Experimental Factor Ontology (EFO) Information | |
Identifier | EFO_0004305 |
Description | The number of red blood cells per unit volume in a sample of venous blood. | Trait category |
Hematological measurement
|
Synonyms |
3 synonyms
|
Mapped terms |
3 mapped terms
|
Polygenic Score ID & Name | PGS Publication ID (PGP) | Reported Trait | Mapped Trait(s) (Ontology) | Number of Variants | Ancestry distribution | Scoring File (FTP Link) |
---|---|---|---|---|---|---|
PGS000110 (rbc) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Red blood cell count | erythrocyte count | 23,242 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000110/ScoringFiles/PGS000110.txt.gz | |
PGS000187 (rbc) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Red blood cell count | erythrocyte count | 678 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000187/ScoringFiles/PGS000187.txt.gz |
PGS001240 (GBE_INI30010) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Red blood cell count | erythrocyte count | 20,480 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001240/ScoringFiles/PGS001240.txt.gz |
PGS001909 (portability-PLR_erythrocyte) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Red blood cell (erythrocyte) count | erythrocyte count | 81,887 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001909/ScoringFiles/PGS001909.txt.gz |
PGS002123 (portability-ldpred2_erythrocyte) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Red blood cell (erythrocyte) count | erythrocyte count | 788,123 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002123/ScoringFiles/PGS002123.txt.gz |
PGS002345 (blood_RED_COUNT.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Count | erythrocyte count | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002345/ScoringFiles/PGS002345.txt.gz |
PGS002374 (blood_RED_COUNT.BOLT-LMM-BBJ) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Count | erythrocyte count | 920,935 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002374/ScoringFiles/PGS002374.txt.gz |
PGS002417 (blood_RED_COUNT.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Count | erythrocyte count | 18,514 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002417/ScoringFiles/PGS002417.txt.gz |
PGS002466 (blood_RED_COUNT.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Count | erythrocyte count | 41,471 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002466/ScoringFiles/PGS002466.txt.gz |
PGS002515 (blood_RED_COUNT.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Count | erythrocyte count | 150,047 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002515/ScoringFiles/PGS002515.txt.gz |
PGS002564 (blood_RED_COUNT.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Count | erythrocyte count | 7,590 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002564/ScoringFiles/PGS002564.txt.gz |
PGS002613 (blood_RED_COUNT.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Count | erythrocyte count | 5,156 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002613/ScoringFiles/PGS002613.txt.gz |
PGS002662 (blood_RED_COUNT.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Count | erythrocyte count | 473,515 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002662/ScoringFiles/PGS002662.txt.gz |
PGS002711 (blood_RED_COUNT.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Count | erythrocyte count | 982,902 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002711/ScoringFiles/PGS002711.txt.gz |
PGS Performance Metric ID (PPM) |
Evaluated Score |
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 |
---|---|---|---|---|---|---|---|---|---|
PPM000252 | PGS000110 (rbc) |
PSS000175| European Ancestry| 81,614 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Red blood cell count | — | — | Pearson correlation coefficent (r): 0.45067 | age, sex, 10 PCs of ancestry, lifestyle factors (diet, smoking, alcohol consumption), technical covariates (the time between venepuncture and full blood cell analysis, seasonal effects, centre of sample collection, time dependent drift of equipment, systematic differences in equipment) | UKB Testing Set - these samples were held out from Score Development (regression training) but overlap with the samples used for variant selection (GWAS) |
PPM000253 | PGS000110 (rbc) |
PSS000149| European Ancestry| 40,262 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Red blood cell count | — | — | Pearson correlation coefficent (r): 0.42574 | age, sex, 10 PCs of ancestry, lifestyle factors (diet, smoking, alcohol consumption), technical covariates (the time between venepuncture and full blood cell analysis, seasonal effects, centre of sample collection, time dependent drift of equipment, systematic differences in equipment) | — |
PPM000558 | PGS000187 (rbc) |
PSS000290| European Ancestry| 2,314 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Red blood cell count | — | — | R²: 0.06798 | sex, age, 10 genetic PCs | — |
