{"id":"W3143983175","doi":"10.1101/2021.04.07.438882","title":"Discovery of target genes and pathways of blood trait loci using pooled CRISPR screens and single cell RNA sequencing","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"RNA modifications and cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Human Genome Research Institute; Canadian Institutes of Health Research; Defense Advanced Research Projects Agency; Sidney Kimmel Foundation; New York Genome Center; National Institute of General Medical Sciences; National Institute of Mental Health; Cancer Research Institute; American Heart Association; National Cancer Institute; National Institutes of Health","keywords":"Biology; Gene; Genetics; CRISPR; Genome; Genome-wide association study; Transcriptome; Genomics; Computational biology; Expression quantitative trait loci; Quantitative trait locus; CRISPR interference; Genome editing; Gene expression; Single-nucleotide polymorphism; Genotype","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008858851,0.0005391228,0.0006908143,0.0006274072,0.0003292761,0.0008097505,0.0004619467,0.000536688,0.002533352],"category_scores_gemma":[0.0005760383,0.0003246391,0.0006184964,0.0003529492,0.0004235671,0.0002109846,0.000793562,0.0009422334,0.000829675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004299093,"about_ca_system_score_gemma":0.0003615365,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009944921,"about_ca_topic_score_gemma":0.002518223,"domain_scores_codex":[0.99949,0.00006538663,0.00003231675,0.0001812526,0.0001663111,0.00006464032],"domain_scores_gemma":[0.9995185,0.0002055319,0.0000917542,0.00008886814,0.00004408906,0.00005123115],"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":[0.00009684849,0.00001756847,0.00104611,0.00007507783,0.00003884411,0.0001007075,0.00001930502,0.0007016829,0.9925892,0.0004341129,0.0002557703,0.004624723],"study_design_scores_gemma":[0.00005120002,0.0002382686,0.0115018,0.00001736315,0.0001269374,0.0004738243,0.0000495793,0.0109878,0.9653962,0.001276835,0.009840045,0.0000400761],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7577336,0.002061548,0.2123774,0.0006559053,0.0002774101,0.0003209363,0.01527832,0.004222251,0.007072633],"genre_scores_gemma":[0.8854094,0.0009666727,0.09713136,0.0007554238,0.00005023052,0.0003771081,0.007234975,0.0006932542,0.007381415],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002533352,"threshold_uncertainty_score":0.008474886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01941145188984574,"score_gpt":0.2134167412073678,"score_spread":0.1940052893175221,"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."}}