{"id":"W1891158457","doi":"10.1093/bioinformatics/btv615","title":"funtooNorm: an R package for normalization of DNA methylation data when there are multiple cell or tissue types","year":2015,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Child and Family Research Institute; University of British Columbia; Douglas Mental Health University Institute; McGill University; Centre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean; Université de Sherbrooke; McGill University Health Centre; Canadian Institute for Advanced Research; Jewish General Hospital","funders":"Canadian Institutes of Health Research","keywords":"Normalization (sociology); DNA methylation; DNA; Computer science; Computational biology; Methylation; R package; Biology; Genetics; Programming language; 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":[0.008815595,0.003622524,0.002729564,0.003021551,0.00113218,0.002911289,0.003930769,0.001390543,0.05586577],"category_scores_gemma":[0.042329,0.002071368,0.003221671,0.003227958,0.001559679,0.002319752,0.003926427,0.003990416,0.05159553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001004676,"about_ca_system_score_gemma":0.003595882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003206544,"about_ca_topic_score_gemma":0.004595292,"domain_scores_codex":[0.9942381,0.0021992,0.0004058214,0.001495721,0.00136885,0.0002922334],"domain_scores_gemma":[0.9875415,0.007552444,0.0008991876,0.002141167,0.001543596,0.000322117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009972617,0.00009320285,0.009729269,0.003484491,0.001828796,0.0005030984,0.0006653036,0.01580827,0.02035426,0.01361003,0.7356547,0.1972714],"study_design_scores_gemma":[0.0005622489,0.0002724596,0.0139474,0.0006270629,0.0008788165,0.00154348,0.0001400054,0.1064053,0.05768787,0.07625563,0.7410827,0.0005970236],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.00390444,0.0009243086,0.6965391,0.0007677691,0.0005129409,0.0003797594,0.06566583,0.2263356,0.004970269],"genre_scores_gemma":[0.02974845,0.0008934056,0.6754365,0.001257022,0.0002502989,0.003458379,0.09299953,0.1861071,0.009849258],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.05586577,"threshold_uncertainty_score":0.1868896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07610816683406356,"score_gpt":0.3102720229849514,"score_spread":0.2341638561508879,"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."}}