| Experimental Factor Ontology (EFO) Information | |
| Identifier | EFO_0004503 |
| Description | A measurement quantifying some blood cell, or component. | Trait category |
Hematological measurement
|
| Child trait(s) |
29 child traits
|
| Polygenic Score ID & Name | PGS Publication ID (PGP) | Reported Trait | Mapped Trait(s) (Ontology) | Number of Variants | Ancestry distribution | Scoring File (FTP Link) |
|---|---|---|---|---|---|---|
| PGS000088 (baso) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Basophil count | basophil count | 9,121 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000088/ScoringFiles/PGS000088.txt.gz | |
| PGS000089 (baso_p) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Basophil percentage of white cells | basophil percentage of leukocytes | 5,248 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000089/ScoringFiles/PGS000089.txt.gz | |
| PGS000090 (eo) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Eosinophil count | eosinophil count | 22,949 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000090/ScoringFiles/PGS000090.txt.gz | |
| PGS000091 (eo_p) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Eosinophil percentage of white cells | eosinophil percentage of leukocytes | 24,406 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000091/ScoringFiles/PGS000091.txt.gz | |
| PGS000092 (hct) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Hematocrit | hematocrit | 28,214 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000092/ScoringFiles/PGS000092.txt.gz | |
| PGS000093 (hgb) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Hemoglobin concentration | hemoglobin measurement | 25,090 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000093/ScoringFiles/PGS000093.txt.gz | |
| 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 | |
| PGS000097 (lymph) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Lymphocyte count | lymphocyte count | 24,646 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000097/ScoringFiles/PGS000097.txt.gz | |
| PGS000098 (lymph_p) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Lymphocyte percentage of white cells | lymphocyte percentage of leukocytes | 22,363 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000098/ScoringFiles/PGS000098.txt.gz | |
| PGS000099 (mch) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Mean corpuscular hemoglobin | mean corpuscular hemoglobin | 27,081 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000099/ScoringFiles/PGS000099.txt.gz | |
| PGS000100 (mchc) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Mean corpuscular hemoglobin concentration | mean corpuscular hemoglobin concentration | 11,832 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000100/ScoringFiles/PGS000100.txt.gz | |
| PGS000101 (mcv) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Mean corpuscular volume | mean corpuscular volume | 25,001 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000101/ScoringFiles/PGS000101.txt.gz | |
| PGS000102 (mono) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Monocyte count | monocyte count | 28,162 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000102/ScoringFiles/PGS000102.txt.gz | |
| PGS000103 (mono_p) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Monocyte percentage of white cells | monocyte percentage of leukocytes | 22,843 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000103/ScoringFiles/PGS000103.txt.gz | |
| PGS000104 (mpv) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Mean platelet volume | mean platelet volume | 25,745 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000104/ScoringFiles/PGS000104.txt.gz | |
| PGS000105 (neut) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Neutrophil count | neutrophil count | 23,864 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000105/ScoringFiles/PGS000105.txt.gz | |
| PGS000106 (neut_p) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Neutrophil percentage of white cells | neutrophil percentage of leukocytes | 22,049 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000106/ScoringFiles/PGS000106.txt.gz | |
| PGS000107 (pct) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Plateletcrit | platelet crit | 30,459 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000107/ScoringFiles/PGS000107.txt.gz | |
| PGS000108 (pdw) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Platelet distribution width | platelet component distribution width | 25,995 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000108/ScoringFiles/PGS000108.txt.gz | |
| 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 | |
| PGS000110 (rbc) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Red blood cell count | erythrocyte count | 23,242 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000110/ScoringFiles/PGS000110.txt.gz | |
| 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 | |
| PGS000113 (wbc) |
PGP000051 | Xu Y et al. Cell Genom (2022) |
White blood cell count | leukocyte count | 28,383 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000113/ScoringFiles/PGS000113.txt.gz | |
| PGS000127 (GS-E-EUR) |
PGP000064 | Wheeler E et al. PLoS Med (2017) |
Hemoglobin A1c | HbA1c measurement | 21 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000127/ScoringFiles/PGS000127.txt.gz |
| PGS000128 (GS-E-AFR) |
PGP000064 | Wheeler E et al. PLoS Med (2017) |
Hemoglobin A1c | HbA1c measurement | 22 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000128/ScoringFiles/PGS000128.txt.gz |
| PGS000129 (GS-E-EAS) |
PGP000064 | Wheeler E et al. PLoS Med (2017) |
Hemoglobin A1c | HbA1c measurement | 17 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000129/ScoringFiles/PGS000129.txt.gz |
| PGS000130 (GS-G-EUR) |
PGP000064 | Wheeler E et al. PLoS Med (2017) |
Hemoglobin A1c | HbA1c measurement | 19 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000130/ScoringFiles/PGS000130.txt.gz |
| PGS000131 (GS-G-AFR) |
PGP000064 | Wheeler E et al. PLoS Med (2017) |
Hemoglobin A1c | HbA1c measurement | 19 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000131/ScoringFiles/PGS000131.txt.gz |
| PGS000132 (GS-G-EAS) |
PGP000064 | Wheeler E et al. PLoS Med (2017) |
Hemoglobin A1c | HbA1c measurement | 19 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000132/ScoringFiles/PGS000132.txt.gz |
| PGS000163 (baso) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Basophil count | basophil count | 185 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000163/ScoringFiles/PGS000163.txt.gz |
| PGS000164 (baso_p) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Basophil percentage of white cells | basophil percentage of leukocytes | 150 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000164/ScoringFiles/PGS000164.txt.gz |
| PGS000165 (eo) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Eosinophil count | eosinophil count | 607 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000165/ScoringFiles/PGS000165.txt.gz |
| PGS000166 (eo_p) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Eosinophil percentage of white cells | eosinophil percentage of leukocytes | 571 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000166/ScoringFiles/PGS000166.txt.gz |
| PGS000167 (hct) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Hematocrit | hematocrit | 502 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000167/ScoringFiles/PGS000167.txt.gz |
| PGS000168 (hgb) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Hemoglobin concentration | hemoglobin measurement | 515 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000168/ScoringFiles/PGS000168.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 |
