Polygenic Score (PGS) ID: PGS001448

Predicted Trait
Reported Trait Mean FA in tapetum on FA skeleton (R)
Mapped Trait(s)
Additional Trait Information https://biobankengine.stanford.edu/RIVAS_HG19/snpnet/INI25102
Released in PGS Catalog: Nov. 25, 2021
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Terms and Licenses
PGS obtained from the Catalog should be cited appropriately, and used in accordance with any licensing restrictions set by the authors. See EBI Terms of Use (https://www.ebi.ac.uk/about/terms-of-use/) for additional details.

Score Details

Score Construction
PGS Name GBE_INI25102
Development Method
Name snpnet
Parameters NR
Variants
Original Genome Build GRCh37
Number of Variants 1,948
Effect Weight Type NR
PGS Source
PGS Catalog Publication (PGP) ID PGP000244
Citation (link to publication) Tanigawa Y et al. PLoS Genet (2022)
Ancestry Distribution
Score Development/Training
European: 100%
21,081 individuals (100%)
PGS Evaluation
European: 40%
African: 20%
East Asian: 20%
South Asian: 20%
5 Sample Sets

Development Samples

Score Development/Training
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Study Identifiers
Sample Numbers
Sample Ancestry
Cohort(s)
Phenotype Definitions & Methods
Age of Study Participants
Participant Follow-up Time
Additional Ancestry Description
Additional Sample/Cohort Information
21,081 individualsEuropeanUKBwhite British ancestryTraining + validation cohort (train_val)
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Performance Metrics

Disclaimer: The performance metrics are displayed as reported by the source studies. It is important to note that metrics are not necessarily comparable with each other. For example, metrics depend on the sample characteristics (described by the PGS Catalog Sample Set [PSS] ID), phenotyping, and statistical modelling. Please refer to the source publication for additional guidance on performance.

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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
PPM005660PSS005496|
African Ancestry|
182 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Mean FA in tapetum on FA skeleton (R): 0.10141 [0.08751, 0.11532]
Incremental R2 (full-covars): -0.01563
PGS R2 (no covariates): 0.00142 [-0.00041, 0.00325]
age, sex, UKB array type, Genotype PCs
PPM005661PSS005497|
East Asian Ancestry|
106 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Mean FA in tapetum on FA skeleton (R): 0.15212 [0.12079, 0.18346]
Incremental R2 (full-covars): -0.0191
PGS R2 (no covariates): 0.0007 [-0.0018, 0.0032]
age, sex, UKB array type, Genotype PCs
PPM005662PSS005498|
European Ancestry|
1,651 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Mean FA in tapetum on FA skeleton (R): 0.11162 [0.10425, 0.11899]
Incremental R2 (full-covars): 0.01157
PGS R2 (no covariates): 0.01191 [0.00924, 0.01459]
age, sex, UKB array type, Genotype PCs
PPM005663PSS005499|
South Asian Ancestry|
299 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Mean FA in tapetum on FA skeleton (R): 0.11679 [0.10343, 0.13016]
Incremental R2 (full-covars): 0.01156
PGS R2 (no covariates): 0.02313 [0.01655, 0.02971]
age, sex, UKB array type, Genotype PCs
PPM005664PSS005500|
European Ancestry|
5,120 individuals
PGP000244 |
Tanigawa Y et al. PLoS Genet (2022)
Reported Trait: Mean FA in tapetum on FA skeleton (R): 0.10139 [0.09707, 0.10571]
Incremental R2 (full-covars): 0.02101
PGS R2 (no covariates): 0.02025 [0.01815, 0.02236]
age, sex, UKB array type, Genotype PCs
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Evaluated Samples

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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
PSS005496182 individualsAfrican unspecifiedUKB
PSS005497106 individualsEast AsianUKB
PSS0054981,651 individualsEuropeannon-white British ancestryUKB
PSS005499299 individualsSouth AsianUKB
PSS0055005,120 individualsEuropeanwhite British ancestryUKBTesting cohort (heldout set)
Showing 1 to 5 of 5 rows
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