Experimental Factor Ontology (EFO) Information | |
Identifier | EFO_0010700 |
Description | A quantification of some aspect of reticulocyte function, quantity, or composition. | Trait category |
Hematological measurement
|
Child trait(s) | 2 child traits |
Polygenic Score ID & Name | PGS Publication ID (PGP) | Reported Trait | Mapped Trait(s) (Ontology) | Number of Variants |
Ancestry distribution GWAS Dev Eval |
Scoring File (FTP Link) |
---|---|---|---|---|---|---|
PGS000094 (hlr) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
High light scatter reticulocyte count | reticulocyte count | 25,493 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000094/ScoringFiles/PGS000094.txt.gz | |
PGS000095 (hlr_p) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
High light scatter reticulocyte percentage of red cells | reticulocyte count | 21,957 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000095/ScoringFiles/PGS000095.txt.gz | |
PGS000096 (irf) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Immature fraction of reticulocytes | reticulocyte count | 17,850 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000096/ScoringFiles/PGS000096.txt.gz | |
PGS000111 (ret) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reticulocyte count | reticulocyte count | 26,077 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000111/ScoringFiles/PGS000111.txt.gz | |
PGS000112 (ret_p) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reticulocyte fraction of red cells | reticulocyte count | 25,939 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000112/ScoringFiles/PGS000112.txt.gz | |
PGS000169 (hlr) |
PGP000078 | Vuckovic D et al. Cell (2020) |
High light scatter reticulocyte count | reticulocyte count | 570 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000169/ScoringFiles/PGS000169.txt.gz |
PGS000170 (hlr_p) |
PGP000078 | Vuckovic D et al. Cell (2020) |
High light scatter reticulocyte percentage of red cells | reticulocyte count | 566 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000170/ScoringFiles/PGS000170.txt.gz |
PGS000171 (irf) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Immature fraction of reticulocytes | reticulocyte count | 372 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000171/ScoringFiles/PGS000171.txt.gz |
PGS000180 (mrv) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Mean reticulocyte volume | mean reticulocyte volume | 629 | - - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000180/ScoringFiles/PGS000180.txt.gz |
PGS000189 (ret) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reticulocyte count | reticulocyte count | 555 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000189/ScoringFiles/PGS000189.txt.gz |
PGS000190 (ret_p) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reticulocyte fraction of red cells | reticulocyte count | 537 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000190/ScoringFiles/PGS000190.txt.gz |
PGS000987 (GBE_INI30260) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Mean reticulocyte volume | mean reticulocyte volume | 13,277 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000987/ScoringFiles/PGS000987.txt.gz |
PGS000988 (GBE_INI30290) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
High light scatter reticulocyte percentage | reticulocyte measurement | 7,184 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000988/ScoringFiles/PGS000988.txt.gz |
PGS000989 (GBE_INI30240) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reticulocyte percentage | reticulocyte measurement | 6,251 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000989/ScoringFiles/PGS000989.txt.gz |
PGS001406 (GBE_INI30300) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
High light scatter reticulocyte count | reticulocyte measurement | 15,856 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001406/ScoringFiles/PGS001406.txt.gz |
PGS001528 (GBE_INI30250) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reticulocyte count | reticulocyte count | 6,262 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001528/ScoringFiles/PGS001528.txt.gz |
PGS001959 (portability-PLR_log_HLR_reticulocyte) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
High light scatter reticulocyte count | reticulocyte measurement | 78,803 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001959/ScoringFiles/PGS001959.txt.gz |
PGS001976 (portability-PLR_log_reticulocyte) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reticulocyte count | reticulocyte count | 75,033 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001976/ScoringFiles/PGS001976.txt.gz |
PGS002003 (portability-PLR_reticulocyte_volume) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Mean reticulocyte volume | mean reticulocyte volume | 24,536 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002003/ScoringFiles/PGS002003.txt.gz |
PGS002177 (portability-ldpred2_log_HLR_reticulocyte) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
High light scatter reticulocyte count | reticulocyte measurement | 780,048 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002177/ScoringFiles/PGS002177.txt.gz |
PGS002194 (portability-ldpred2_log_reticulocyte) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reticulocyte count | reticulocyte count | 773,305 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002194/ScoringFiles/PGS002194.txt.gz |
PGS002221 (portability-ldpred2_reticulocyte_volume) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Mean reticulocyte volume | mean reticulocyte volume | 523,074 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002221/ScoringFiles/PGS002221.txt.gz |
PGS002333 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
High light scatter reticulocyte count | reticulocyte count | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002333/ScoringFiles/PGS002333.txt.gz |
PGS002405 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
High light scatter reticulocyte count | reticulocyte count | 16,031 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002405/ScoringFiles/PGS002405.txt.gz |
PGS002454 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
High light scatter reticulocyte count | reticulocyte count | 37,335 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002454/ScoringFiles/PGS002454.txt.gz |
PGS002503 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
High light scatter reticulocyte count | reticulocyte count | 143,701 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002503/ScoringFiles/PGS002503.txt.gz |
PGS002552 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
High light scatter reticulocyte count | reticulocyte count | 6,655 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002552/ScoringFiles/PGS002552.txt.gz |
PGS002601 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
High light scatter reticulocyte count | reticulocyte count | 4,569 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002601/ScoringFiles/PGS002601.txt.gz |
PGS002650 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
High light scatter reticulocyte count | reticulocyte count | 406,785 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002650/ScoringFiles/PGS002650.txt.gz |
PGS002699 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
High light scatter reticulocyte count | reticulocyte count | 983,680 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002699/ScoringFiles/PGS002699.txt.gz |
PGS003515 (cont-decay-immature_reticulocyte_frac) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Immature reticulocyte fraction | reticulocyte measurement | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003515/ScoringFiles/PGS003515.txt.gz |
PGS003551 (cont-decay-log_reticulocyte) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reticulocyte count | reticulocyte count | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003551/ScoringFiles/PGS003551.txt.gz |
PGS003567 (cont-decay-reticulocyte_volume) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Mean reticulocyte volume | mean reticulocyte volume | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003567/ScoringFiles/PGS003567.txt.gz |
PGS003946 (INI30240) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reticulocyte percentage | reticulocyte measurement | 7,884 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003946/ScoringFiles/PGS003946.txt.gz |
PGS003947 (INI30250) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reticulocyte count | reticulocyte count | 9,558 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003947/ScoringFiles/PGS003947.txt.gz |
PGS003948 (INI30260) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Mean reticulocyte volume | mean reticulocyte volume | 18,832 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003948/ScoringFiles/PGS003948.txt.gz |
PGS003951 (INI30290) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
High light scatter reticulocyte percentage | reticulocyte measurement | 11,641 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003951/ScoringFiles/PGS003951.txt.gz |
