponding":false},{"id":478955,"name":"Dave Bouvier","orcid":"0000-0001-8031-5069","position":3,"is_corresponding":false},{"id":738611,"name":"Mei Han","orcid":"0000-0002-2567-5464","position":4,"is_corresponding":false},{"id":19433,"name":"Anton Nekrutenko","orcid":"0000-0002-5987-8032","position":5,"is_corresponding":false},{"id":84014,"name":"Darren P. Martin","orcid":"0000-0002-8785-0870","position":6,"is_corresponding":false},{"id":69662,"name":"Sergei L. Kosakovsky Pond","orcid":"0000-0003-4817-4029","position":7,"is_corresponding":false},{"id":564564,"name":"Alexander G. Lucaci","orcid":"0000-0002-4896-6088","position":0,"is_corresponding":true}],"reference_count":29,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T00:31:49.412501Z","pmid":"35075458","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":[]}