{"id":"W2096746187","doi":"10.1101/gr.180281.114","title":"TITAN: inference of copy number architectures in clonal cell populations from tumor whole-genome sequence data","year":2014,"lang":"en","type":"article","venue":"Genome Research","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":429,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vancouver General Hospital; Ontario Genomics; University of British Columbia; British Columbia Centre on Substance Use; BC Cancer Agency","funders":"Natural Sciences and Engineering Research Council of Canada; Terry Fox Research Institute; Canadian Cancer Society Research Institute; Genome Canada; Canadian Institutes of Health Research; Genome British Columbia; Michael Smith Health Research BC","keywords":"Biology; Loss of heterozygosity; Genome; Genetics; Computational biology; Copy-number variation; Population; Somatic cell; Whole genome sequencing; Gene","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":[0.003230128,0.0005041165,0.0005846393,0.001014312,0.0006840106,0.001167748,0.001192661,0.0009202957,0.0008925165],"category_scores_gemma":[0.01014703,0.0006615871,0.001033531,0.0006340572,0.0009108867,0.000897722,0.001160816,0.0009970915,0.0001986333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001358856,"about_ca_system_score_gemma":0.001210315,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009971997,"about_ca_topic_score_gemma":0.01558471,"domain_scores_codex":[0.9993376,0.0002884237,0.00002720456,0.0002174271,0.00008730835,0.00004199428],"domain_scores_gemma":[0.9953865,0.003552785,0.0003671776,0.0003788815,0.0001784508,0.0001361996],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001629796,0.00004487978,0.02473651,0.00006760836,0.0001926598,0.0001466551,0.0001915357,0.940253,0.005889647,0.007416592,0.0007598944,0.02013812],"study_design_scores_gemma":[0.000006669915,0.00001071031,0.000907889,0.000002606077,0.000007417214,0.00003676582,0.000009125209,0.9938028,0.0007414827,0.004281688,0.0001875446,0.000005352695],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.4135509,0.0003003695,0.5818889,0.000318579,0.0000237083,0.000106213,0.001200237,0.001633987,0.0009770407],"genre_scores_gemma":[0.831832,0.0001841814,0.1637579,0.0001959698,0.00002696553,0.0002122063,0.002498031,0.0001985302,0.001094115],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009971997,"threshold_uncertainty_score":0.0198279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1119003118096085,"score_gpt":0.3951657348059641,"score_spread":0.2832654229963555,"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."}}