| PGS000172 (lymph) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Lymphocyte count | lymphocyte count | 621 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000172/ScoringFiles/PGS000172.txt.gz |
| PGS000173 (lymph_p) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Lymphocyte percentage of white cells | lymphocyte percentage of leukocytes | 472 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000173/ScoringFiles/PGS000173.txt.gz |
| PGS000174 (mch) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Mean corpuscular hemoglobin | mean corpuscular hemoglobin | 628 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000174/ScoringFiles/PGS000174.txt.gz |
| PGS000175 (mchc) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Mean corpuscular hemoglobin concentration | mean corpuscular hemoglobin concentration | 224 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000175/ScoringFiles/PGS000175.txt.gz |
| PGS000176 (mcv) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Mean corpuscular volume | mean corpuscular volume | 685 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000176/ScoringFiles/PGS000176.txt.gz |
| PGS000177 (mono) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Monocyte count | monocyte count | 638 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000177/ScoringFiles/PGS000177.txt.gz |
| PGS000178 (mono_p) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Monocyte percentage of white cells | monocyte percentage of leukocytes | 549 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000178/ScoringFiles/PGS000178.txt.gz |
| PGS000179 (mpv) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Mean platelet volume | mean platelet volume | 654 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000179/ScoringFiles/PGS000179.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 |
| PGS000181 (mscv) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Mean sphered corpuscular volume | mean corpuscular volume | 761 | - - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000181/ScoringFiles/PGS000181.txt.gz |
| PGS000182 (neut) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Neutrophil count | neutrophil count | 492 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000182/ScoringFiles/PGS000182.txt.gz |
| PGS000183 (neut_p) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Neutrophil percentage of white cells | neutrophil percentage of leukocytes | 437 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000183/ScoringFiles/PGS000183.txt.gz |
| PGS000184 (pct) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Plateletcrit | platelet crit | 700 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000184/ScoringFiles/PGS000184.txt.gz |
| PGS000185 (pdw) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Platelet distribution width | platelet component distribution width | 555 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000185/ScoringFiles/PGS000185.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 |
| PGS000187 (rbc) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Red blood cell count | erythrocyte count | 678 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000187/ScoringFiles/PGS000187.txt.gz |
| PGS000188 (rdw) |
PGP000078 | Vuckovic D et al. Cell (2020) |
Red cell distribution width | Red cell distribution width | 546 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000188/ScoringFiles/PGS000188.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 |
| PGS000191 (wbc) |
PGP000078 | Vuckovic D et al. Cell (2020) |
White blood cell count | leukocyte count | 636 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000191/ScoringFiles/PGS000191.txt.gz |
| PGS000304 (GRS43_HbA1c) |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
HbA1c | HbA1c measurement | 43 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000304/ScoringFiles/PGS000304.txt.gz |
| PGS000685 (snpnet.Glycated_haemoglobin_HbA1c) |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
HbA1c [mmol/mol] | HbA1c measurement | 14,658 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000685/ScoringFiles/PGS000685.txt.gz |
| PGS000698 (snpnet.Total_protein) |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Total protein [g/L] | total blood protein measurement | 16,420 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000698/ScoringFiles/PGS000698.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 % | reticulocyte measurement | 6,251 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS000989/ScoringFiles/PGS000989.txt.gz |
| PGS001076 (GBE_INI30210) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Eosinophill % | eosinophil percentage of leukocytes | 12,563 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001076/ScoringFiles/PGS001076.txt.gz |
| PGS001077 (GBE_INI30200) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Neutrophill % | neutrophil percentage of leukocytes | 13,703 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001077/ScoringFiles/PGS001077.txt.gz |
| PGS001078 (GBE_INI30190) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Monocyte % | monocyte percentage of leukocytes | 8,762 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001078/ScoringFiles/PGS001078.txt.gz |
| PGS001079 (GBE_INI30110) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Platelet distribution width | platelet component distribution width | 18,814 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001079/ScoringFiles/PGS001079.txt.gz |
| PGS001152 (GBE_INI30070) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Red blood cell distribution width | Red cell distribution width | 10,179 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001152/ScoringFiles/PGS001152.txt.gz |
| PGS001163 (GBE_INI30130) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Monocyte count | monocyte count | 9,323 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001163/ScoringFiles/PGS001163.txt.gz |
| PGS001172 (GBE_INI30150) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Eosinophill count | eosinophil count | 12,579 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001172/ScoringFiles/PGS001172.txt.gz |
| PGS001173 (GBE_INI30140) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Neutrophill count | neutrophil count | 15,578 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001173/ScoringFiles/PGS001173.txt.gz |
| PGS001199 (GBE_INI30120) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Lymphocyte count | lymphocyte count | 4,212 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001199/ScoringFiles/PGS001199.txt.gz |
| PGS001200 (GBE_INI30100) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Mean platelet volume | mean platelet volume | 24,114 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001200/ScoringFiles/PGS001200.txt.gz |
| PGS001218 (GBE_INI30060) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Mean corpuscular haemoglobin concentration | mean corpuscular hemoglobin concentration | 2,359 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001218/ScoringFiles/PGS001218.txt.gz |
| PGS001219 (GBE_INI30050) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Mean corpuscular hemoglobin | mean corpuscular hemoglobin | 13,003 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001219/ScoringFiles/PGS001219.txt.gz |
| PGS001220 (GBE_INI30040) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Mean corpuscular volume | mean corpuscular volume | 17,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001220/ScoringFiles/PGS001220.txt.gz |
| PGS001225 (GBE_INI30030) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Percentage of hematocrit | hematocrit | 15,721 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001225/ScoringFiles/PGS001225.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 |
