{"id":"W2009170877","doi":"10.1016/j.tig.2010.10.006","title":"The study of eQTL variations by RNA-seq: from SNPs to phenotypes","year":2010,"lang":"en","type":"review","venue":"Trends in Genetics","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":238,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University and Génome Québec Innovation Centre","funders":"","keywords":"Biology; Expression quantitative trait loci; Genetics; Computational biology; Phenotype; Gene; Single-nucleotide polymorphism; Quantitative trait locus; RNA-Seq; Genomics; Genetic variation; RNA; Regulation of gene expression; Gene expression; Transcriptome; Genome; Genotype","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002468874,0.0002450249,0.0005048628,0.0001184428,0.0000890179,0.00003906576,0.0006996772,0.0002870963,0.00002617689],"category_scores_gemma":[0.0001005869,0.0001745764,0.0001357494,0.0003212843,0.00004888222,9.055503e-7,0.0002833257,0.0003301222,0.00001064583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001797367,"about_ca_system_score_gemma":0.0001140833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002475806,"about_ca_topic_score_gemma":0.002068771,"domain_scores_codex":[0.9983897,0.0001864485,0.0004907182,0.0003937242,0.0002365052,0.0003029316],"domain_scores_gemma":[0.9987227,0.00008594241,0.0001634966,0.0008591975,0.00006315416,0.0001054518],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00000975952,0.0001627118,0.00004343298,0.00005485936,0.0001132531,0.000001540973,0.00006112525,0.000009488037,0.003055676,0.000009016459,0.002581781,0.9938974],"study_design_scores_gemma":[0.0002635826,0.0003794795,0.0001654497,0.0001296222,0.0001220664,7.243087e-7,0.00004933511,0.00001519171,0.0004115711,0.00001782092,0.9982304,0.0002147397],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01846379,0.9800393,0.00008359605,0.00003022695,0.0001898776,0.0004059814,0.0002202533,0.000004329701,0.000562639],"genre_scores_gemma":[0.002049543,0.9932038,0.0005026769,0.00001571189,0.0002290733,0.0001152478,0.0003744594,0.00004608691,0.003463373],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9956486,"threshold_uncertainty_score":0.7119017,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03976888589396656,"score_gpt":0.3722743431005078,"score_spread":0.3325054572065413,"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."}}