| Experimental Factor Ontology (EFO) Information | |
| Identifier | EFO_0004309 |
| Description | The number of PLATELETS per unit volume in a sample of venous BLOOD. | Trait category |
Hematological measurement
|
| Synonym | blood platelet number |
| Mapped terms |
4 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) |
|---|---|---|---|---|---|---|
| PGS000109 (plt) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Platelet count | platelet count | 26,683 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000109/ScoringFiles/PGS000109.txt.gz | |
| PGS000186 (plt) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Platelet count | platelet count | 739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000186/ScoringFiles/PGS000186.txt.gz |
| PGS001238 (GBE_INI30080) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Platelet count | platelet count | 24,893 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001238/ScoringFiles/PGS001238.txt.gz |
| PGS001973 (portability-PLR_log_platelet) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Platelet count | platelet count | 60,665 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001973/ScoringFiles/PGS001973.txt.gz |
| PGS002191 (portability-ldpred2_log_platelet) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Platelet count | platelet count | 663,591 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002191/ScoringFiles/PGS002191.txt.gz |
| PGS002343 (blood_PLATELET_COUNT.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Platelet count | platelet count | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002343/ScoringFiles/PGS002343.txt.gz |
| PGS002373 (blood_PLATELET_COUNT.BOLT-LMM-BBJ) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Platelet count | platelet count | 920,923 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002373/ScoringFiles/PGS002373.txt.gz |
| PGS002415 (blood_PLATELET_COUNT.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Platelet count | platelet count | 27,345 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002415/ScoringFiles/PGS002415.txt.gz |
| PGS002464 (blood_PLATELET_COUNT.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Platelet count | platelet count | 54,318 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002464/ScoringFiles/PGS002464.txt.gz |
| PGS002513 (blood_PLATELET_COUNT.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Platelet count | platelet count | 170,052 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002513/ScoringFiles/PGS002513.txt.gz |
| PGS002562 (blood_PLATELET_COUNT.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Platelet count | platelet count | 12,742 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002562/ScoringFiles/PGS002562.txt.gz |
| PGS002611 (blood_PLATELET_COUNT.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Platelet count | platelet count | 9,050 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002611/ScoringFiles/PGS002611.txt.gz |
| PGS002660 (blood_PLATELET_COUNT.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Platelet count | platelet count | 396,074 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002660/ScoringFiles/PGS002660.txt.gz |
| PGS002709 (blood_PLATELET_COUNT.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Platelet count | platelet count | 981,460 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002709/ScoringFiles/PGS002709.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 |
|---|---|---|---|---|---|---|---|---|---|
| PPM000250 | PGS000109 (plt) |
PSS000174| European Ancestry| 78,246 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Platelet count | — | — | Pearson correlation coefficent (r): 0.52039 | 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) |
| PPM000251 | PGS000109 (plt) |
PSS000148| European Ancestry| 38,939 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Platelet count | — | — | Pearson correlation coefficent (r): 0.53746 | 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) | — |
| PPM001775 | PGS000186 (plt) |
PSS000911| Greater Middle Eastern Ancestry| 13,989 individuals |
PGP000147 | Thareja G et al. Nat Commun (2021) |Ext. |
Reported Trait: Platelet count | — | — | Pearson correlation coefficent (r): 0.35 | — | — |
| PPM000557 | PGS000186 (plt) |
PSS000290| European Ancestry| 2,314 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Platelet count | — | — | R²: 0.16049 | sex, age, 10 genetic PCs | — |
| PPM000540 | PGS000186 (plt) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Platelet count | — | — | R²: 0.19195 | sex, age, 10 genetic PCs | — |
| PPM008699 | PGS001238 (GBE_INI30080) |
PSS006946| African Ancestry| 6,139 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Platelet count | — | — | R²: 0.13129 [0.11599, 0.14659] Incremental R2 (full-covars): 0.04423 PGS R2 (no covariates): 0.04881 [0.03859, 0.05902] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008700 | PGS001238 (GBE_INI30080) |