| PGS001239 (GBE_INI30000) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
White blood cell count | leukocyte count | 13,785 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001239/ScoringFiles/PGS001239.txt.gz |
| PGS001240 (GBE_INI30010) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Red blood cell count | erythrocyte count | 20,480 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001240/ScoringFiles/PGS001240.txt.gz |
| PGS001352 (MAGICTA_EUR_PGS_HbA1c) |
PGP000246 | Chen J et al. Nat Genet (2021) |
Glycated haemoglobin levels (HbA1c) | HbA1c measurement | 1,018,836 | https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001352/ScoringFiles/PGS001352.txt.gz | |
| PGS001377 (GBE_INI30220) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Basophill % | basophil percentage of leukocytes | 3,205 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001377/ScoringFiles/PGS001377.txt.gz |
| PGS001378 (GBE_INI30160) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Basophill count | basophil count | 3,050 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001378/ScoringFiles/PGS001378.txt.gz |
| PGS001400 (GBE_INI30020) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Haemoglobin concentration | hemoglobin measurement | 15,602 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001400/ScoringFiles/PGS001400.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 |
| PGS001408 (GBE_INI30280) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Immature reticulocyte fraction | Immature Reticulocyte Fraction Measurement | 10,871 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001408/ScoringFiles/PGS001408.txt.gz |
| PGS001414 (GBE_INI30180) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Lymphocyte % | lymphocyte percentage of leukocytes | 15,143 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001414/ScoringFiles/PGS001414.txt.gz |
| PGS001517 (GBE_INI30090) |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Platelet crit | platelet crit | 20,910 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001517/ScoringFiles/PGS001517.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 |
| PGS001908 (portability-PLR_erythrocyte_width) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Red blood cell (erythrocyte) distribution width | Red cell distribution width | 32,431 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001908/ScoringFiles/PGS001908.txt.gz |
| PGS001909 (portability-PLR_erythrocyte) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Red blood cell (erythrocyte) count | erythrocyte count | 81,887 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001909/ScoringFiles/PGS001909.txt.gz |
| PGS001925 (portability-PLR_haematocrit_perc) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Haematocrit percentage | hematocrit | 67,571 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001925/ScoringFiles/PGS001925.txt.gz |
| PGS001926 (portability-PLR_haemoglobin) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Haemoglobin concentration | hemoglobin measurement | 69,467 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001926/ScoringFiles/PGS001926.txt.gz |
| PGS001930 (portability-PLR_immature_reticulocyte_frac) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Immature reticulocyte fraction | Immature Reticulocyte Fraction Measurement | 39,162 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001930/ScoringFiles/PGS001930.txt.gz |
| PGS001949 (portability-PLR_log_eosinophil_perc) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Eosinophil percentage | eosinophil percentage of leukocytes | 9,236 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001949/ScoringFiles/PGS001949.txt.gz |
| PGS001953 (portability-PLR_log_HbA1c) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Glycated haemoglobin (HbA1c) | HbA1c measurement | 46,566 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001953/ScoringFiles/PGS001953.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 |
| PGS001962 (portability-PLR_log_leukocyte) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
White blood cell (leukocyte) count | leukocyte count | 80,228 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001962/ScoringFiles/PGS001962.txt.gz |
| PGS001965 (portability-PLR_log_lymphocyte) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Lymphocyte count | lymphocyte count | 76,535 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001965/ScoringFiles/PGS001965.txt.gz |
| PGS001968 (portability-PLR_log_monocyte) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Monocyte count | monocyte count | 46,673 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001968/ScoringFiles/PGS001968.txt.gz |
| PGS001969 (portability-PLR_log_neutrophil) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Neutrophil count | neutrophil count | 71,566 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001969/ScoringFiles/PGS001969.txt.gz |
| PGS001970 (portability-PLR_log_platelet_crit) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Platelet crit | platelet crit | 56,402 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001970/ScoringFiles/PGS001970.txt.gz |
| PGS001971 (portability-PLR_log_platelet_volume) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Mean platelet (thrombocyte) volume | mean platelet volume | 65,450 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001971/ScoringFiles/PGS001971.txt.gz |
| PGS001972 (portability-PLR_log_platelet_width) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Platelet distribution width | platelet component distribution width | 46,157 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001972/ScoringFiles/PGS001972.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 |
| 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 |
| PGS001986 (portability-PLR_lymphocyte_perc) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Lymphocyte percentage | lymphocyte percentage of leukocytes | 66,778 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001986/ScoringFiles/PGS001986.txt.gz |
| PGS001989 (portability-PLR_MCH) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Mean corpuscular haemoglobin | mean corpuscular hemoglobin | 44,174 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001989/ScoringFiles/PGS001989.txt.gz |
| PGS001990 (portability-PLR_MCV) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Mean corpuscular volume | mean corpuscular volume | 47,916 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001990/ScoringFiles/PGS001990.txt.gz |
| PGS001991 (portability-PLR_monocyte_perc) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Monocyte percentage | monocyte percentage of leukocytes | 41,887 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001991/ScoringFiles/PGS001991.txt.gz |
| PGS001997 (portability-PLR_neutrophil_perc) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Neutrophil percentage | neutrophil percentage of leukocytes | 65,022 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS001997/ScoringFiles/PGS001997.txt.gz |
| PGS002001 (portability-PLR_protein) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Total protein | total blood protein measurement | 69,557 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002001/ScoringFiles/PGS002001.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 |
| PGS002008 (portability-PLR_sphered_cell_volume) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Mean sphered cell volume | hematological measurement | 50,360 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002008/ScoringFiles/PGS002008.txt.gz |
