{"id":"W2518845767","doi":"10.1186/s12920-016-0220-7","title":"Immunoseq: the identification of functionally relevant variants through targeted capture and sequencing of active regulatory regions in human immune cells","year":2016,"lang":"en","type":"article","venue":"BMC Medical Genomics","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université du Québec à Chicoutimi; McGill University and Génome Québec Innovation Centre","funders":"Medical Research Council; National Institute for Health and Care Research; Canadian Institutes of Health Research; Forskningsrådet om Hälsa, Arbetsliv och Välfärd; Knut och Alice Wallenbergs Stiftelse; Vetenskapsrådet","keywords":"Biology; Human genetics; Computational biology; Genome-wide association study; Genetics; Gene; Transcriptome; Exome sequencing; DNA microarray; Genomics; Exome; Human genome; Genome; Allele; Genetic association; Phenotype; Gene expression; Single-nucleotide polymorphism; Genotype","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":[0.00108966,0.0005991126,0.0005566131,0.0008788506,0.0002967989,0.0006304597,0.0004565966,0.0004749496,0.001742912],"category_scores_gemma":[0.001464312,0.0002631257,0.0007330799,0.0005855759,0.0003361111,0.0002120208,0.0007410523,0.0005481163,0.0007526744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002308976,"about_ca_system_score_gemma":0.0003088029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009212422,"about_ca_topic_score_gemma":0.001729381,"domain_scores_codex":[0.9992102,0.0001280412,0.00004576628,0.0003077702,0.0002424026,0.00006572613],"domain_scores_gemma":[0.9994549,0.000266688,0.0001019908,0.0000555519,0.00007444734,0.00004641066],"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":[0.0007457426,0.000062414,0.01534573,0.0002933973,0.0002243178,0.0002819627,0.0001910347,0.002220989,0.9443893,0.0008547852,0.002091752,0.03329847],"study_design_scores_gemma":[0.0004055481,0.001239451,0.1894785,0.0001071211,0.000719026,0.003040661,0.000232154,0.06571604,0.6891331,0.004344074,0.04542407,0.0001601944],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6497391,0.003347483,0.3136843,0.0004662523,0.0002043361,0.0004646982,0.02640741,0.002402474,0.003283933],"genre_scores_gemma":[0.6756868,0.001528588,0.2841345,0.001394115,0.0002571954,0.0009902788,0.0307452,0.0007089093,0.004554398],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001742912,"threshold_uncertainty_score":0.005830586,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01113948981729969,"score_gpt":0.2324753274125457,"score_spread":0.221335837595246,"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."}}