PGS003952 (INI30300) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
High light scatter reticulocyte count | reticulocyte count | 19,565 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003952/ScoringFiles/PGS003952.txt.gz |
PGS004363 (X30240.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reticulocyte percentage | reticulocyte measurement | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004363/ScoringFiles/PGS004363.txt.gz |
PGS004364 (X30250.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reticulocyte count | reticulocyte count | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004364/ScoringFiles/PGS004364.txt.gz |
PGS004365 (X30260.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Mean reticulocyte volume | mean reticulocyte volume | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004365/ScoringFiles/PGS004365.txt.gz |
PGS004367 (X30280.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
Immature reticulocyte fraction | reticulocyte measurement | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004367/ScoringFiles/PGS004367.txt.gz |
PGS004368 (X30290.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
High light scatter reticulocyte percentage | reticulocyte measurement | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004368/ScoringFiles/PGS004368.txt.gz |
PGS004369 (X30300.score) |
PGP000561 | Jung H et al. Commun Biol (2024) |
High light scatter reticulocyte count | reticulocyte count | 1,059,939 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS004369/ScoringFiles/PGS004369.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 |
---|---|---|---|---|---|---|---|---|---|
PPM000220 | PGS000094 (hlr) |
PSS000159| European Ancestry| 80,067 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: High light scatter reticulocyte count | — | — | Pearson correlation coefficent (r): 0.4559 | 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) |
PPM000221 | PGS000094 (hlr) |
PSS000133| European Ancestry| 40,244 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: High light scatter reticulocyte count | — | — | Pearson correlation coefficent (r): 0.40097 | 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) | — |
PPM000222 | PGS000095 (hlr_p) |
PSS000160| European Ancestry| 80,088 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: High light scatter reticulocyte percentage of red cells | — | — | Pearson correlation coefficent (r): 0.46291 | 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) |
PPM000223 | PGS000095 (hlr_p) |
PSS000134| European Ancestry| 40,225 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: High light scatter reticulocyte percentage of red cells | — | — | Pearson correlation coefficent (r): 0.40544 | 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) | — |
PPM000224 | PGS000096 (irf) |
PSS000161| European Ancestry| 79,282 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Immature fraction of reticulocytes | — | — | Pearson correlation coefficent (r): 0.35972 | 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) |
PPM000225 | PGS000096 (irf) |
PSS000135| European Ancestry| 40,227 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Immature fraction of reticulocytes | — | — | Pearson correlation coefficent (r): 0.36441 | 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) | — |
PPM000254 | PGS000111 (ret) |
PSS000176| European Ancestry| 79,344 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Reticulocyte count | — | — | Pearson correlation coefficent (r): 0.45071 | 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) |
PPM000255 | PGS000111 (ret) |
PSS000150| European Ancestry| 40,253 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Reticulocyte count | — | — | Pearson correlation coefficent (r): 0.44742 | 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) | — |
PPM000256 | PGS000112 (ret_p) |
PSS000177| European Ancestry| 79,362 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Reticulocyte fraction of red cells | — | — | Pearson correlation coefficent (r): 0.45239 | 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) |
PPM000257 | PGS000112 (ret_p) |
PSS000151| European Ancestry| 40,286 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Reticulocyte fraction of red cells | — | — | Pearson correlation coefficent (r): 0.45318 | 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) | — |
PPM000525 | PGS000169 (hlr) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: High light scatter reticulocyte count | — | — | R²: 0.11896 | sex, age, 10 genetic PCs | — |
PPM000526 | PGS000170 (hlr_p) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: High light scatter reticulocyte percentage of red cells | — | — | R²: 0.12799 | sex, age, 10 genetic PCs | — |
PPM000527 | PGS000171 (irf) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Immature fraction of reticulocytes | — | — | R²: 0.09164 | sex, age, 10 genetic PCs | — |
PPM000543 | PGS000189 (ret) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Reticulocyte count | — | — | R²: 0.14142 | sex, age, 10 genetic PCs | — |
PPM000544 | PGS000190 (ret_p) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Reticulocyte fraction of red cells | — | — | R²: 0.15022 | sex, age, 10 genetic PCs | — |
PPM007703 | PGS000987 (GBE_INI30260) |
PSS007026| African Ancestry| 5,973 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean reticulocyte volume | — | — | R²: 0.03718 [0.02815, 0.0462] Incremental R2 (full-covars): 0.02777 PGS R2 (no covariates): 0.02867 [0.02068, 0.03667] |
age, sex, UKB array type, Genotype PCs | — |
PPM007704 | PGS000987 (GBE_INI30260) |
PSS007027| East Asian Ancestry| 1,623 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean reticulocyte volume | — | — | R²: 0.08812 [0.06247, 0.11377] Incremental R2 (full-covars): 0.07173 PGS R2 (no covariates): 0.07447 [0.05053, 0.0984] |
age, sex, UKB array type, Genotype PCs | — |
PPM007705 | PGS000987 (GBE_INI30260) |
PSS007028| European Ancestry| 23,687 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean reticulocyte volume | — | — | R²: 0.1616 [0.15323, 0.16997] Incremental R2 (full-covars): 0.14435 PGS R2 (no covariates): 0.1455 [0.1374, 0.15359] |
age, sex, UKB array type, Genotype PCs | — |
PPM007706 | PGS000987 (GBE_INI30260) |
PSS007029| South Asian Ancestry| 7,323 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean reticulocyte volume | — | — | R²: 0.13294 [0.11894, 0.14694] Incremental R2 (full-covars): 0.09343 PGS R2 (no covariates): 0.09786 [0.08537, 0.11036] |
age, sex, UKB array type, Genotype PCs | — |
PPM007707 | PGS000987 (GBE_INI30260) |
PSS007030| European Ancestry| 64,570 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean reticulocyte volume | — | — | R²: 0.15675 [0.15171, 0.16179] Incremental R2 (full-covars): 0.14554 PGS R2 (no covariates): 0.14631 [0.14138, 0.15124] |
age, sex, UKB array type, Genotype PCs | — |
PPM007708 | PGS000988 (GBE_INI30290) |
PSS007036| African Ancestry| 5,974 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: High light scatter reticulocyte % | — | — | R²: 0.02767 [0.0198, 0.03553] Incremental R2 (full-covars): 0.01965 PGS R2 (no covariates): 0.01997 [0.01324, 0.0267] |
age, sex, UKB array type, Genotype PCs | — |
PPM007709 | PGS000988 (GBE_INI30290) |
PSS007037| East Asian Ancestry| 1,623 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: High light scatter reticulocyte % | — | — | R²: 0.05671 [0.03542, 0.07799] Incremental R2 (full-covars): 0.04573 PGS R2 (no covariates): 0.04876 [0.02885, 0.06866] |
age, sex, UKB array type, Genotype PCs | — |
PPM007710 | PGS000988 (GBE_INI30290) |
PSS007038| European Ancestry| 23,681 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: High light scatter reticulocyte % | — | — | R²: 0.08594 [0.07929, 0.0926] Incremental R2 (full-covars): 0.07798 PGS R2 (no covariates): 0.07863 [0.07222, 0.08505] |
age, sex, UKB array type, Genotype PCs | — |
PPM007711 | PGS000988 (GBE_INI30290) |
PSS007039| South Asian Ancestry| 7,321 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: High light scatter reticulocyte % | — | — | R²: 0.07357 [0.06245, 0.0847] Incremental R2 (full-covars): 0.06049 PGS R2 (no covariates): 0.06609 [0.05546, 0.07672] |
age, sex, UKB array type, Genotype PCs | — |
PPM007712 | PGS000988 (GBE_INI30290) |
PSS007040| European Ancestry| 64,524 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: High light scatter reticulocyte % | — | — | R²: 0.01671 [0.0148, 0.01863] Incremental R2 (full-covars): 0.01605 PGS R2 (no covariates): 0.016 [0.01412, 0.01788] |
age, sex, UKB array type, Genotype PCs | — |
PPM007715 | PGS000989 (GBE_INI30240) |
PSS007018| European Ancestry| 23,688 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Reticulocyte % | — | — | R²: 0.0318 [0.02751, 0.03609] Incremental R2 (full-covars): 0.02883 PGS R2 (no covariates): 0.02905 [0.02494, 0.03316] |
age, sex, UKB array type, Genotype PCs | — |