| PGS002122 (portability-ldpred2_erythrocyte_width) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Red blood cell (erythrocyte) distribution width | Red cell distribution width | 543,714 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002122/ScoringFiles/PGS002122.txt.gz |
| PGS002123 (portability-ldpred2_erythrocyte) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Red blood cell (erythrocyte) count | erythrocyte count | 788,123 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002123/ScoringFiles/PGS002123.txt.gz |
| PGS002141 (portability-ldpred2_haematocrit_perc) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Haematocrit percentage | hematocrit | 797,804 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002141/ScoringFiles/PGS002141.txt.gz |
| PGS002142 (portability-ldpred2_haemoglobin) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Haemoglobin concentration | hemoglobin measurement | 786,386 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002142/ScoringFiles/PGS002142.txt.gz |
| PGS002147 (portability-ldpred2_immature_reticulocyte_frac) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Immature reticulocyte fraction | Immature Reticulocyte Fraction Measurement | 664,696 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002147/ScoringFiles/PGS002147.txt.gz |
| PGS002167 (portability-ldpred2_log_eosinophil_perc) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Eosinophil percentage | eosinophil percentage of leukocytes | 593,459 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002167/ScoringFiles/PGS002167.txt.gz |
| PGS002171 (portability-ldpred2_log_HbA1c) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Glycated haemoglobin (HbA1c) | HbA1c measurement | 736,730 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002171/ScoringFiles/PGS002171.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 |
| PGS002180 (portability-ldpred2_log_leukocyte) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
White blood cell (leukocyte) count | leukocyte count | 846,337 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002180/ScoringFiles/PGS002180.txt.gz |
| PGS002183 (portability-ldpred2_log_lymphocyte) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Lymphocyte count | lymphocyte count | 814,921 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002183/ScoringFiles/PGS002183.txt.gz |
| PGS002186 (portability-ldpred2_log_monocyte) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Monocyte count | monocyte count | 641,455 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002186/ScoringFiles/PGS002186.txt.gz |
| PGS002187 (portability-ldpred2_log_neutrophil) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Neutrophil count | neutrophil count | 803,767 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002187/ScoringFiles/PGS002187.txt.gz |
| PGS002188 (portability-ldpred2_log_platelet_crit) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Platelet crit | platelet crit | 703,576 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002188/ScoringFiles/PGS002188.txt.gz |
| PGS002189 (portability-ldpred2_log_platelet_volume) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Mean platelet (thrombocyte) volume | mean platelet volume | 462,934 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002189/ScoringFiles/PGS002189.txt.gz |
| PGS002190 (portability-ldpred2_log_platelet_width) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Platelet distribution width | platelet component distribution width | 482,649 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002190/ScoringFiles/PGS002190.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 |
| 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 |
| PGS002203 (portability-ldpred2_lymphocyte_perc) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Lymphocyte percentage | lymphocyte percentage of leukocytes | 775,312 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002203/ScoringFiles/PGS002203.txt.gz |
| PGS002206 (portability-ldpred2_MCH) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Mean corpuscular haemoglobin | mean corpuscular hemoglobin | 504,929 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002206/ScoringFiles/PGS002206.txt.gz |
| PGS002207 (portability-ldpred2_MCV) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Mean corpuscular volume | mean corpuscular volume | 564,228 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002207/ScoringFiles/PGS002207.txt.gz |
| PGS002208 (portability-ldpred2_monocyte_perc) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Monocyte percentage | monocyte percentage of leukocytes | 544,905 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002208/ScoringFiles/PGS002208.txt.gz |
| PGS002214 (portability-ldpred2_neutrophil_perc) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Neutrophil percentage | neutrophil percentage of leukocytes | 769,542 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002214/ScoringFiles/PGS002214.txt.gz |
| PGS002219 (portability-ldpred2_protein) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Total protein | total blood protein measurement | 819,013 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002219/ScoringFiles/PGS002219.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 |
| PGS002227 (portability-ldpred2_sphered_cell_volume) |
PGP000263 | Privé F et al. Am J Hum Genet (2022) |
Mean sphered cell volume | hematological measurement | 630,576 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002227/ScoringFiles/PGS002227.txt.gz |
| PGS002325 (blood_EOSINOPHIL_COUNT.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Eosinophil count | eosinophil count | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002325/ScoringFiles/PGS002325.txt.gz |
| PGS002331 (biochemistry_HbA1c.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
HbA1c | HbA1c measurement | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002331/ScoringFiles/PGS002331.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 |
| PGS002338 (blood_LYMPHOCYTE_COUNT.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Lymphocyte Count | lymphocyte count | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002338/ScoringFiles/PGS002338.txt.gz |
| PGS002339 (blood_MEAN_CORPUSCULAR_HEMOGLOBIN.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Mean Corpuscular Hemoglobin | mean corpuscular hemoglobin | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002339/ScoringFiles/PGS002339.txt.gz |
| PGS002340 (blood_MEAN_PLATELET_VOL.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Mean Platelet Volume | mean platelet volume | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002340/ScoringFiles/PGS002340.txt.gz |
| PGS002341 (blood_MONOCYTE_COUNT.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Monocyte Count | monocyte count | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002341/ScoringFiles/PGS002341.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 |
| PGS002345 (blood_RED_COUNT.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Count | erythrocyte count | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002345/ScoringFiles/PGS002345.txt.gz |
| PGS002346 (blood_RBC_DISTRIB_WIDTH.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Distribution Width | Red cell distribution width | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002346/ScoringFiles/PGS002346.txt.gz |
| PGS002357 (blood_WHITE_COUNT.BOLT-LMM) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
White Blood Count | leukocyte count | 1,109,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002357/ScoringFiles/PGS002357.txt.gz |
| PGS002364 (blood_EOSINOPHIL_COUNT.BOLT-LMM-BBJ) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Eosinophil count | eosinophil count | 920,929 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002364/ScoringFiles/PGS002364.txt.gz |
