Predicted Trait | |
Reported Trait | Prostate adenocarcinoma |
Mapped Trait(s) | prostate adenocarcinoma (EFO_0000673) |
Score Construction | |
PGS Name | best_PRAD |
Development Method | |
Name | lassosum |
Parameters | s = 0.5, lambda = 0.00545559 |
Variants | |
Original Genome Build | GRCh37 |
Number of Variants | 168,700 |
Effect Weight Type | beta |
PGS Source | |
PGS Catalog Publication (PGP) ID | PGP000413 |
Citation (link to publication) | Namba S et al. Cancer Res (2022) |
Ancestry Distribution | |
Source of Variant Associations (GWAS) | European: 100% 140,254 individuals (100%) |
PGS Evaluation | European: 100% 1 Sample Sets |
Study Identifiers | Sample Numbers | Sample Ancestry | Cohort(s) |
---|---|---|---|
GWAS Catalog: GCST006085 Europe PMC: 29892016 |
140,254 individuals | European | NR |
PGS Performance Metric ID (PPM) |
PGS Sample Set ID (PSS) |
Performance Source | Trait |
PGS Effect Sizes (per SD change) |
Classification Metrics | Other Metrics | Covariates Included in the Model |
PGS Performance: Other Relevant Information |
---|---|---|---|---|---|---|---|---|
PPM016258 | PSS010084| European Ancestry| 133,752 individuals |
PGP000413 | Namba S et al. Cancer Res (2022) |
Reported Trait: prostate adenocarcinoma | — | AUROC: 0.813 | R²: 0.0798 | age, top 20 genetic principal components | — |
PGS Sample Set ID (PSS) |
Phenotype Definitions and Methods | Participant Follow-up Time | Sample Numbers | Age of Study Participants | Sample Ancestry | Additional Ancestry Description | Cohort(s) | Additional Sample/Cohort Information |
---|---|---|---|---|---|---|---|---|
PSS010084 | C61 | — | [
|
— | European (British) |
— | UKB | Controls were samples without any cancer diagnosis or self-reported cancer |