PPM007713 | PGS000989 (GBE_INI30240) |
PSS007016| African Ancestry| 5,974 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Reticulocyte % | — | — | R²: 0.01993 [0.01321, 0.02666] Incremental R2 (full-covars): 0.01309 PGS R2 (no covariates): 0.01384 [0.0082, 0.01948] |
age, sex, UKB array type, Genotype PCs | — |
PPM007714 | PGS000989 (GBE_INI30240) |
PSS007017| East Asian Ancestry| 1,623 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Reticulocyte % | — | — | R²: 0.05032 [0.03013, 0.0705] Incremental R2 (full-covars): 0.03871 PGS R2 (no covariates): 0.03842 [0.02056, 0.05628] |
age, sex, UKB array type, Genotype PCs | — |
PPM007716 | PGS000989 (GBE_INI30240) |
PSS007019| South Asian Ancestry| 7,323 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Reticulocyte % | — | — | R²: 0.03312 [0.02533, 0.04091] Incremental R2 (full-covars): 0.02678 PGS R2 (no covariates): 0.02784 [0.02066, 0.03502] |
age, sex, UKB array type, Genotype PCs | — |
PPM007717 | PGS000989 (GBE_INI30240) |
PSS007020| European Ancestry| 64,569 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Reticulocyte % | — | — | R²: 0.02928 [0.02677, 0.03179] Incremental R2 (full-covars): 0.02823 PGS R2 (no covariates): 0.02826 [0.0258, 0.03073] |
age, sex, UKB array type, Genotype PCs | — |
PPM007070 | PGS001406 (GBE_INI30300) |
PSS007041| African Ancestry| 5,974 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: High light scatter reticulocyte count | — | — | R²: 0.03376 [0.02514, 0.04239] Incremental R2 (full-covars): 0.02097 PGS R2 (no covariates): 0.02166 [0.01466, 0.02866] |
age, sex, UKB array type, Genotype PCs | — |
PPM007071 | PGS001406 (GBE_INI30300) |
PSS007042| East Asian Ancestry| 1,623 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: High light scatter reticulocyte count | — | — | R²: 0.08784 [0.06222, 0.11346] Incremental R2 (full-covars): 0.06019 PGS R2 (no covariates): 0.06306 [0.04077, 0.08536] |
age, sex, UKB array type, Genotype PCs | — |
PPM007072 | PGS001406 (GBE_INI30300) |
PSS007043| European Ancestry| 23,681 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: High light scatter reticulocyte count | — | — | R²: 0.116 [0.10853, 0.12348] Incremental R2 (full-covars): 0.09413 PGS R2 (no covariates): 0.09553 [0.08859, 0.10247] |
age, sex, UKB array type, Genotype PCs | — |
PPM007073 | PGS001406 (GBE_INI30300) |
PSS007044| South Asian Ancestry| 7,321 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: High light scatter reticulocyte count | — | — | R²: 0.09799 [0.08549, 0.1105] Incremental R2 (full-covars): 0.07113 PGS R2 (no covariates): 0.07659 [0.06528, 0.08791] |
age, sex, UKB array type, Genotype PCs | — |
PPM007074 | PGS001406 (GBE_INI30300) |
PSS007045| European Ancestry| 64,524 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: High light scatter reticulocyte count | — | — | R²: 0.12733 [0.12263, 0.13203] Incremental R2 (full-covars): 0.11178 PGS R2 (no covariates): 0.1113 [0.10683, 0.11578] |
age, sex, UKB array type, Genotype PCs | — |
PPM007061 | PGS001528 (GBE_INI30250) |
PSS007022| East Asian Ancestry| 1,623 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Reticulocyte count | — | — | R²: 0.07592 [0.05179, 0.10005] Incremental R2 (full-covars): 0.04581 PGS R2 (no covariates): 0.04535 [0.02608, 0.06461] |
age, sex, UKB array type, Genotype PCs | — |
PPM007062 | PGS001528 (GBE_INI30250) |
PSS007023| European Ancestry| 23,688 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Reticulocyte count | — | — | R²: 0.04398 [0.039, 0.04896] Incremental R2 (full-covars): 0.0298 PGS R2 (no covariates): 0.03007 [0.02589, 0.03425] |
age, sex, UKB array type, Genotype PCs | — |
PPM007063 | PGS001528 (GBE_INI30250) |
PSS007024| South Asian Ancestry| 7,323 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Reticulocyte count | — | — | R²: 0.05148 [0.04195, 0.06101] Incremental R2 (full-covars): 0.03077 PGS R2 (no covariates): 0.03212 [0.02444, 0.0398] |
age, sex, UKB array type, Genotype PCs | — |
PPM007060 | PGS001528 (GBE_INI30250) |
PSS007021| African Ancestry| 5,974 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Reticulocyte count | — | — | R²: 0.03089 [0.02261, 0.03917] Incremental R2 (full-covars): 0.01205 PGS R2 (no covariates): 0.01388 [0.00823, 0.01953] |
age, sex, UKB array type, Genotype PCs | — |
PPM007064 | PGS001528 (GBE_INI30250) |
PSS007025| European Ancestry| 64,570 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Reticulocyte count | — | — | R²: 0.0518 [0.04854, 0.05506] Incremental R2 (full-covars): 0.03968 PGS R2 (no covariates): 0.03966 [0.03677, 0.04254] |
age, sex, UKB array type, Genotype PCs | — |
PPM010548 | PGS001959 (portability-PLR_log_HLR_reticulocyte) |
PSS009207| European Ancestry| 3,919 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: High light scatter reticulocyte count | — | — | Partial Correlation (partial-r): 0.4054 [0.3788, 0.4313] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010549 | PGS001959 (portability-PLR_log_HLR_reticulocyte) |
PSS008761| European Ancestry| 6,289 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: High light scatter reticulocyte count | — | — | Partial Correlation (partial-r): 0.3962 [0.3751, 0.4169] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010550 | PGS001959 (portability-PLR_log_HLR_reticulocyte) |
PSS008535| Greater Middle Eastern Ancestry| 1,124 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: High light scatter reticulocyte count | — | — | Partial Correlation (partial-r): 0.3255 [0.2717, 0.3772] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010551 | PGS001959 (portability-PLR_log_HLR_reticulocyte) |
PSS008313| South Asian Ancestry| 5,923 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: High light scatter reticulocyte count | — | — | Partial Correlation (partial-r): 0.3191 [0.296, 0.3418] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010552 | PGS001959 (portability-PLR_log_HLR_reticulocyte) |
PSS008090| East Asian Ancestry| 1,715 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: High light scatter reticulocyte count | — | — | Partial Correlation (partial-r): 0.2778 [0.2333, 0.3212] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010553 | PGS001959 (portability-PLR_log_HLR_reticulocyte) |
PSS007877| African Ancestry| 2,293 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: High light scatter reticulocyte count | — | — | Partial Correlation (partial-r): 0.2182 [0.1787, 0.257] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010554 | PGS001959 (portability-PLR_log_HLR_reticulocyte) |
PSS008981| African Ancestry| 3,600 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: High light scatter reticulocyte count | — | — | Partial Correlation (partial-r): 0.2136 [0.1822, 0.2447] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010547 | PGS001959 (portability-PLR_log_HLR_reticulocyte) |
PSS009433| European Ancestry| 19,088 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: High light scatter reticulocyte count | — | — | Partial Correlation (partial-r): 0.4069 [0.395, 0.4186] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010683 | PGS001976 (portability-PLR_log_reticulocyte) |
PSS009465| European Ancestry| 19,117 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Reticulocyte count | — | — | Partial Correlation (partial-r): 0.3967 [0.3847, 0.4086] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010684 | PGS001976 (portability-PLR_log_reticulocyte) |
PSS009239| European Ancestry| 3,923 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Reticulocyte count | — | — | Partial Correlation (partial-r): 0.3757 [0.3485, 0.4024] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010685 | PGS001976 (portability-PLR_log_reticulocyte) |
PSS008793| European Ancestry| 6,297 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Reticulocyte count | — | — | Partial Correlation (partial-r): 0.3753 [0.3538, 0.3963] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010686 | PGS001976 (portability-PLR_log_reticulocyte) |
PSS008567| Greater Middle Eastern Ancestry| 1,127 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Reticulocyte count | — | — | Partial Correlation (partial-r): 0.3116 [0.2574, 0.3638] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010688 | PGS001976 (portability-PLR_log_reticulocyte) |
PSS008122| East Asian Ancestry| 1,722 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Reticulocyte count | — | — | Partial Correlation (partial-r): 0.2708 [0.2261, 0.3142] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010690 | PGS001976 (portability-PLR_log_reticulocyte) |
PSS009013| African Ancestry| 3,602 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Reticulocyte count | — | — | Partial Correlation (partial-r): 0.1736 [0.1416, 0.2052] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010687 | PGS001976 (portability-PLR_log_reticulocyte) |