PSS006947| East Asian Ancestry| 1,655 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Platelet count | — | — | R²: 0.14398 [0.1132, 0.17476] Incremental R2 (full-covars): 0.09414 PGS R2 (no covariates): 0.09846 [0.07165, 0.12527] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008701 | PGS001238 (GBE_INI30080) |
PSS006948| European Ancestry| 24,175 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Platelet count | — | — | R²: 0.26403 [0.25464, 0.27343] Incremental R2 (full-covars): 0.21574 PGS R2 (no covariates): 0.21973 [0.21064, 0.22881] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008702 | PGS001238 (GBE_INI30080) |
PSS006949| South Asian Ancestry| 7,520 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Platelet count | — | — | R²: 0.24088 [0.22438, 0.25738] Incremental R2 (full-covars): 0.15169 PGS R2 (no covariates): 0.153 [0.13833, 0.16767] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008703 | PGS001238 (GBE_INI30080) |
PSS006950| European Ancestry| 65,637 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Platelet count | — | — | R²: 0.26678 [0.26106, 0.2725] Incremental R2 (full-covars): 0.20845 PGS R2 (no covariates): 0.20987 [0.20441, 0.21533] |
age, sex, UKB array type, Genotype PCs | — |
| PPM010665 | PGS001973 (portability-PLR_log_platelet) |
PSS007903| African Ancestry| 2,343 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Platelet count | — | — | Partial Correlation (partial-r): 0.2414 [0.2028, 0.2794] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010659 | PGS001973 (portability-PLR_log_platelet) |
PSS009459| European Ancestry| 19,422 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Platelet count | — | — | Partial Correlation (partial-r): 0.4839 [0.473, 0.4946] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010660 | PGS001973 (portability-PLR_log_platelet) |
PSS009233| European Ancestry| 4,002 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Platelet count | — | — | Partial Correlation (partial-r): 0.4742 [0.4498, 0.498] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010661 | PGS001973 (portability-PLR_log_platelet) |
PSS008787| European Ancestry| 6,436 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Platelet count | — | — | Partial Correlation (partial-r): 0.4739 [0.4547, 0.4927] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010662 | PGS001973 (portability-PLR_log_platelet) |
PSS008561| Greater Middle Eastern Ancestry| 1,153 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Platelet count | — | — | Partial Correlation (partial-r): 0.4562 [0.4088, 0.5011] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010663 | PGS001973 (portability-PLR_log_platelet) |
PSS008339| South Asian Ancestry| 6,076 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Platelet count | — | — | Partial Correlation (partial-r): 0.4242 [0.4034, 0.4447] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010664 | PGS001973 (portability-PLR_log_platelet) |
PSS008116| East Asian Ancestry| 1,762 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Platelet count | — | — | Partial Correlation (partial-r): 0.3503 [0.3084, 0.3908] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM010666 | PGS001973 (portability-PLR_log_platelet) |
PSS009007| African Ancestry| 3,711 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Platelet count | — | — | Partial Correlation (partial-r): 0.2443 [0.2137, 0.2744] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012375 | PGS002191 (portability-ldpred2_log_platelet) |
PSS009459| European Ancestry| 19,422 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Platelet count | — | — | Partial Correlation (partial-r): 0.4757 [0.4648, 0.4866] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012376 | PGS002191 (portability-ldpred2_log_platelet) |
PSS009233| European Ancestry| 4,002 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Platelet count | — | — | Partial Correlation (partial-r): 0.469 [0.4444, 0.4929] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012377 | PGS002191 (portability-ldpred2_log_platelet) |
PSS008787| European Ancestry| 6,436 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Platelet count | — | — | Partial Correlation (partial-r): 0.468 [0.4487, 0.4869] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012378 | PGS002191 (portability-ldpred2_log_platelet) |
PSS008561| Greater Middle Eastern Ancestry| 1,153 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Platelet count | — | — | Partial Correlation (partial-r): 0.4476 [0.3998, 0.493] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012379 | PGS002191 (portability-ldpred2_log_platelet) |
PSS008339| South Asian Ancestry| 6,076 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Platelet count | — | — | Partial Correlation (partial-r): 0.4155 [0.3944, 0.4361] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012380 | PGS002191 (portability-ldpred2_log_platelet) |
PSS008116| East Asian Ancestry| 1,762 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Platelet count | — | — | Partial Correlation (partial-r): 0.3472 [0.3052, 0.3878] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012381 | PGS002191 (portability-ldpred2_log_platelet) |
