{"id":"W4403381371","doi":"10.1016/j.xgen.2024.100674","title":"Long-read sequencing of an advanced cancer cohort resolves rearrangements, unravels haplotypes, and reveals methylation landscapes","year":2024,"lang":"en","type":"article","venue":"Cell Genomics","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency; University of British Columbia; Canada's Michael Smith Genome Sciences Centre","funders":"British Columbia Knowledge Development Fund; National Institutes of Health; BC Cancer Foundation; Terry Fox Foundation; Genome British Columbia; Terry Fox Research Institute; Canada Foundation for Innovation; Canadian Cancer Society Research Institute; Canadian Institutes of Health Research; Genome Canada","keywords":"Haplotype; DNA methylation; Computational biology; Biology; Genetics; Methylation; Cohort; Cancer; Evolutionary biology; DNA sequencing; Gene; Bioinformatics; Medicine; Genotype; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009175351,0.0005517277,0.0007521743,0.001152282,0.0006499949,0.0008065085,0.0006648311,0.0008315032,0.004305052],"category_scores_gemma":[0.002460638,0.0002700718,0.0005041228,0.001294507,0.0002557408,0.0002811535,0.0009864898,0.0007058477,0.0017559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005427612,"about_ca_system_score_gemma":0.00083929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005630359,"about_ca_topic_score_gemma":0.01821205,"domain_scores_codex":[0.999356,0.00007944917,0.00005232244,0.0002921341,0.0001383529,0.00008185914],"domain_scores_gemma":[0.9982359,0.0005165853,0.0002430028,0.0004472701,0.0003332591,0.0002238226],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004135896,0.0003715071,0.5511581,0.001596111,0.001649076,0.002129704,0.0007252239,0.01133803,0.1604723,0.002790133,0.1489572,0.1146767],"study_design_scores_gemma":[0.0006019286,0.000714945,0.6669816,0.0002616578,0.0008731489,0.004325553,0.0005313739,0.01373755,0.05640303,0.006553381,0.2488546,0.0001612837],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.4710675,0.001930378,0.01091313,0.0007542087,0.0001145005,0.00009926236,0.5090727,0.001406146,0.00464218],"genre_scores_gemma":[0.2925693,0.0005551645,0.0106801,0.0005174944,0.00005933422,0.0001572493,0.692291,0.0002986441,0.002871745],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005630359,"threshold_uncertainty_score":0.01440185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01226342416880211,"score_gpt":0.2708570936523012,"score_spread":0.258593669483499,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}