| PGS002367 (biochemistry_HbA1c.BOLT-LMM-BBJ) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
HbA1c | HbA1c measurement | 920,924 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002367/ScoringFiles/PGS002367.txt.gz |
| PGS002370 (blood_LYMPHOCYTE_COUNT.BOLT-LMM-BBJ) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Lymphocyte Count | lymphocyte count | 920,935 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002370/ScoringFiles/PGS002370.txt.gz |
| PGS002371 (blood_MEAN_CORPUSCULAR_HEMOGLOBIN.BOLT-LMM-BBJ) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Mean Corpuscular Hemoglobin | mean corpuscular hemoglobin | 920,923 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002371/ScoringFiles/PGS002371.txt.gz |
| PGS002372 (blood_MONOCYTE_COUNT.BOLT-LMM-BBJ) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Monocyte Count | monocyte count | 920,930 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002372/ScoringFiles/PGS002372.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 |
| PGS002374 (blood_RED_COUNT.BOLT-LMM-BBJ) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Count | erythrocyte count | 920,935 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002374/ScoringFiles/PGS002374.txt.gz |
| PGS002380 (blood_WHITE_COUNT.BOLT-LMM-BBJ) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
White Blood Count | leukocyte count | 920,936 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002380/ScoringFiles/PGS002380.txt.gz |
| PGS002397 (blood_EOSINOPHIL_COUNT.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Eosinophil count | eosinophil count | 15,667 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002397/ScoringFiles/PGS002397.txt.gz |
| PGS002403 (biochemistry_HbA1c.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
HbA1c | HbA1c measurement | 11,872 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002403/ScoringFiles/PGS002403.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 |
| PGS002410 (blood_LYMPHOCYTE_COUNT.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Lymphocyte Count | lymphocyte count | 14,889 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002410/ScoringFiles/PGS002410.txt.gz |
| PGS002411 (blood_MEAN_CORPUSCULAR_HEMOGLOBIN.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Mean Corpuscular Hemoglobin | mean corpuscular hemoglobin | 22,349 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002411/ScoringFiles/PGS002411.txt.gz |
| PGS002412 (blood_MEAN_PLATELET_VOL.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Mean Platelet Volume | mean platelet volume | 36,285 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002412/ScoringFiles/PGS002412.txt.gz |
| PGS002413 (blood_MONOCYTE_COUNT.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Monocyte Count | monocyte count | 17,405 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002413/ScoringFiles/PGS002413.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 |
| PGS002417 (blood_RED_COUNT.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Count | erythrocyte count | 18,514 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002417/ScoringFiles/PGS002417.txt.gz |
| PGS002418 (blood_RBC_DISTRIB_WIDTH.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Distribution Width | Red cell distribution width | 16,996 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002418/ScoringFiles/PGS002418.txt.gz |
| PGS002429 (blood_WHITE_COUNT.P+T.0.0001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
White Blood Count | leukocyte count | 13,898 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002429/ScoringFiles/PGS002429.txt.gz |
| PGS002446 (blood_EOSINOPHIL_COUNT.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Eosinophil count | eosinophil count | 35,512 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002446/ScoringFiles/PGS002446.txt.gz |
| PGS002452 (biochemistry_HbA1c.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
HbA1c | HbA1c measurement | 30,603 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002452/ScoringFiles/PGS002452.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 |
| PGS002459 (blood_LYMPHOCYTE_COUNT.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Lymphocyte Count | lymphocyte count | 36,117 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002459/ScoringFiles/PGS002459.txt.gz |
| PGS002460 (blood_MEAN_CORPUSCULAR_HEMOGLOBIN.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Mean Corpuscular Hemoglobin | mean corpuscular hemoglobin | 44,827 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002460/ScoringFiles/PGS002460.txt.gz |
| PGS002461 (blood_MEAN_PLATELET_VOL.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Mean Platelet Volume | mean platelet volume | 65,237 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002461/ScoringFiles/PGS002461.txt.gz |
| PGS002462 (blood_MONOCYTE_COUNT.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Monocyte Count | monocyte count | 38,012 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002462/ScoringFiles/PGS002462.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 |
| PGS002466 (blood_RED_COUNT.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Count | erythrocyte count | 41,471 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002466/ScoringFiles/PGS002466.txt.gz |
| PGS002467 (blood_RBC_DISTRIB_WIDTH.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Distribution Width | Red cell distribution width | 36,619 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002467/ScoringFiles/PGS002467.txt.gz |
| PGS002478 (blood_WHITE_COUNT.P+T.0.001) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
White Blood Count | leukocyte count | 35,005 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002478/ScoringFiles/PGS002478.txt.gz |
| PGS002495 (blood_EOSINOPHIL_COUNT.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Eosinophil count | eosinophil count | 135,927 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002495/ScoringFiles/PGS002495.txt.gz |
| PGS002501 (biochemistry_HbA1c.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
HbA1c | HbA1c measurement | 128,425 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002501/ScoringFiles/PGS002501.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 |
| PGS002508 (blood_LYMPHOCYTE_COUNT.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Lymphocyte Count | lymphocyte count | 140,957 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002508/ScoringFiles/PGS002508.txt.gz |
| PGS002509 (blood_MEAN_CORPUSCULAR_HEMOGLOBIN.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Mean Corpuscular Hemoglobin | mean corpuscular hemoglobin | 151,362 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002509/ScoringFiles/PGS002509.txt.gz |
| PGS002510 (blood_MEAN_PLATELET_VOL.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Mean Platelet Volume | mean platelet volume | 183,887 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002510/ScoringFiles/PGS002510.txt.gz |
| PGS002511 (blood_MONOCYTE_COUNT.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Monocyte Count | monocyte count | 140,833 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002511/ScoringFiles/PGS002511.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 |
| PGS002515 (blood_RED_COUNT.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Count | erythrocyte count | 150,047 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002515/ScoringFiles/PGS002515.txt.gz |
| PGS002516 (blood_RBC_DISTRIB_WIDTH.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Distribution Width | Red cell distribution width | 136,154 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002516/ScoringFiles/PGS002516.txt.gz |