PPM000541 | PGS000187 (rbc) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Red blood cell count | — | — | R²: 0.11765 | sex, age, 10 genetic PCs | — |
PPM001771 | PGS000187 (rbc) |
PSS000911| Greater Middle Eastern Ancestry| 13,989 individuals |
PGP000147 | Thareja G et al. Nat Commun (2021) |Ext. |
Reported Trait: Red blood cell count | — | — | Pearson correlation coefficent (r): 0.22 | — | — |
PPM008709 | PGS001240 (GBE_INI30010) |
PSS006896| African Ancestry| 6,139 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell count | — | — | R²: 0.26906 [0.25063, 0.28749] Incremental R2 (full-covars): 0.01652 PGS R2 (no covariates): 0.01819 [0.01175, 0.02463] |
age, sex, UKB array type, Genotype PCs | — |
PPM008710 | PGS001240 (GBE_INI30010) |
PSS006897| East Asian Ancestry| 1,655 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell count | — | — | R²: 0.32546 [0.289, 0.36193] Incremental R2 (full-covars): 0.04519 PGS R2 (no covariates): 0.05665 [0.03538, 0.07793] |
age, sex, UKB array type, Genotype PCs | — |
PPM008711 | PGS001240 (GBE_INI30010) |
PSS006898| European Ancestry| 24,175 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell count | — | — | R²: 0.37954 [0.37005, 0.38904] Incremental R2 (full-covars): 0.10462 PGS R2 (no covariates): 0.11155 [0.10418, 0.11892] |
age, sex, UKB array type, Genotype PCs | — |
PPM008712 | PGS001240 (GBE_INI30010) |
PSS006899| South Asian Ancestry| 7,520 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell count | — | — | R²: 0.33598 [0.31894, 0.35302] Incremental R2 (full-covars): 0.05745 PGS R2 (no covariates): 0.05295 [0.0433, 0.0626] |
age, sex, UKB array type, Genotype PCs | — |
PPM008713 | PGS001240 (GBE_INI30010) |
PSS006900| European Ancestry| 65,638 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell count | — | — | R²: 0.37344 [0.36766, 0.37922] Incremental R2 (full-covars): 0.11681 PGS R2 (no covariates): 0.11784 [0.11327, 0.12241] |
age, sex, UKB array type, Genotype PCs | — |
PPM010155 | PGS001909 (portability-PLR_erythrocyte) |
PSS009399| European Ancestry| 19,422 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.3987 [0.3868, 0.4105] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010156 | PGS001909 (portability-PLR_erythrocyte) |
PSS009173| European Ancestry| 4,001 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.404 [0.3776, 0.4296] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010157 | PGS001909 (portability-PLR_erythrocyte) |
PSS008727| European Ancestry| 6,437 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.3387 [0.3169, 0.3602] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010158 | PGS001909 (portability-PLR_erythrocyte) |
PSS008501| Greater Middle Eastern Ancestry| 1,153 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.3306 [0.2777, 0.3815] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010159 | PGS001909 (portability-PLR_erythrocyte) |
PSS008279| South Asian Ancestry| 6,078 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.2916 [0.2684, 0.3145] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010160 | PGS001909 (portability-PLR_erythrocyte) |
PSS008056| East Asian Ancestry| 1,762 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.2689 [0.2247, 0.3119] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010161 | PGS001909 (portability-PLR_erythrocyte) |
PSS007843| African Ancestry| 2,342 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.1886 [0.149, 0.2275] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010162 | PGS001909 (portability-PLR_erythrocyte) |
PSS008947| African Ancestry| 3,711 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.1298 [0.098, 0.1614] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM011839 | PGS002123 (portability-ldpred2_erythrocyte) |
PSS009399| European Ancestry| 19,422 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.39 [0.3781, 0.4019] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM011840 | PGS002123 (portability-ldpred2_erythrocyte) |
PSS009173| European Ancestry| 4,001 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.398 [0.3716, 0.4239] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM011841 | PGS002123 (portability-ldpred2_erythrocyte) |
PSS008727| European Ancestry| 6,437 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.3326 [0.3107, 0.3542] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM011842 | PGS002123 (portability-ldpred2_erythrocyte) |
PSS008501| Greater Middle Eastern Ancestry| 1,153 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.3308 [0.2779, 0.3816] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM011843 | PGS002123 (portability-ldpred2_erythrocyte) |
PSS008279| South Asian Ancestry| 6,078 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.2888 [0.2656, 0.3117] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM011844 | PGS002123 (portability-ldpred2_erythrocyte) |
PSS008056| East Asian Ancestry| 1,762 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.271 [0.2269, 0.314] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM011845 | PGS002123 (portability-ldpred2_erythrocyte) |