PSS008345| South Asian Ancestry| 5,935 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Reticulocyte count | — | — | Partial Correlation (partial-r): 0.2981 [0.2747, 0.3211] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010689 | PGS001976 (portability-PLR_log_reticulocyte) |
PSS007909| African Ancestry| 2,294 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Reticulocyte count | — | — | Partial Correlation (partial-r): 0.1931 [0.1532, 0.2323] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010898 | PGS002003 (portability-PLR_reticulocyte_volume) |
PSS009487| European Ancestry| 19,120 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Mean reticulocyte volume | — | — | Partial Correlation (partial-r): 0.3934 [0.3814, 0.4054] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010899 | PGS002003 (portability-PLR_reticulocyte_volume) |
PSS009261| European Ancestry| 3,924 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Mean reticulocyte volume | — | — | Partial Correlation (partial-r): 0.3882 [0.3612, 0.4145] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010900 | PGS002003 (portability-PLR_reticulocyte_volume) |
PSS008815| European Ancestry| 6,298 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Mean reticulocyte volume | — | — | Partial Correlation (partial-r): 0.3774 [0.356, 0.3984] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010901 | PGS002003 (portability-PLR_reticulocyte_volume) |
PSS008589| Greater Middle Eastern Ancestry| 1,127 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Mean reticulocyte volume | — | — | Partial Correlation (partial-r): 0.3348 [0.2815, 0.3861] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010902 | PGS002003 (portability-PLR_reticulocyte_volume) |
PSS008367| South Asian Ancestry| 5,935 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Mean reticulocyte volume | — | — | Partial Correlation (partial-r): 0.3217 [0.2986, 0.3443] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010903 | PGS002003 (portability-PLR_reticulocyte_volume) |
PSS008143| East Asian Ancestry| 1,722 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Mean reticulocyte volume | — | — | Partial Correlation (partial-r): 0.2638 [0.219, 0.3074] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010904 | PGS002003 (portability-PLR_reticulocyte_volume) |
PSS007931| African Ancestry| 2,293 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Mean reticulocyte volume | — | — | Partial Correlation (partial-r): 0.2125 [0.1729, 0.2514] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM010905 | PGS002003 (portability-PLR_reticulocyte_volume) |
PSS009035| African Ancestry| 3,602 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Mean reticulocyte volume | — | — | Partial Correlation (partial-r): 0.1616 [0.1296, 0.1934] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012263 | PGS002177 (portability-ldpred2_log_HLR_reticulocyte) |
PSS009433| European Ancestry| 19,088 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: High light scatter reticulocyte count | — | — | Partial Correlation (partial-r): 0.3974 [0.3854, 0.4093] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012264 | PGS002177 (portability-ldpred2_log_HLR_reticulocyte) |
PSS009207| European Ancestry| 3,919 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: High light scatter reticulocyte count | — | — | Partial Correlation (partial-r): 0.3985 [0.3718, 0.4246] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012265 | PGS002177 (portability-ldpred2_log_HLR_reticulocyte) |
PSS008761| European Ancestry| 6,289 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: High light scatter reticulocyte count | — | — | Partial Correlation (partial-r): 0.3888 [0.3676, 0.4096] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012266 | PGS002177 (portability-ldpred2_log_HLR_reticulocyte) |
PSS008535| Greater Middle Eastern Ancestry| 1,124 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: High light scatter reticulocyte count | — | — | Partial Correlation (partial-r): 0.3261 [0.2723, 0.3778] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012267 | PGS002177 (portability-ldpred2_log_HLR_reticulocyte) |
PSS008313| South Asian Ancestry| 5,923 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: High light scatter reticulocyte count | — | — | Partial Correlation (partial-r): 0.3041 [0.2808, 0.3271] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012268 | PGS002177 (portability-ldpred2_log_HLR_reticulocyte) |
PSS008090| East Asian Ancestry| 1,715 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: High light scatter reticulocyte count | — | — | Partial Correlation (partial-r): 0.2632 [0.2183, 0.307] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012269 | PGS002177 (portability-ldpred2_log_HLR_reticulocyte) |
PSS007877| African Ancestry| 2,293 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: High light scatter reticulocyte count | — | — | Partial Correlation (partial-r): 0.2241 [0.1847, 0.2628] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012270 | PGS002177 (portability-ldpred2_log_HLR_reticulocyte) |
PSS008981| African Ancestry| 3,600 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: High light scatter reticulocyte count | — | — | Partial Correlation (partial-r): 0.1964 [0.1647, 0.2277] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012399 | PGS002194 (portability-ldpred2_log_reticulocyte) |
PSS009465| European Ancestry| 19,117 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Reticulocyte count | — | — | Partial Correlation (partial-r): 0.391 [0.3789, 0.403] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012400 | PGS002194 (portability-ldpred2_log_reticulocyte) |
PSS009239| European Ancestry| 3,923 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Reticulocyte count | — | — | Partial Correlation (partial-r): 0.3672 [0.3398, 0.3941] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012401 | PGS002194 (portability-ldpred2_log_reticulocyte) |
PSS008793| European Ancestry| 6,297 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Reticulocyte count | — | — | Partial Correlation (partial-r): 0.3718 [0.3503, 0.393] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012402 | PGS002194 (portability-ldpred2_log_reticulocyte) |
PSS008567| Greater Middle Eastern Ancestry| 1,127 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Reticulocyte count | — | — | Partial Correlation (partial-r): 0.3104 [0.2562, 0.3627] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012403 | PGS002194 (portability-ldpred2_log_reticulocyte) |
PSS008345| South Asian Ancestry| 5,935 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Reticulocyte count | — | — | Partial Correlation (partial-r): 0.2814 [0.2577, 0.3047] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012404 | PGS002194 (portability-ldpred2_log_reticulocyte) |
PSS008122| East Asian Ancestry| 1,722 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Reticulocyte count | — | — | Partial Correlation (partial-r): 0.2574 [0.2125, 0.3013] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012405 | PGS002194 (portability-ldpred2_log_reticulocyte) |
PSS007909| African Ancestry| 2,294 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Reticulocyte count | — | — | Partial Correlation (partial-r): 0.21 [0.1704, 0.249] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012406 | PGS002194 (portability-ldpred2_log_reticulocyte) |
PSS009013| African Ancestry| 3,602 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Reticulocyte count | — | — | Partial Correlation (partial-r): 0.1782 [0.1463, 0.2097] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012614 | PGS002221 (portability-ldpred2_reticulocyte_volume) |
PSS009487| European Ancestry| 19,120 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Mean reticulocyte volume | — | — | Partial Correlation (partial-r): 0.3894 [0.3773, 0.4014] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012615 | PGS002221 (portability-ldpred2_reticulocyte_volume) |
PSS009261| European Ancestry| 3,924 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Mean reticulocyte volume | — | — | Partial Correlation (partial-r): 0.3877 [0.3608, 0.4141] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012616 | PGS002221 (portability-ldpred2_reticulocyte_volume) |
PSS008815| European Ancestry| 6,298 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Mean reticulocyte volume | — | — | Partial Correlation (partial-r): 0.3736 [0.3521, 0.3947] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012617 | PGS002221 (portability-ldpred2_reticulocyte_volume) |
PSS008589| Greater Middle Eastern Ancestry| 1,127 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Mean reticulocyte volume | — | — | Partial Correlation (partial-r): 0.3308 [0.2773, 0.3823] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012618 | PGS002221 (portability-ldpred2_reticulocyte_volume) |
PSS008367| South Asian Ancestry| 5,935 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Mean reticulocyte volume | — | — | Partial Correlation (partial-r): 0.3152 [0.2921, 0.338] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012619 | PGS002221 (portability-ldpred2_reticulocyte_volume) |