| PGS002527 (blood_WHITE_COUNT.P+T.0.01) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
White Blood Count | leukocyte count | 141,866 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002527/ScoringFiles/PGS002527.txt.gz |
| PGS002544 (blood_EOSINOPHIL_COUNT.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Eosinophil count | eosinophil count | 6,683 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002544/ScoringFiles/PGS002544.txt.gz |
| PGS002550 (biochemistry_HbA1c.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
HbA1c | HbA1c measurement | 4,546 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002550/ScoringFiles/PGS002550.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 |
| PGS002557 (blood_LYMPHOCYTE_COUNT.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Lymphocyte Count | lymphocyte count | 5,729 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002557/ScoringFiles/PGS002557.txt.gz |
| PGS002558 (blood_MEAN_CORPUSCULAR_HEMOGLOBIN.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Mean Corpuscular Hemoglobin | mean corpuscular hemoglobin | 10,888 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002558/ScoringFiles/PGS002558.txt.gz |
| PGS002559 (blood_MEAN_PLATELET_VOL.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Mean Platelet Volume | mean platelet volume | 19,124 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002559/ScoringFiles/PGS002559.txt.gz |
| PGS002560 (blood_MONOCYTE_COUNT.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Monocyte Count | monocyte count | 7,666 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002560/ScoringFiles/PGS002560.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 |
| PGS002564 (blood_RED_COUNT.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Count | erythrocyte count | 7,590 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002564/ScoringFiles/PGS002564.txt.gz |
| PGS002565 (blood_RBC_DISTRIB_WIDTH.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Distribution Width | Red cell distribution width | 7,740 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002565/ScoringFiles/PGS002565.txt.gz |
| PGS002576 (blood_WHITE_COUNT.P+T.1e-06) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
White Blood Count | leukocyte count | 4,921 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002576/ScoringFiles/PGS002576.txt.gz |
| PGS002593 (blood_EOSINOPHIL_COUNT.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Eosinophil count | eosinophil count | 4,677 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002593/ScoringFiles/PGS002593.txt.gz |
| PGS002599 (biochemistry_HbA1c.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
HbA1c | HbA1c measurement | 3,055 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002599/ScoringFiles/PGS002599.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 |
| PGS002606 (blood_LYMPHOCYTE_COUNT.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Lymphocyte Count | lymphocyte count | 3,808 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002606/ScoringFiles/PGS002606.txt.gz |
| PGS002607 (blood_MEAN_CORPUSCULAR_HEMOGLOBIN.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Mean Corpuscular Hemoglobin | mean corpuscular hemoglobin | 8,017 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002607/ScoringFiles/PGS002607.txt.gz |
| PGS002608 (blood_MEAN_PLATELET_VOL.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Mean Platelet Volume | mean platelet volume | 14,380 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002608/ScoringFiles/PGS002608.txt.gz |
| PGS002609 (blood_MONOCYTE_COUNT.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Monocyte Count | monocyte count | 5,367 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002609/ScoringFiles/PGS002609.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 |
| PGS002613 (blood_RED_COUNT.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Count | erythrocyte count | 5,156 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002613/ScoringFiles/PGS002613.txt.gz |
| PGS002614 (blood_RBC_DISTRIB_WIDTH.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Distribution Width | Red cell distribution width | 5,543 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002614/ScoringFiles/PGS002614.txt.gz |
| PGS002625 (blood_WHITE_COUNT.P+T.5e-08) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
White Blood Count | leukocyte count | 3,184 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002625/ScoringFiles/PGS002625.txt.gz |
| PGS002642 (blood_EOSINOPHIL_COUNT.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Eosinophil count | eosinophil count | 346,331 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002642/ScoringFiles/PGS002642.txt.gz |
| PGS002648 (biochemistry_HbA1c.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
HbA1c | HbA1c measurement | 394,312 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002648/ScoringFiles/PGS002648.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 |
| PGS002655 (blood_LYMPHOCYTE_COUNT.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Lymphocyte Count | lymphocyte count | 472,203 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002655/ScoringFiles/PGS002655.txt.gz |
| PGS002656 (blood_MEAN_CORPUSCULAR_HEMOGLOBIN.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Mean Corpuscular Hemoglobin | mean corpuscular hemoglobin | 351,633 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002656/ScoringFiles/PGS002656.txt.gz |
| PGS002657 (blood_MEAN_PLATELET_VOL.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Mean Platelet Volume | mean platelet volume | 354,280 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002657/ScoringFiles/PGS002657.txt.gz |
| PGS002658 (blood_MONOCYTE_COUNT.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Monocyte Count | monocyte count | 353,881 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002658/ScoringFiles/PGS002658.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 |
| PGS002662 (blood_RED_COUNT.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Count | erythrocyte count | 473,515 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002662/ScoringFiles/PGS002662.txt.gz |
| PGS002663 (blood_RBC_DISTRIB_WIDTH.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Distribution Width | Red cell distribution width | 340,172 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002663/ScoringFiles/PGS002663.txt.gz |
| PGS002674 (blood_WHITE_COUNT.PolyFun-pred) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
White Blood Count | leukocyte count | 491,764 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002674/ScoringFiles/PGS002674.txt.gz |
| PGS002691 (blood_EOSINOPHIL_COUNT.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Eosinophil count | eosinophil count | 980,421 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002691/ScoringFiles/PGS002691.txt.gz |
| PGS002697 (biochemistry_HbA1c.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
HbA1c | HbA1c measurement | 989,344 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002697/ScoringFiles/PGS002697.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 |
| PGS002704 (blood_LYMPHOCYTE_COUNT.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Lymphocyte Count | lymphocyte count | 983,350 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002704/ScoringFiles/PGS002704.txt.gz |
| PGS002705 (blood_MEAN_CORPUSCULAR_HEMOGLOBIN.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Mean Corpuscular Hemoglobin | mean corpuscular hemoglobin | 979,778 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002705/ScoringFiles/PGS002705.txt.gz |