PSS007843| African Ancestry| 2,342 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.1984 [0.159, 0.2371] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM011846 | PGS002123 (portability-ldpred2_erythrocyte) |
PSS008947| African Ancestry| 3,711 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Red blood cell (erythrocyte) count | — | — | Partial Correlation (partial-r): 0.1336 [0.1018, 0.1651] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM013208 | PGS002345 (blood_RED_COUNT.BOLT-LMM) |
PSS009825| European Ancestry| 42,065 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.1566 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013257 | PGS002345 (blood_RED_COUNT.BOLT-LMM) |
PSS009826| South Asian Ancestry| 7,707 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0917 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013110 | PGS002345 (blood_RED_COUNT.BOLT-LMM) |
PSS009823| African Ancestry| 6,120 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0248 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013159 | PGS002345 (blood_RED_COUNT.BOLT-LMM) |
PSS009824| East Asian Ancestry| 885 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0807 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013286 | PGS002374 (blood_RED_COUNT.BOLT-LMM-BBJ) |
PSS009823| African Ancestry| 6,120 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0026 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013309 | PGS002374 (blood_RED_COUNT.BOLT-LMM-BBJ) |
PSS009824| East Asian Ancestry| 885 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0611 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013332 | PGS002374 (blood_RED_COUNT.BOLT-LMM-BBJ) |
PSS009825| European Ancestry| 42,065 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0146 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013355 | PGS002374 (blood_RED_COUNT.BOLT-LMM-BBJ) |
PSS009826| South Asian Ancestry| 7,707 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0119 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013398 | PGS002417 (blood_RED_COUNT.P+T.0.0001) |
PSS009823| African Ancestry| 6,120 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0031 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013447 | PGS002417 (blood_RED_COUNT.P+T.0.0001) |
PSS009824| East Asian Ancestry| 885 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0331 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013545 | PGS002417 (blood_RED_COUNT.P+T.0.0001) |
PSS009826| South Asian Ancestry| 7,707 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.037 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013496 | PGS002417 (blood_RED_COUNT.P+T.0.0001) |
PSS009825| European Ancestry| 42,065 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0916 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013594 | PGS002466 (blood_RED_COUNT.P+T.0.001) |
PSS009823| African Ancestry| 6,120 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0006 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013643 | PGS002466 (blood_RED_COUNT.P+T.0.001) |
PSS009824| East Asian Ancestry| 885 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0089 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013741 | PGS002466 (blood_RED_COUNT.P+T.0.001) |
PSS009826| South Asian Ancestry| 7,707 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.027 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013692 | PGS002466 (blood_RED_COUNT.P+T.0.001) |
PSS009825| European Ancestry| 42,065 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0939 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013790 | PGS002515 (blood_RED_COUNT.P+T.0.01) |
PSS009823| African Ancestry| 6,120 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013839 | PGS002515 (blood_RED_COUNT.P+T.0.01) |
PSS009824| East Asian Ancestry| 885 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0033 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013937 | PGS002515 (blood_RED_COUNT.P+T.0.01) |
PSS009826| South Asian Ancestry| 7,707 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.018 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013888 | PGS002515 (blood_RED_COUNT.P+T.0.01) |
PSS009825| European Ancestry| 42,065 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0705 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM014035 | PGS002564 (blood_RED_COUNT.P+T.1e-06) |
PSS009824| East Asian Ancestry| 885 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0602 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM014084 | PGS002564 (blood_RED_COUNT.P+T.1e-06) |
PSS009825| European Ancestry| 42,065 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0762 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013986 | PGS002564 (blood_RED_COUNT.P+T.1e-06) |
PSS009823| African Ancestry| 6,120 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0079 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM014133 | PGS002564 (blood_RED_COUNT.P+T.1e-06) |