PSS008143| East Asian Ancestry| 1,722 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Mean reticulocyte volume | — | — | Partial Correlation (partial-r): 0.2541 [0.2091, 0.298] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012620 | PGS002221 (portability-ldpred2_reticulocyte_volume) |
PSS007931| African Ancestry| 2,293 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Mean reticulocyte volume | — | — | Partial Correlation (partial-r): 0.2118 [0.1722, 0.2507] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM012621 | PGS002221 (portability-ldpred2_reticulocyte_volume) |
PSS009035| African Ancestry| 3,602 individuals |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Reported Trait: Mean reticulocyte volume | — | — | Partial Correlation (partial-r): 0.1834 [0.1516, 0.2149] | sex, age, birth date, deprivation index, 16 PCs | — |
PPM013147 | PGS002333 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.BOLT-LMM) |
PSS009776| East Asian Ancestry| 881 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0931 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013196 | PGS002333 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.BOLT-LMM) |
PSS009777| European Ancestry| 41,231 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.1501 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013098 | PGS002333 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.BOLT-LMM) |
PSS009775| African Ancestry| 5,976 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0378 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013245 | PGS002333 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.BOLT-LMM) |
PSS009778| South Asian Ancestry| 7,560 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0872 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013435 | PGS002405 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.0001) |
PSS009776| East Asian Ancestry| 881 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.055 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013484 | PGS002405 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.0001) |
PSS009777| European Ancestry| 41,231 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0785 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013533 | PGS002405 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.0001) |
PSS009778| South Asian Ancestry| 7,560 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.05 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013386 | PGS002405 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.0001) |
PSS009775| African Ancestry| 5,976 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0037 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013582 | PGS002454 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.001) |
PSS009775| African Ancestry| 5,976 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0011 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013631 | PGS002454 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.001) |
PSS009776| East Asian Ancestry| 881 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0141 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013680 | PGS002454 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.001) |
PSS009777| European Ancestry| 41,231 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0817 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013729 | PGS002454 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.001) |
PSS009778| South Asian Ancestry| 7,560 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0228 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013778 | PGS002503 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.01) |
PSS009775| African Ancestry| 5,976 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0055 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013876 | PGS002503 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.01) |
PSS009777| European Ancestry| 41,231 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0492 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013925 | PGS002503 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.01) |
PSS009778| South Asian Ancestry| 7,560 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0066 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013827 | PGS002503 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.0.01) |
PSS009776| East Asian Ancestry| 881 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0057 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM013974 | PGS002552 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.1e-06) |
PSS009775| African Ancestry| 5,976 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0149 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM014072 | PGS002552 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.1e-06) |
PSS009777| European Ancestry| 41,231 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0653 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM014121 | PGS002552 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.1e-06) |
PSS009778| South Asian Ancestry| 7,560 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0442 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM014023 | PGS002552 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.1e-06) |
PSS009776| East Asian Ancestry| 881 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0649 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM014219 | PGS002601 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.5e-08) |
PSS009776| East Asian Ancestry| 881 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0643 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM014268 | PGS002601 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.5e-08) |
PSS009777| European Ancestry| 41,231 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0598 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM014170 | PGS002601 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.5e-08) |
PSS009775| African Ancestry| 5,976 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0141 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM014317 | PGS002601 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.P+T.5e-08) |
PSS009778| South Asian Ancestry| 7,560 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0413 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM014513 | PGS002650 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.PolyFun-pred) |
PSS009778| South Asian Ancestry| 7,560 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1032 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
PPM014366 | PGS002650 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.PolyFun-pred) |
PSS009775| African Ancestry| 5,976 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.0563 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
PPM014415 | PGS002650 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.PolyFun-pred) |
PSS009776| East Asian Ancestry| 881 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1068 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
PPM014464 | PGS002650 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.PolyFun-pred) |
PSS009777| European Ancestry| 41,231 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model when combined with BOLT-LMM vs. covariates alone): 0.1606 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | See blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.mixweights file at http://data.broadinstitute.org/alkesgroup/polypred_results for combination weights |
PPM014562 | PGS002699 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.SBayesR) |
PSS009775| African Ancestry| 5,976 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0423 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM014611 | PGS002699 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.SBayesR) |
PSS009776| East Asian Ancestry| 881 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0835 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM014660 | PGS002699 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.SBayesR) |
PSS009777| European Ancestry| 41,231 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.1452 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM014709 | PGS002699 (blood_HIGH_LIGHT_SCATTER_RETICULOCYTE_COUNT.SBayesR) |
PSS009778| South Asian Ancestry| 7,560 individuals |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Reported Trait: High Light Scatter Reticulocyte Count | — | — | Incremental R2 (full model vs. covariates alone): 0.0888 | age, sex, age*sex, assessment center, genotyping array, 10 PCs | — |
PPM017443 | PGS003515 (cont-decay-immature_reticulocyte_frac) |
PSS010877| European Ancestry| 19,116 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Immature reticulocyte fraction | — | — | partial-R2: 0.1 | sex, age, deprivation index, PC1-16 | — |