PSS007903| African Ancestry| 2,343 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Platelet count | — | — | Partial Correlation (partial-r): 0.2554 [0.217, 0.293] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM012382 | PGS002191 (portability-ldpred2_log_platelet) |
PSS009007| African Ancestry| 3,711 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Platelet count | — | — | Partial Correlation (partial-r): 0.2355 [0.2048, 0.2658] | sex, age, birth date, deprivation index, 16 PCs | — |
| PPM013108 | PGS002343 (blood_PLATELET_COUNT.BOLT-LMM) |
PSS009815| African Ancestry| 6,143 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.0682 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013157 | PGS002343 (blood_PLATELET_COUNT.BOLT-LMM) |
PSS009816| East Asian Ancestry| 895 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.0998 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013206 | PGS002343 (blood_PLATELET_COUNT.BOLT-LMM) |
PSS009817| European Ancestry| 42,007 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.2489 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013255 | PGS002343 (blood_PLATELET_COUNT.BOLT-LMM) |
PSS009818| South Asian Ancestry| 7,730 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.1747 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013285 | PGS002373 (blood_PLATELET_COUNT.BOLT-LMM-BBJ) |
PSS009815| African Ancestry| 6,143 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.0054 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013308 | PGS002373 (blood_PLATELET_COUNT.BOLT-LMM-BBJ) |
PSS009816| East Asian Ancestry| 895 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.091 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013331 | PGS002373 (blood_PLATELET_COUNT.BOLT-LMM-BBJ) |
PSS009817| European Ancestry| 42,007 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.0111 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013354 | PGS002373 (blood_PLATELET_COUNT.BOLT-LMM-BBJ) |
PSS009818| South Asian Ancestry| 7,730 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.0186 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013396 | PGS002415 (blood_PLATELET_COUNT.P+T.0.0001) |
PSS009815| African Ancestry| 6,143 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.001 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013494 | PGS002415 (blood_PLATELET_COUNT.P+T.0.0001) |
PSS009817| European Ancestry| 42,007 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.1524 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013543 | PGS002415 (blood_PLATELET_COUNT.P+T.0.0001) |
PSS009818| South Asian Ancestry| 7,730 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.0979 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013445 | PGS002415 (blood_PLATELET_COUNT.P+T.0.0001) |
PSS009816| East Asian Ancestry| 895 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.0672 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013592 | PGS002464 (blood_PLATELET_COUNT.P+T.0.001) |
PSS009815| African Ancestry| 6,143 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.0009 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013641 | PGS002464 (blood_PLATELET_COUNT.P+T.0.001) |
PSS009816| East Asian Ancestry| 895 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.0596 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013690 | PGS002464 (blood_PLATELET_COUNT.P+T.0.001) |
PSS009817| European Ancestry| 42,007 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.1455 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013739 | PGS002464 (blood_PLATELET_COUNT.P+T.0.001) |
PSS009818| South Asian Ancestry| 7,730 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.0778 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013788 | PGS002513 (blood_PLATELET_COUNT.P+T.0.01) |
PSS009815| African Ancestry| 6,143 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.0006 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013886 | PGS002513 (blood_PLATELET_COUNT.P+T.0.01) |
PSS009817| European Ancestry| 42,007 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.1163 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013935 | PGS002513 (blood_PLATELET_COUNT.P+T.0.01) |
PSS009818| South Asian Ancestry| 7,730 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.0301 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013837 | PGS002513 (blood_PLATELET_COUNT.P+T.0.01) |
PSS009816| East Asian Ancestry| 895 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.0374 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM013984 | PGS002562 (blood_PLATELET_COUNT.P+T.1e-06) |
PSS009815| African Ancestry| 6,143 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.035 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014033 | PGS002562 (blood_PLATELET_COUNT.P+T.1e-06) |
PSS009816| East Asian Ancestry| 895 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.0664 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014131 | PGS002562 (blood_PLATELET_COUNT.P+T.1e-06) |
PSS009818| South Asian Ancestry| 7,730 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.1092 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014082 | PGS002562 (blood_PLATELET_COUNT.P+T.1e-06) |
