{"id":"W4415283170","doi":"10.1093/bioinformatics/btaf578","title":"Sparse polygenic risk score inference with the spike-and-slab LASSO","year":2025,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill Genome Centre; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Inference; Lasso (programming language); R package; Polygenic risk score; Covariate; Elastic net regularization; Software","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.003805407,0.001153857,0.001247914,0.0004050186,0.0005329243,0.0009128416,0.001699463,0.001135413,0.002624691],"category_scores_gemma":[0.01128637,0.0005233385,0.001043884,0.0006886133,0.001137407,0.001037614,0.001563313,0.003017253,0.0007297443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005945649,"about_ca_system_score_gemma":0.002084917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009301661,"about_ca_topic_score_gemma":0.009510175,"domain_scores_codex":[0.998289,0.0009730738,0.00006754786,0.0002520104,0.0003149794,0.0001032389],"domain_scores_gemma":[0.9954626,0.003159087,0.0003757338,0.0004526562,0.0003823315,0.0001676294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001613636,0.00007128096,0.002688732,0.00009129407,0.0001258457,0.0001134649,0.0000835961,0.9268791,0.001444008,0.0170754,0.005870317,0.04539564],"study_design_scores_gemma":[0.00001599497,0.000009916816,0.000122919,0.000004826884,0.000003633935,0.000009925191,0.000005069233,0.9944934,0.0002068981,0.00485397,0.0002689322,0.000004505239],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01310027,0.000162893,0.9839643,0.0005738476,0.00003618877,0.00004021348,0.0002441015,0.0008272943,0.001050855],"genre_scores_gemma":[0.4153681,0.0002708384,0.5780464,0.0007284463,0.0001808807,0.000301483,0.001727096,0.0004304812,0.002946194],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009301661,"threshold_uncertainty_score":0.02012521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01104433433225866,"score_gpt":0.2495141751595947,"score_spread":0.238469840827336,"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."}}