PSS009826| South Asian Ancestry| 7,707 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0496 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM014182 | PGS002613 (blood_RED_COUNT.P+T.5e-08) |
PSS009823| African Ancestry| 6,120 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0114 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM014231 | PGS002613 (blood_RED_COUNT.P+T.5e-08) |
PSS009824| East Asian Ancestry| 885 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0594 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM014280 | PGS002613 (blood_RED_COUNT.P+T.5e-08) |
PSS009825| European Ancestry| 42,065 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0684 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM014329 | PGS002613 (blood_RED_COUNT.P+T.5e-08) |
PSS009826| South Asian Ancestry| 7,707 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0445 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM014427 | PGS002662 (blood_RED_COUNT.PolyFun-pred) |
PSS009824| East Asian Ancestry| 885 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0976 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See blood_RED_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
PPM014476 | PGS002662 (blood_RED_COUNT.PolyFun-pred) |
PSS009825| European Ancestry| 42,065 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1679 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See blood_RED_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
PPM014525 | PGS002662 (blood_RED_COUNT.PolyFun-pred) |
PSS009826| South Asian Ancestry| 7,707 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1044 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See blood_RED_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
PPM014378 | PGS002662 (blood_RED_COUNT.PolyFun-pred) |
PSS009823| African Ancestry| 6,120 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0299 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See blood_RED_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
PPM014574 | PGS002711 (blood_RED_COUNT.SBayesR) |
PSS009823| African Ancestry| 6,120 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.027 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM014672 | PGS002711 (blood_RED_COUNT.SBayesR) |
PSS009825| European Ancestry| 42,065 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.1523 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM014623 | PGS002711 (blood_RED_COUNT.SBayesR) |
PSS009824| East Asian Ancestry| 885 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0804 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM014721 | PGS002711 (blood_RED_COUNT.SBayesR) |
PSS009826| South Asian Ancestry| 7,707 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Red Blood Cell Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0944 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
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 |
---|---|---|---|---|---|---|---|---|
PSS009173 | — | — | 4,001 individuals | — | European | Poland (NE Europe) | UKB | — |
PSS008279 | — | — | 6,078 individuals | — | South Asian | India (South Asia) | UKB | — |
PSS000290 | — | — | 2,314 individuals | — | European (French Canadian) |
— | CARTaGENE | — |
PSS000291 | — | — | 39,260 individuals | — | European | — | INTERVAL | — |
PSS008947 | — | — | 3,711 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
PSS000911 | — | — | 13,989 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) (Qatari) |
— | QBB | — |
PSS006896 | — | — | 6,139 individuals | — | African unspecified | — | UKB | — |
PSS006897 | — | — | 1,655 individuals | — | East Asian | — | UKB | — |
PSS006898 | — | — | 24,175 individuals | — | European | non-white British ancestry | UKB | — |
PSS006899 | — | — | 7,520 individuals | — | South Asian | — | UKB | — |
PSS006900 | — | — | 65,638 individuals | — | European | white British ancestry | UKB | Testing cohort (heldout set) |
PSS008056 | — | — | 1,762 individuals | — | East Asian | China (East Asia) | UKB | — |
PSS000149 | — | — | 40,262 individuals, 49.0 % Male samples |
Mean = 43.84 years Range = [18.0, 76.4] years |
European | — | INTERVAL | — |
PSS008727 | — | — | 6,437 individuals | — | European | Italy (South Europe) | UKB | — |
PSS009823 | — | — | 6,120 individuals | — | African unspecified | — | UKB | — |
PSS009825 | — | — | 42,065 individuals | — | European | Non-British European | UKB | — |
PSS009826 | — | — | 7,707 individuals | — | South Asian | — | UKB | — |
PSS009824 | — | — | 885 individuals | — | East Asian | — | UKB | — |
PSS007843 | — | — | 2,342 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
PSS000175 | — | — | 81,614 individuals, 45.0 % Male samples |
Mean = 57.26 years Range = [39.99, 70.99] years |
European | — | UKB | — |
PSS008501 | — | — | 1,153 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
PSS009399 | — | — | 19,422 individuals | — | European | UK (+ Ireland) | UKB | — |