PPM017527 | PGS003515 (cont-decay-immature_reticulocyte_frac) |
PSS010793| European Ancestry| 3,913 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Immature reticulocyte fraction | — | — | partial-R2: 0.1 | sex, age, deprivation index, PC1-16 | — |
PPM017611 | PGS003515 (cont-decay-immature_reticulocyte_frac) |
PSS010625| European Ancestry| 6,144 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Immature reticulocyte fraction | — | — | partial-R2: 0.1 | sex, age, deprivation index, PC1-16 | — |
PPM017695 | PGS003515 (cont-decay-immature_reticulocyte_frac) |
PSS010541| Greater Middle Eastern Ancestry| 1,097 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Immature reticulocyte fraction | — | — | partial-R2: 0.07 | sex, age, deprivation index, PC1-16 | — |
PPM017779 | PGS003515 (cont-decay-immature_reticulocyte_frac) |
PSS010205| European Ancestry| 2,221 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Immature reticulocyte fraction | — | — | partial-R2: 0.11 | sex, age, deprivation index, PC1-16 | — |
PPM017863 | PGS003515 (cont-decay-immature_reticulocyte_frac) |
PSS010457| South Asian Ancestry| 5,888 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Immature reticulocyte fraction | — | — | partial-R2: 0.07 | sex, age, deprivation index, PC1-16 | — |
PPM017947 | PGS003515 (cont-decay-immature_reticulocyte_frac) |
PSS010373| East Asian Ancestry| 1,711 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Immature reticulocyte fraction | — | — | partial-R2: 0.04 | sex, age, deprivation index, PC1-16 | — |
PPM018031 | PGS003515 (cont-decay-immature_reticulocyte_frac) |
PSS010289| African Ancestry| 2,282 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Immature reticulocyte fraction | — | — | partial-R2: 0.04 | sex, age, deprivation index, PC1-16 | — |
PPM018115 | PGS003515 (cont-decay-immature_reticulocyte_frac) |
PSS010709| African Ancestry| 3,574 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Immature reticulocyte fraction | — | — | partial-R2: 0.03 | sex, age, deprivation index, PC1-16 | — |
PPM017479 | PGS003551 (cont-decay-log_reticulocyte) |
PSS010917| European Ancestry| 19,111 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Reticulocyte count | — | — | partial-R2: 0.15 | sex, age, deprivation index, PC1-16 | — |
PPM017563 | PGS003551 (cont-decay-log_reticulocyte) |
PSS010833| European Ancestry| 3,912 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Reticulocyte count | — | — | partial-R2: 0.14 | sex, age, deprivation index, PC1-16 | — |
PPM017647 | PGS003551 (cont-decay-log_reticulocyte) |
PSS010665| European Ancestry| 6,143 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Reticulocyte count | — | — | partial-R2: 0.14 | sex, age, deprivation index, PC1-16 | — |
PPM017731 | PGS003551 (cont-decay-log_reticulocyte) |
PSS010581| Greater Middle Eastern Ancestry| 1,097 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Reticulocyte count | — | — | partial-R2: 0.09 | sex, age, deprivation index, PC1-16 | — |
PPM017815 | PGS003551 (cont-decay-log_reticulocyte) |
PSS010245| European Ancestry| 2,221 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Reticulocyte count | — | — | partial-R2: 0.13 | sex, age, deprivation index, PC1-16 | — |
PPM017899 | PGS003551 (cont-decay-log_reticulocyte) |
PSS010497| South Asian Ancestry| 5,886 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Reticulocyte count | — | — | partial-R2: 0.08 | sex, age, deprivation index, PC1-16 | — |
PPM017983 | PGS003551 (cont-decay-log_reticulocyte) |
PSS010413| East Asian Ancestry| 1,711 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Reticulocyte count | — | — | partial-R2: 0.07 | sex, age, deprivation index, PC1-16 | — |
PPM018067 | PGS003551 (cont-decay-log_reticulocyte) |
PSS010329| African Ancestry| 2,282 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Reticulocyte count | — | — | partial-R2: 0.04 | sex, age, deprivation index, PC1-16 | — |
PPM018151 | PGS003551 (cont-decay-log_reticulocyte) |
PSS010749| African Ancestry| 3,574 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Reticulocyte count | — | — | partial-R2: 0.03 | sex, age, deprivation index, PC1-16 | — |
PPM017495 | PGS003567 (cont-decay-reticulocyte_volume) |
PSS010934| European Ancestry| 19,112 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Mean reticulocyte volume | — | — | partial-R2: 0.15 | sex, age, deprivation index, PC1-16 | — |
PPM017579 | PGS003567 (cont-decay-reticulocyte_volume) |
PSS010850| European Ancestry| 3,913 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Mean reticulocyte volume | — | — | partial-R2: 0.15 | sex, age, deprivation index, PC1-16 | — |
PPM017663 | PGS003567 (cont-decay-reticulocyte_volume) |
PSS010682| European Ancestry| 6,144 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Mean reticulocyte volume | — | — | partial-R2: 0.13 | sex, age, deprivation index, PC1-16 | — |
PPM017747 | PGS003567 (cont-decay-reticulocyte_volume) |
PSS010598| Greater Middle Eastern Ancestry| 1,097 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Mean reticulocyte volume | — | — | partial-R2: 0.1 | sex, age, deprivation index, PC1-16 | — |
PPM017831 | PGS003567 (cont-decay-reticulocyte_volume) |
PSS010262| European Ancestry| 2,221 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Mean reticulocyte volume | — | — | partial-R2: 0.16 | sex, age, deprivation index, PC1-16 | — |
PPM017915 | PGS003567 (cont-decay-reticulocyte_volume) |
PSS010514| South Asian Ancestry| 5,886 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Mean reticulocyte volume | — | — | partial-R2: 0.1 | sex, age, deprivation index, PC1-16 | — |
PPM017999 | PGS003567 (cont-decay-reticulocyte_volume) |
PSS010430| East Asian Ancestry| 1,711 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Mean reticulocyte volume | — | — | partial-R2: 0.06 | sex, age, deprivation index, PC1-16 | — |
PPM018083 | PGS003567 (cont-decay-reticulocyte_volume) |
PSS010346| African Ancestry| 2,281 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Mean reticulocyte volume | — | — | partial-R2: 0.04 | sex, age, deprivation index, PC1-16 | — |
PPM018167 | PGS003567 (cont-decay-reticulocyte_volume) |
PSS010766| African Ancestry| 3,574 individuals |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Reported Trait: Mean reticulocyte volume | — | — | partial-R2: 0.03 | sex, age, deprivation index, PC1-16 | — |
PPM019049 | PGS003946 (INI30240) |
PSS011141| European Ancestry| 64,860 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Reticulocyte percentage | — | — | R²: 0.0298 [0.02728, 0.03233] PGS R2 (no covariates): 0.02838 [0.02592, 0.03085] Incremental R2 (full-covars): 0.02829 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019050 | PGS003946 (INI30240) |
PSS011099| European Ancestry| 2,770 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Reticulocyte percentage | — | — | R²: 0.07465 [0.05625, 0.09305] PGS R2 (no covariates): 0.06854 [0.05079, 0.08629] Incremental R2 (full-covars): 0.06923 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019051 | PGS003946 (INI30240) |
PSS011111| South Asian Ancestry| 1,393 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Reticulocyte percentage | — | — | R²: 0.08898 [0.06142, 0.11654] PGS R2 (no covariates): 0.08201 [0.05535, 0.10867] Incremental R2 (full-covars): 0.07867 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019052 | PGS003946 (INI30240) |
PSS011153| African Ancestry| 1,125 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Reticulocyte percentage | — | — | R²: 0.01247 [0.00009, 0.02484] PGS R2 (no covariates): 0.01579 [0.00191, 0.02967] Incremental R2 (full-covars): 0.012 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019053 | PGS003946 (INI30240) |
PSS011169| Multi-ancestry (excluding European)| 7,578 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Reticulocyte percentage | — | — | R²: 0.04153 [0.03298, 0.05009] PGS R2 (no covariates): 0.03618 [0.02815, 0.04421] Incremental R2 (full-covars): 0.03446 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019054 | PGS003947 (INI30250) |
PSS011140| European Ancestry| 64,861 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Reticulocyte count | — | — | R²: 0.0537 [0.0504, 0.057] PGS R2 (no covariates): 0.04073 [0.03782, 0.04365] Incremental R2 (full-covars): 0.04072 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019056 | PGS003947 (INI30250) |
PSS011111| South Asian Ancestry| 1,393 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Reticulocyte count | — | — | R²: 0.09735 [0.06879, 0.12592] PGS R2 (no covariates): 0.07127 [0.04612, 0.09641] Incremental R2 (full-covars): 0.06906 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019057 | PGS003947 (INI30250) |
PSS011153| African Ancestry| 1,125 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Reticulocyte count | — | — | R²: 0.02713 [0.00914, 0.04511] PGS R2 (no covariates): 0.01461 [0.00124, 0.02797] Incremental R2 (full-covars): 0.01527 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019058 | PGS003947 (INI30250) |
