{"id":"W3028658133","doi":"10.1186/s13059-020-02038-8","title":"Personalized and graph genomes reveal missing signal in epigenomic data","year":2020,"lang":"en","type":"article","venue":"Genome biology","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill Genome Centre; McGill University Health Centre; McGill University and Génome Québec Innovation Centre; McGill University","funders":"Canadian Institutes of Health Research; Compute Canada","keywords":"Epigenomics; Biology; Human genetics; Genome Biology; Computational biology; Genome; Genomics; Graph; Evolutionary biology; Genetics; Computer science; Theoretical computer science; DNA methylation; 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":[0.001387917,0.0004009427,0.0004039982,0.001416315,0.0002707919,0.0006680421,0.000493685,0.0008774612,0.001687596],"category_scores_gemma":[0.006811424,0.000264532,0.0004594229,0.001679474,0.00040917,0.0006998079,0.0007436398,0.0006352115,0.0003553268],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004442963,"about_ca_system_score_gemma":0.000245181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008351229,"about_ca_topic_score_gemma":0.001892355,"domain_scores_codex":[0.9988166,0.0002997042,0.00006054362,0.0004473884,0.0002862117,0.00008957841],"domain_scores_gemma":[0.99388,0.004092864,0.0008764646,0.0007404432,0.0002806509,0.0001294223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003134473,0.0002170253,0.3270561,0.001498277,0.00162647,0.001273697,0.000582909,0.0559292,0.4789649,0.008066107,0.004928408,0.1167224],"study_design_scores_gemma":[0.00009553922,0.0004993003,0.4875783,0.0001017999,0.0008796573,0.00379798,0.0003976368,0.2345905,0.2209411,0.02531238,0.02565387,0.0001521217],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8653075,0.0009578074,0.1195075,0.0002533405,0.00004916905,0.00005335805,0.01041146,0.002074528,0.001385345],"genre_scores_gemma":[0.8920202,0.0002978028,0.08867742,0.00020668,0.00003294062,0.00006514629,0.01777212,0.0003795008,0.0005482183],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001687596,"threshold_uncertainty_score":0.007340133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02609817136561877,"score_gpt":0.2537285373061441,"score_spread":0.2276303659405253,"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."}}