| PGS002706 (blood_MEAN_PLATELET_VOL.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Mean Platelet Volume | mean platelet volume | 973,986 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002706/ScoringFiles/PGS002706.txt.gz |
| PGS002707 (blood_MONOCYTE_COUNT.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Monocyte Count | monocyte count | 980,307 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002707/ScoringFiles/PGS002707.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 |
| PGS002711 (blood_RED_COUNT.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Count | erythrocyte count | 982,902 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002711/ScoringFiles/PGS002711.txt.gz |
| PGS002712 (blood_RBC_DISTRIB_WIDTH.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
Red Blood Cell Distribution Width | Red cell distribution width | 976,311 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002712/ScoringFiles/PGS002712.txt.gz |
| PGS002723 (blood_WHITE_COUNT.SBayesR) |
PGP000332 | Weissbrod O et al. Nat Genet (2022) |
White Blood Count | leukocyte count | 983,751 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS002723/ScoringFiles/PGS002723.txt.gz |
| PGS003330 (PRS-F8) |
PGP000395 | Valenti L et al. JHEP Rep (2022) |
Factor VIII levels | factor VIII measurement | 10 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003330/ScoringFiles/PGS003330.txt.gz |
| PGS003337 (CVGRS_HbA1c) |
PGP000405 | Kim YJ et al. Nat Commun (2022) |
Hemoglobin A1c level | HbA1c measurement | 68 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003337/ScoringFiles/PGS003337.txt.gz |
| PGS003346 (ALLGRS_HbA1c) |
PGP000405 | Kim YJ et al. Nat Commun (2022) |
Hemoglobin A1c level | HbA1c measurement | 74 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003346/ScoringFiles/PGS003346.txt.gz |
| PGS003464 (LDPred2_EOS) |
PGP000456 | Zhang Y et al. EBioMedicine (2022) |
Eosinophils count | eosinophil count | 859,056 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003464/ScoringFiles/PGS003464.txt.gz |
| PGS003467 (LDPred2_HCT) |
PGP000456 | Zhang Y et al. EBioMedicine (2022) |
Hematocrit | hematocrit | 860,314 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003467/ScoringFiles/PGS003467.txt.gz |
| PGS003468 (LDPred2_HGB) |
PGP000456 | Zhang Y et al. EBioMedicine (2022) |
Hemoglobin | hemoglobin measurement | 860,341 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003468/ScoringFiles/PGS003468.txt.gz |
| PGS003471 (LDPred2_HbA1c) |
PGP000456 | Zhang Y et al. EBioMedicine (2022) |
HbA1c | HbA1c measurement | 848,979 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003471/ScoringFiles/PGS003471.txt.gz |
| PGS003475 (LDPred2_LYM) |
PGP000456 | Zhang Y et al. EBioMedicine (2022) |
Lymphocyte count | lymphocyte count | 859,875 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003475/ScoringFiles/PGS003475.txt.gz |
| PGS003478 (LDPred2_RBC) |
PGP000456 | Zhang Y et al. EBioMedicine (2022) |
Red blood count | erythrocyte count | 860,281 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003478/ScoringFiles/PGS003478.txt.gz |
| PGS003483 (LDPred2_WBC) |
PGP000456 | Zhang Y et al. EBioMedicine (2022) |
White blood count | leukocyte count | 860,306 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003483/ScoringFiles/PGS003483.txt.gz |
| PGS003502 (cont-decay-erythrocyte) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Red blood cell (erythrocyte) count | erythrocyte count | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003502/ScoringFiles/PGS003502.txt.gz |
| PGS003503 (cont-decay-erythrocyte_width) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Red blood cell (erythrocyte) distribution width | Red cell distribution width | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003503/ScoringFiles/PGS003503.txt.gz |
| PGS003511 (cont-decay-haematocrit_perc) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Haematocrit percentage | hematocrit | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003511/ScoringFiles/PGS003511.txt.gz |
| PGS003512 (cont-decay-haemoglobin) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Haemoglobin concentration | hemoglobin measurement | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003512/ScoringFiles/PGS003512.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 |
| PGS003530 (cont-decay-log_eosinophil_perc) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Eosinophil percentage | eosinophil percentage of leukocytes | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003530/ScoringFiles/PGS003530.txt.gz |
| PGS003533 (cont-decay-log_HbA1c) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Glycated haemoglobin (HbA1c) | HbA1c measurement | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003533/ScoringFiles/PGS003533.txt.gz |
| PGS003541 (cont-decay-log_leukocyte) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
White blood cell (leukocyte) count | leukocyte count | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003541/ScoringFiles/PGS003541.txt.gz |
| PGS003544 (cont-decay-log_monocyte) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Monocyte count | monocyte count | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003544/ScoringFiles/PGS003544.txt.gz |
| PGS003545 (cont-decay-log_neutrophil) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Neutrophil count | neutrophil count | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003545/ScoringFiles/PGS003545.txt.gz |
| PGS003546 (cont-decay-log_platelet) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Platelet count | platelet count | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003546/ScoringFiles/PGS003546.txt.gz |
| PGS003547 (cont-decay-log_platelet_crit) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Platelet crit | platelet crit | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003547/ScoringFiles/PGS003547.txt.gz |
| PGS003548 (cont-decay-log_platelet_volume) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Mean platelet (thrombocyte) volume | mean platelet volume | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003548/ScoringFiles/PGS003548.txt.gz |
| PGS003549 (cont-decay-log_platelet_width) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Platelet distribution width | platelet component distribution width | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003549/ScoringFiles/PGS003549.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 |
| PGS003557 (cont-decay-lymphocyte_perc) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Lymphocyte percentage | lymphocyte percentage of leukocytes | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003557/ScoringFiles/PGS003557.txt.gz |
| PGS003560 (cont-decay-MCH) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Mean corpuscular haemoglobin | mean corpuscular hemoglobin | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003560/ScoringFiles/PGS003560.txt.gz |
| PGS003561 (cont-decay-MCV) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Mean corpuscular volume | mean corpuscular volume | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003561/ScoringFiles/PGS003561.txt.gz |
| PGS003562 (cont-decay-monocyte_perc) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Monocyte percentage | monocyte percentage of leukocytes | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003562/ScoringFiles/PGS003562.txt.gz |
| PGS003566 (cont-decay-neutrophil_perc) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Neutrophil percentage | neutrophil percentage of leukocytes | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003566/ScoringFiles/PGS003566.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 |