PSS011169| Multi-ancestry (excluding European)| 7,578 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Reticulocyte count | — | — | R²: 0.05468 [0.045, 0.06436] PGS R2 (no covariates): 0.03553 [0.02757, 0.04349] Incremental R2 (full-covars): 0.03303 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019055 | PGS003947 (INI30250) |
PSS011099| European Ancestry| 2,770 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Reticulocyte count | — | — | R²: 0.10144 [0.08061, 0.12226] PGS R2 (no covariates): 0.07084 [0.05284, 0.08884] Incremental R2 (full-covars): 0.07225 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019059 | PGS003948 (INI30260) |
PSS011140| European Ancestry| 64,861 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Mean reticulocyte volume | — | — | R²: 0.16087 [0.1558, 0.16594] PGS R2 (no covariates): 0.14603 [0.14111, 0.15095] Incremental R2 (full-covars): 0.14515 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019060 | PGS003948 (INI30260) |
PSS011099| European Ancestry| 2,770 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Mean reticulocyte volume | — | — | R²: 0.17217 [0.14717, 0.19717] PGS R2 (no covariates): 0.14414 [0.1205, 0.16779] Incremental R2 (full-covars): 0.14281 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019061 | PGS003948 (INI30260) |
PSS011111| South Asian Ancestry| 1,393 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Mean reticulocyte volume | — | — | R²: 0.13781 [0.10535, 0.17027] PGS R2 (no covariates): 0.11019 [0.08024, 0.14015] Incremental R2 (full-covars): 0.10391 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019062 | PGS003948 (INI30260) |
PSS011152| African Ancestry| 1,124 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Mean reticulocyte volume | — | — | R²: 0.03874 [0.01751, 0.05997] PGS R2 (no covariates): 0.03349 [0.01364, 0.05333] Incremental R2 (full-covars): 0.033 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019063 | PGS003948 (INI30260) |
PSS011169| Multi-ancestry (excluding European)| 7,578 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: Mean reticulocyte volume | — | — | R²: 0.15509 [0.14052, 0.16966] PGS R2 (no covariates): 0.13046 [0.11671, 0.14422] Incremental R2 (full-covars): 0.11887 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019075 | PGS003951 (INI30290) |
PSS011100| European Ancestry| 2,768 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: High light scatter reticulocyte percentage | — | — | R²: 0.10452 [0.08345, 0.12558] PGS R2 (no covariates): 0.09885 [0.07823, 0.11947] Incremental R2 (full-covars): 0.09847 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019076 | PGS003951 (INI30290) |
PSS011111| South Asian Ancestry| 1,393 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: High light scatter reticulocyte percentage | — | — | R²: 0.09744 [0.06887, 0.12601] PGS R2 (no covariates): 0.08757 [0.06019, 0.11496] Incremental R2 (full-covars): 0.08129 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019077 | PGS003951 (INI30290) |
PSS011153| African Ancestry| 1,125 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: High light scatter reticulocyte percentage | — | — | R²: 0.02997 [0.01112, 0.04881] PGS R2 (no covariates): 0.03101 [0.01186, 0.05016] Incremental R2 (full-covars): 0.0295 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019078 | PGS003951 (INI30290) |
PSS011170| Multi-ancestry (excluding European)| 7,574 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: High light scatter reticulocyte percentage | — | — | R²: 0.09491 [0.0827, 0.10712] PGS R2 (no covariates): 0.08288 [0.07132, 0.09444] Incremental R2 (full-covars): 0.07762 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019074 | PGS003951 (INI30290) |
PSS011143| European Ancestry| 64,816 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: High light scatter reticulocyte percentage | — | — | R²: 0.01834 [0.01634, 0.02034] PGS R2 (no covariates): 0.01717 [0.01523, 0.01911] Incremental R2 (full-covars): 0.01712 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019079 | PGS003952 (INI30300) |
PSS011143| European Ancestry| 64,816 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: High light scatter reticulocyte count | — | — | R²: 0.13075 [0.12601, 0.13548] PGS R2 (no covariates): 0.11335 [0.10885, 0.11784] Incremental R2 (full-covars): 0.11327 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019080 | PGS003952 (INI30300) |
PSS011100| European Ancestry| 2,768 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: High light scatter reticulocyte count | — | — | R²: 0.14122 [0.11773, 0.16471] PGS R2 (no covariates): 0.12176 [0.09946, 0.14407] Incremental R2 (full-covars): 0.12235 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019081 | PGS003952 (INI30300) |
PSS011111| South Asian Ancestry| 1,393 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: High light scatter reticulocyte count | — | — | R²: 0.11255 [0.08236, 0.14275] PGS R2 (no covariates): 0.0909 [0.0631, 0.1187] Incremental R2 (full-covars): 0.08654 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019082 | PGS003952 (INI30300) |
PSS011153| African Ancestry| 1,125 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: High light scatter reticulocyte count | — | — | R²: 0.04777 [0.02441, 0.07112] PGS R2 (no covariates): 0.04026 [0.01865, 0.06188] Incremental R2 (full-covars): 0.04027 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM019083 | PGS003952 (INI30300) |
PSS011170| Multi-ancestry (excluding European)| 7,574 individuals |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Reported Trait: High light scatter reticulocyte count | — | — | R²: 0.12479 [0.11125, 0.13833] PGS R2 (no covariates): 0.09343 [0.0813, 0.10557] Incremental R2 (full-covars): 0.08525 |
age, sex, age^2, age*sex, Townsend deprivation index, genotype PCs (PC1-PC18) | — |
PPM020478 | PGS004363 (X30240.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: Reticulocyte percentage | — | — | PGS R2 (no covariates): 0.26292 | — | — |
PPM020479 | PGS004364 (X30250.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: Reticulocyte count | — | — | PGS R2 (no covariates): 0.26266 | — | — |
PPM020480 | PGS004365 (X30260.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: Mean reticulocyte volume | — | — | PGS R2 (no covariates): 0.26343 | — | — |
PPM020482 | PGS004367 (X30280.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: Immature reticulocyte fraction | — | — | PGS R2 (no covariates): 0.20473 | — | — |
PPM020483 | PGS004368 (X30290.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: High light scatter reticulocyte percentage | — | — | PGS R2 (no covariates): 0.27287 | — | — |
PPM020484 | PGS004369 (X30300.score) |
PSS011364| European Ancestry| 56,192 individuals |
PGP000561 | Jung H et al. Commun Biol (2024) |
Reported Trait: High light scatter reticulocyte count | — | — | PGS R2 (no covariates): 0.27177 | — | — |
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 |
---|---|---|---|---|---|---|---|---|
PSS008143 | — | — | 1,722 individuals | — | East Asian | China (East Asia) | UKB | — |
PSS010665 | — | — | 6,143 individuals, 45.0 % Male samples |
Mean = 54.4 years Sd = 8.4 years |
European | Italian | UKB | — |
PSS010682 | — | — | 6,144 individuals, 45.0 % Male samples |
Mean = 54.4 years Sd = 8.4 years |
European | Italian | UKB | — |
PSS000291 | — | — | 39,260 individuals | — | European | — | INTERVAL | — |
PSS009207 | — | — | 3,919 individuals | — | European | Poland (NE Europe) | UKB | — |
PSS010709 | — | — | 3,574 individuals, 47.0 % Male samples |
Mean = 51.9 years Sd = 8.1 years |
African unspecified | Nigerian | UKB | — |
PSS010205 | — | — | 2,221 individuals, 45.0 % Male samples |
Mean = 58.0 years Sd = 7.1 years |
European | Ashkenazi | UKB | — |
PSS000133 | — | — | 40,244 individuals, 49.0 % Male samples |
Mean = 43.84 years Range = [18.0, 76.4] years |
European | — | INTERVAL | — |
PSS000134 | — | — | 40,225 individuals, 49.0 % Male samples |
Mean = 43.84 years Range = [18.0, 76.4] years |
European | — | INTERVAL | — |
PSS000135 | — | — | 40,227 individuals, 49.0 % Male samples |
Mean = 43.85 years Range = [18.0, 76.4] years |
European | — | INTERVAL | — |
PSS000150 | — | — | 40,253 individuals, 49.0 % Male samples |
Mean = 43.84 years Range = [18.0, 76.4] years |
European | — | INTERVAL | — |
PSS000151 | — | — | 40,286 individuals, 49.0 % Male samples |
Mean = 43.84 years Range = [18.0, 76.4] years |
European | — | INTERVAL | — |
PSS009239 | — | — | 3,923 individuals | — | European | Poland (NE Europe) | UKB | — |
PSS000159 | — | — | 80,067 individuals, 46.0 % Male samples |
Mean = 57.2 years Range = [39.91, 70.52] years |
European | — | UKB | — |
PSS000160 | — | — | 80,088 individuals, 46.0 % Male samples |
Mean = 57.19 years Range = [39.66, 72.91] years |
European | — | UKB | — |
PSS000161 | — | — | 79,282 individuals, 46.0 % Male samples |
