{"id":"W4410801543","doi":"10.1016/j.celrep.2025.115755","title":"Complete reference genome and pangenome improve genome-wide detection and interpretation of DNA methylation using sequencing and array data","year":2025,"lang":"en","type":"article","venue":"Cell Reports","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Children's Hospital; University of British Columbia","funders":"National Institute on Aging; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Institutes of Health; University of California Berkeley; Compute Canada; University of British Columbia; Wellcome Trust; Universidad de Costa Rica; Canadian Institute for Advanced Research; BC Children's Hospital","keywords":"Genome; DNA methylation; Biology; Genetics; Computational biology; Reference genome; DNA sequencing; DNA; Whole genome sequencing; Methylation; Gene; Gene expression","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":[0.005008569,0.001252535,0.001172849,0.003050779,0.0006816413,0.001519602,0.001465013,0.001342427,0.006352494],"category_scores_gemma":[0.01172582,0.0008000317,0.001161812,0.00358743,0.0004053218,0.0008657529,0.002095689,0.001328701,0.002976952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006994172,"about_ca_system_score_gemma":0.001545344,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003867908,"about_ca_topic_score_gemma":0.0125369,"domain_scores_codex":[0.9958585,0.001295985,0.0003181563,0.001400495,0.0008767144,0.0002501132],"domain_scores_gemma":[0.9955647,0.001205328,0.0004445267,0.001401839,0.001231446,0.0001521632],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00121801,0.0001056085,0.03736612,0.002333272,0.001120299,0.0004939939,0.0009653888,0.009644553,0.6719943,0.00981947,0.02009888,0.24484],"study_design_scores_gemma":[0.0002849243,0.0005409446,0.1465446,0.0004477059,0.001146132,0.002038241,0.0004515066,0.03461492,0.4783498,0.01407036,0.3212484,0.0002624688],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1577712,0.00920974,0.7599117,0.0009506448,0.0006149848,0.000311539,0.04652447,0.01359961,0.01110608],"genre_scores_gemma":[0.2058229,0.002362707,0.6998297,0.0007096998,0.000165127,0.0007038761,0.08212975,0.00320297,0.005073154],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006352494,"threshold_uncertainty_score":0.02648813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03105995969413185,"score_gpt":0.2724011571948039,"score_spread":0.241341197500672,"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."}}