{"id":"W2758143621","doi":"10.1111/cts.12511","title":"Whole Transcriptome Profiling: An RNA‐Seq Primer and Implications for Pharmacogenomics Research","year":2017,"lang":"en","type":"review","venue":"Clinical and Translational Science","topic":"RNA and protein synthesis mechanisms","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Genetics","funders":"National Institute of General Medical Sciences; National Institutes of Health","keywords":"Biology; Transcriptome; Gene; Genetics; Computational biology; Gene expression; RNA-Seq; Alternative splicing; Pharmacogenomics; Gene expression profiling; RNA; Locus (genetics); Regulation of gene expression; Phenotype; Non-coding RNA; Exon","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007200657,0.001153896,0.001468873,0.001429986,0.0006538751,0.002997143,0.001328745,0.002598355,0.002724358],"category_scores_gemma":[0.003744646,0.001007344,0.001236606,0.002035116,0.001406196,0.001820471,0.001070976,0.00428452,0.003191363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001389975,"about_ca_system_score_gemma":0.001383872,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007721327,"about_ca_topic_score_gemma":0.001116965,"domain_scores_codex":[0.997769,0.0008021554,0.0001210452,0.0004884375,0.0006900801,0.0001292744],"domain_scores_gemma":[0.997617,0.00110711,0.0002087589,0.0001822867,0.0007156025,0.0001692975],"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":[0.0005511334,0.0002582949,0.003282843,0.002843614,0.0002116485,0.0004014935,0.0003523543,0.0039038,0.3758303,0.0325983,0.05436334,0.525403],"study_design_scores_gemma":[0.00009950549,0.001194925,0.01480981,0.002031119,0.0003445514,0.001876146,0.000466616,0.02691048,0.1966508,0.06249377,0.6926963,0.0004258641],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01602028,0.2671739,0.6374663,0.04041609,0.007573579,0.0009765704,0.01005034,0.003080083,0.01724282],"genre_scores_gemma":[0.05838566,0.2909793,0.5946895,0.01863873,0.004834661,0.003014682,0.009280708,0.001488676,0.0186881],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007200657,"threshold_uncertainty_score":0.03808117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4533281413841591,"score_gpt":0.5566978987380172,"score_spread":0.1033697573538582,"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."}}