{"id":"W4380077595","doi":"10.1038/s42003-023-04974-0","title":"Whole genome analysis for 163 gRNAs in Cas9-edited mice reveals minimal off-target activity","year":2023,"lang":"en","type":"article","venue":"Communications Biology","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Toronto Centre for Phenogenomics; Hospital for Sick Children","funders":"Common Fund; National Human Genome Research Institute; National Cancer Institute; U.S. Department of Health and Human Services; National Institutes of Health; Genome Canada; Ontario Genomics; NIH Office of the Director; University of California, Davis","keywords":"Cas9; CRISPR; Genome; Genome editing; Biology; Sanger sequencing; Genetics; Computational biology; Mutagenesis; Context (archaeology); Whole genome sequencing; DNA sequencing; Gene; Mutation","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":[0.0001647354,0.0002689837,0.0002594445,0.0004871436,0.0001569017,0.0002233544,0.0002239905,0.0004602864,0.001008237],"category_scores_gemma":[0.0002019422,0.0001445679,0.0003929354,0.0002421308,0.0002303261,0.0001060984,0.0001600359,0.0005623024,0.000254994],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001500829,"about_ca_system_score_gemma":0.0001325346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006022502,"about_ca_topic_score_gemma":0.001271187,"domain_scores_codex":[0.9997923,0.00001531556,0.00001608726,0.00007716024,0.00007366263,0.00002546681],"domain_scores_gemma":[0.999787,0.00004751699,0.00008624555,0.00002236642,0.00001481542,0.00004204243],"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":[0.00005047577,0.00001212995,0.0005974337,0.00001178141,0.000008570219,0.00005369255,0.00001325317,0.00009769234,0.9979994,0.00004244389,0.0000173104,0.001095817],"study_design_scores_gemma":[0.00001137307,0.0003698491,0.04831707,0.000009116635,0.00004235881,0.001074088,0.00003500063,0.00188762,0.9463962,0.0001330605,0.001709612,0.00001458622],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9890203,0.0002293905,0.008382369,0.00002823886,0.000007105267,0.0000159629,0.001449085,0.0002331582,0.0006344511],"genre_scores_gemma":[0.9816527,0.0002932761,0.01220329,0.00009539451,0.000002856449,0.00004461824,0.003314258,0.0002326189,0.002161046],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001008237,"threshold_uncertainty_score":0.003372908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03142881984335195,"score_gpt":0.3755027815989624,"score_spread":0.3440739617556105,"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."}}