Mean = 57.28 years Range = [39.91, 70.99] years |
European | — | UKB | — |
PSS010749 | — | — | 3,574 individuals, 47.0 % Male samples |
Mean = 51.9 years Sd = 8.1 years |
African unspecified | Nigerian | UKB | — |
PSS010245 | — | — | 2,221 individuals, 45.0 % Male samples |
Mean = 58.0 years Sd = 7.1 years |
European | Ashkenazi | UKB | — |
PSS009261 | — | — | 3,924 individuals | — | European | Poland (NE Europe) | UKB | — |
PSS000176 | — | — | 79,344 individuals, 46.0 % Male samples |
Mean = 57.29 years Range = [39.66, 72.91] years |
European | — | UKB | — |
PSS000177 | — | — | 79,362 individuals, 46.0 % Male samples |
Mean = 57.22 years Range = [39.66, 72.91] years |
European | — | UKB | — |
PSS010766 | — | — | 3,574 individuals, 47.0 % Male samples |
Mean = 51.9 years Sd = 8.1 years |
African unspecified | Nigerian | UKB | — |
PSS008761 | — | — | 6,289 individuals | — | European | Italy (South Europe) | UKB | — |
PSS010262 | — | — | 2,221 individuals, 45.0 % Male samples |
Mean = 58.0 years Sd = 7.1 years |
European | Ashkenazi | UKB | — |
PSS010793 | — | — | 3,913 individuals, 38.0 % Male samples |
Mean = 54.3 years Sd = 7.5 years |
European | Polish | UKB | — |
PSS010289 | — | — | 2,282 individuals, 37.0 % Male samples |
Mean = 52.4 years Sd = 8.0 years |
African American or Afro-Caribbean | Caribbean | UKB | — |
PSS008793 | — | — | 6,297 individuals | — | European | Italy (South Europe) | UKB | — |
PSS008815 | — | — | 6,298 individuals | — | European | Italy (South Europe) | UKB | — |
PSS010833 | — | — | 3,912 individuals, 38.0 % Male samples |
Mean = 54.3 years Sd = 7.5 years |
European | Polish | UKB | — |
PSS008313 | — | — | 5,923 individuals | — | South Asian | India (South Asia) | UKB | — |
PSS010329 | — | — | 2,282 individuals, 37.0 % Male samples |
Mean = 52.4 years Sd = 8.0 years |
African American or Afro-Caribbean | Caribbean | UKB | — |
PSS010850 | — | — | 3,913 individuals, 38.0 % Male samples |
Mean = 54.3 years Sd = 7.5 years |
European | Polish | UKB | — |
PSS010346 | — | — | 2,281 individuals, 37.0 % Male samples |
Mean = 52.4 years Sd = 8.0 years |
African American or Afro-Caribbean | Caribbean | UKB | — |
PSS008345 | — | — | 5,935 individuals | — | South Asian | India (South Asia) | UKB | — |
PSS011099 | — | — | 2,770 individuals | — | European (non-white British ancestry) |
— | UKB | — |
PSS011100 | — | — | 2,768 individuals | — | European (non-white British ancestry) |
— | UKB | — |
PSS010877 | — | — | 19,116 individuals, 46.0 % Male samples |
Mean = 56.9 years Sd = 7.9 years |
European | white British | UKB | — |
PSS011111 | — | — | 1,393 individuals | — | South Asian | — | UKB | — |
PSS010373 | — | — | 1,711 individuals, 33.0 % Male samples |
Mean = 52.4 years Sd = 7.8 years |
East Asian | Chinese | UKB | — |
PSS008367 | — | — | 5,935 individuals | — | South Asian | India (South Asia) | UKB | — |
PSS011140 | — | — | 64,861 individuals | — | European (white British ancestry) |
— | UKB | — |
PSS007877 | — | — | 2,293 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
PSS011141 | — | — | 64,860 individuals | — | European (white British ancestry) |
— | UKB | — |
PSS011143 | — | — | 64,816 individuals | — | European (white British ancestry) |
— | UKB | — |
PSS010917 | — | — | 19,111 individuals, 46.0 % Male samples |
Mean = 56.9 years Sd = 7.9 years |
European | white British | UKB | — |
PSS011152 | — | — | 1,124 individuals | — | African unspecified | — | UKB | — |
PSS011153 | — | — | 1,125 individuals | — | African unspecified | — | UKB | — |
PSS010413 | — | — | 1,711 individuals, 33.0 % Male samples |
Mean = 52.4 years Sd = 7.8 years |
East Asian | Chinese | UKB | — |
PSS009433 | — | — | 19,088 individuals | — | European | UK (+ Ireland) | UKB | — |
PSS010934 | — | — | 19,112 individuals, 46.0 % Male samples |
Mean = 56.9 years Sd = 7.9 years |
European | white British | UKB | — |
PSS011169 | — | — | 7,578 individuals | — | East Asian, Other admixed ancestry | East Asian, Other admixed ancestry | UKB | — |
PSS011170 | — | — | 7,574 individuals | — | East Asian, Other admixed ancestry | East Asian, Other admixed ancestry | UKB | — |
PSS010430 | — | — | 1,711 individuals, 33.0 % Male samples |
Mean = 52.4 years Sd = 7.8 years |
East Asian | Chinese | UKB | — |
PSS007909 | — | — | 2,294 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
PSS007016 | — | — | 5,974 individuals | — | African unspecified | — | UKB | — |
PSS007017 | — | — | 1,623 individuals | — | East Asian | — | UKB | — |
PSS007018 | — | — | 23,688 individuals | — | European | non-white British ancestry | UKB | — |
PSS007019 | — | — | 7,323 individuals | — | South Asian | — | UKB | — |
PSS007020 | — | — | 64,569 individuals | — | European | white British ancestry | UKB | Testing cohort (heldout set) |
PSS007021 | — | — | 5,974 individuals | — | African unspecified | — | UKB | — |
PSS007022 | — | — | 1,623 individuals | — | East Asian | — | UKB | — |
PSS007023 | — | — | 23,688 individuals | — | European | non-white British ancestry | UKB | — |
PSS007024 | — | — | 7,323 individuals | — | South Asian | — | UKB | — |
PSS007025 | — | — | 64,570 individuals | — | European | white British ancestry | UKB | Testing cohort (heldout set) |
PSS007026 | — | — | 5,973 individuals | — | African unspecified | — | UKB | — |
PSS007027 | — | — | 1,623 individuals | — | East Asian | — | UKB | — |
PSS007028 | — | — | 23,687 individuals | — | European | non-white British ancestry | UKB | — |
PSS007029 | — | — | 7,323 individuals | — | South Asian | — | UKB | — |
PSS007030 | — | — | 64,570 individuals | — | European | white British ancestry | UKB | Testing cohort (heldout set) |
PSS010457 | — | — | 5,888 individuals, 55.0 % Male samples |
Mean = 53.3 years Sd = 8.4 years |
South Asian | Indian | UKB | — |
PSS009465 | — | — | 19,117 individuals | — | European | UK (+ Ireland) | UKB | — |
PSS007931 | — | — | 2,293 individuals | — | African American or Afro-Caribbean | Carribean | UKB | — |
PSS007036 | — | — | 5,974 individuals | — | African unspecified | — | UKB | — |
PSS007037 | — | — | 1,623 individuals | — | East Asian | — | UKB | — |
PSS007038 | — | — | 23,681 individuals | — | European | non-white British ancestry | UKB | — |
PSS007039 | — | — | 7,321 individuals | — | South Asian | — | UKB | — |
PSS007040 | — | — | 64,524 individuals | — | European | white British ancestry | UKB | Testing cohort (heldout set) |
PSS007041 | — | — | 5,974 individuals | — | African unspecified | — | UKB | — |
PSS007042 | — | — | 1,623 individuals | — | East Asian | — | UKB | — |
PSS007043 | — | — | 23,681 individuals | — | European | non-white British ancestry | UKB | — |
PSS007044 | — | — | 7,321 individuals | — | South Asian | — | UKB | — |
PSS007045 | — | — | 64,524 individuals | — | European | white British ancestry | UKB | Testing cohort (heldout set) |
PSS009487 | — | — | 19,120 individuals | — | European | UK (+ Ireland) | UKB | — |
PSS008981 | — | — | 3,600 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
PSS011364 | — | — | 56,192 individuals | — | European | — | UKB | — |
PSS010497 | — | — | 5,886 individuals, 55.0 % Male samples |
Mean = 53.3 years Sd = 8.4 years |
South Asian | Indian | UKB | — |
PSS009013 | — | — | 3,602 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
PSS010514 | — | — | 5,886 individuals, 55.0 % Male samples |
Mean = 53.3 years Sd = 8.4 years |
South Asian | Indian | UKB | — |
PSS009035 | — | — | 3,602 individuals | — | African unspecified | Nigeria (West Africa) | UKB | — |
PSS010541 | — | — | 1,097 individuals, 59.0 % Male samples |
Mean = 52.0 years Sd = 8.0 years |
Greater Middle Eastern (Middle Eastern, North African or Persian) | Iranian | UKB | — |
PSS008535 | — | — | 1,124 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
PSS009775 | — | — | 5,976 individuals | — | African unspecified | — | UKB | — |
PSS009776 | — | — | 881 individuals | — | East Asian | — | UKB | — |
PSS009777 | — | — | 41,231 individuals | — | European | Non-British European | UKB | — |
PSS009778 | — | — | 7,560 individuals | — | South Asian | — | UKB | — |
PSS008567 | — | — | 1,127 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
PSS010581 | — | — | 1,097 individuals, 59.0 % Male samples |
Mean = 52.0 years Sd = 8.0 years |
Greater Middle Eastern (Middle Eastern, North African or Persian) | Iranian | UKB | — |
PSS010598 | — | — | 1,097 individuals, 59.0 % Male samples |
Mean = 52.0 years Sd = 8.0 years |
Greater Middle Eastern (Middle Eastern, North African or Persian) | Iranian | UKB | — |
PSS008589 | — | — | 1,127 individuals | — | Greater Middle Eastern (Middle Eastern, North African or Persian) | Iran (Middle East) | UKB | — |
PSS008090 | — | — | 1,715 individuals | — | East Asian | China (East Asia) | UKB | — |
PSS010625 | — | — | 6,144 individuals, 45.0 % Male samples |
Mean = 54.4 years Sd = 8.4 years |
European | Italian | UKB | — |
PSS008122 | — | — | 1,722 individuals | — | East Asian | China (East Asia) | UKB | — |