PSS009817| European Ancestry| 42,007 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.1496 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014180 | PGS002611 (blood_PLATELET_COUNT.P+T.5e-08) |
PSS009815| African Ancestry| 6,143 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.0343 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014229 | PGS002611 (blood_PLATELET_COUNT.P+T.5e-08) |
PSS009816| East Asian Ancestry| 895 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.0598 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014278 | PGS002611 (blood_PLATELET_COUNT.P+T.5e-08) |
PSS009817| European Ancestry| 42,007 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.1408 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014327 | PGS002611 (blood_PLATELET_COUNT.P+T.5e-08) |
PSS009818| South Asian Ancestry| 7,730 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.1049 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014376 | PGS002660 (blood_PLATELET_COUNT.PolyFun-pred) |
PSS009815| African Ancestry| 6,143 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1041 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See blood_PLATELET_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014425 | PGS002660 (blood_PLATELET_COUNT.PolyFun-pred) |
PSS009816| East Asian Ancestry| 895 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1227 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See blood_PLATELET_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014474 | PGS002660 (blood_PLATELET_COUNT.PolyFun-pred) |
PSS009817| European Ancestry| 42,007 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.2716 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See blood_PLATELET_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014523 | PGS002660 (blood_PLATELET_COUNT.PolyFun-pred) |
PSS009818| South Asian Ancestry| 7,730 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.2014 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See blood_PLATELET_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
| PPM014572 | PGS002709 (blood_PLATELET_COUNT.SBayesR) |
PSS009815| African Ancestry| 6,143 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.0667 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014621 | PGS002709 (blood_PLATELET_COUNT.SBayesR) |
PSS009816| East Asian Ancestry| 895 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.0811 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014670 | PGS002709 (blood_PLATELET_COUNT.SBayesR) |
PSS009817| European Ancestry| 42,007 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.24 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
| PPM014719 | PGS002709 (blood_PLATELET_COUNT.SBayesR) |
PSS009818| South Asian Ancestry| 7,730 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: Platelet count | — | — | Incremental R2 (full model vs. covariates alone): 0.1748 | 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 |
|---|---|---|---|---|---|---|---|---|
| PSS008787 | — | — | 6,436 individuals | — | European | Italy (South Europe) | UKB | — |
| PSS007903 | — | — | 2,343 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
| PSS000290 | — | — | 2,314 individuals | — | European (French Canadian) |
— | CARTaGENE | — |
| PSS000291 | — | — | 39,260 individuals | — | European | — | INTERVAL | — |
| PSS008561 | — | — | 1,153 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
| PSS009459 | — | — | 19,422 individuals | — | European | UK (+ Ireland) | UKB | — |
| PSS000911 | — | — | 13,989 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) (Qatari) |
— | QBB | — |
| PSS009815 | — | — | 6,143 individuals | — | African unspecified | — | UKB | — |
| PSS009816 | — | — | 895 individuals | — | East Asian | — | UKB | — |
| PSS009233 | — | — | 4,002 individuals | — | European | Poland (NE Europe) | UKB | — |
| PSS009817 | — | — | 42,007 individuals | — | European | Non-British European | UKB | — |
| PSS008339 | — | — | 6,076 individuals | — | South Asian | India (South Asia) | UKB | — |
| PSS000148 | — | — | 38,939 individuals, 49.0 % Male samples |
Mean = 43.75 years Range = [18.0, 76.4] years |
European | — | INTERVAL | — |
| PSS009818 | — | — | 7,730 individuals | — | South Asian | — | UKB | — |
| PSS006946 | — | — | 6,139 individuals | — | African unspecified | — | UKB | — |
| PSS006947 | — | — | 1,655 individuals | — | East Asian | — | UKB | — |
| PSS006948 | — | — | 24,175 individuals | — | European | non-white British ancestry | UKB | — |
| PSS006949 | — | — | 7,520 individuals | — | South Asian | — | UKB | — |
| PSS000174 | — | — | 78,246 individuals, 46.0 % Male samples |
Mean = 57.23 years Range = [39.98, 70.43] years |
European | — | UKB | — |
| PSS006950 | — | — | 65,637 individuals | — | European | white British ancestry | UKB | Testing cohort (heldout set) |
| PSS009007 | — | — | 3,711 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
| PSS008116 | — | — | 1,762 individuals | — | East Asian | China (East Asia) | UKB | — |