| PGS003570 (cont-decay-sphered_cell_volume) |
PGP000457 | Ding Y et al. bioRxiv (2022) |Pre |
Mean sphered cell volume | mean corpuscular volume | 979,739 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003570/ScoringFiles/PGS003570.txt.gz |
| PGS003924 (INI30000) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
White blood cell (leukocyte) count | leukocyte count | 17,890 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003924/ScoringFiles/PGS003924.txt.gz |
| PGS003925 (INI30010) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Red blood cell (erythrocyte) count | erythrocyte count | 27,293 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003925/ScoringFiles/PGS003925.txt.gz |
| PGS003926 (INI30020) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Hemoglobin concentration | hemoglobin measurement | 21,078 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003926/ScoringFiles/PGS003926.txt.gz |
| PGS003927 (INI30030) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Hematocrit percentage | hematocrit | 20,106 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003927/ScoringFiles/PGS003927.txt.gz |
| PGS003928 (INI30040) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Mean corpuscular volume | mean corpuscular volume | 21,818 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003928/ScoringFiles/PGS003928.txt.gz |
| PGS003929 (INI30050) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Mean corpuscular hemoglobin | mean corpuscular hemoglobin | 17,127 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003929/ScoringFiles/PGS003929.txt.gz |
| PGS003930 (INI30060) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Mean corpuscular hemoglobin concentration | mean corpuscular hemoglobin concentration | 4,468 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003930/ScoringFiles/PGS003930.txt.gz |
| PGS003931 (INI30070) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Red blood cell (erythrocyte) distribution width | Red cell distribution width | 12,557 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003931/ScoringFiles/PGS003931.txt.gz |
| PGS003932 (INI30080) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Platelet count | platelet count | 32,944 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003932/ScoringFiles/PGS003932.txt.gz |
| PGS003933 (INI30090) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Platelet crit | platelet crit | 27,034 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003933/ScoringFiles/PGS003933.txt.gz |
| PGS003934 (INI30100) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Mean platelet (thrombocyte) volume | mean platelet volume | 31,032 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003934/ScoringFiles/PGS003934.txt.gz |
| PGS003935 (INI30110) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Platelet distribution width | platelet component distribution width | 21,899 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003935/ScoringFiles/PGS003935.txt.gz |
| PGS003936 (INI30120) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Lymphocyte count | lymphocyte count | 7,291 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003936/ScoringFiles/PGS003936.txt.gz |
| PGS003937 (INI30130) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Monocyte count | monocyte count | 13,415 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003937/ScoringFiles/PGS003937.txt.gz |
| PGS003938 (INI30140) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Neutrophil count | neutrophil count | 18,612 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003938/ScoringFiles/PGS003938.txt.gz |
| PGS003939 (INI30150) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Eosinophil count | eosinophil count | 16,859 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003939/ScoringFiles/PGS003939.txt.gz |
| PGS003940 (INI30160) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Basophil count | basophil count | 4,184 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003940/ScoringFiles/PGS003940.txt.gz |
| PGS003941 (INI30180) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Lymphocyte percentage | lymphocyte percentage of leukocytes | 20,804 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003941/ScoringFiles/PGS003941.txt.gz |
| PGS003942 (INI30190) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Monocyte percentage | monocyte percentage of leukocytes | 10,717 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003942/ScoringFiles/PGS003942.txt.gz |
| PGS003943 (INI30200) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Neutrophil percentage | neutrophil percentage of leukocytes | 16,931 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003943/ScoringFiles/PGS003943.txt.gz |
| PGS003944 (INI30210) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Eosinophil percentage | eosinophil percentage of leukocytes | 17,227 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003944/ScoringFiles/PGS003944.txt.gz |
| PGS003945 (INI30220) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Basophil percentage | basophil percentage of leukocytes | 3,472 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003945/ScoringFiles/PGS003945.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 |
| PGS003949 (INI30270) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Mean sphered cell volume | mean corpuscular volume | 21,558 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003949/ScoringFiles/PGS003949.txt.gz |
| PGS003950 (INI30280) |
PGP000502 | Tanigawa Y et al. AJHG (2023) |
Immature reticulocyte fraction | Immature Reticulocyte Fraction Measurement | 16,307 | - |
https://ftp.ebi.ac.uk/pub/databases/spot/pgs/scores/PGS003950/ScoringFiles/PGS003950.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 |
|
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 |
|---|---|---|---|---|---|---|---|---|---|
| PPM000208 | PGS000088 (baso) |
PSS000153| European Ancestry| 80,944 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Basophil count | — | — | Pearson correlation coefficent (r): 0.20539 | 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) |
| PPM000209 | PGS000088 (baso) |
PSS000127| European Ancestry| 39,986 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Basophil count | — | — | Pearson correlation coefficent (r): 0.20489 | 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) | — |
| PPM000210 | PGS000089 (baso_p) |
PSS000154| European Ancestry| 80,906 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Basophil percentage of white cells | — | — | Pearson correlation coefficent (r): 0.18838 | 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) |
| PPM000211 | PGS000089 (baso_p) |
PSS000128| European Ancestry| 40,133 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Basophil percentage of white cells | — | — | Pearson correlation coefficent (r): 0.17123 | 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) | — |
| PPM000212 | PGS000090 (eo) |
PSS000155| European Ancestry| 81,294 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Eosinophil count | — | — | Pearson correlation coefficent (r): 0.40991 | 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) |
| PPM000213 | PGS000090 (eo) |
PSS000129| European Ancestry| 40,276 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Eosinophil count | — | — | Pearson correlation coefficent (r): 0.39315 | 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) | — |
| PPM000214 | PGS000091 (eo_p) |
PSS000156| European Ancestry| 81,283 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Eosinophil percentage of white cells | — | — | Pearson correlation coefficent (r): 0.39099 | 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) |
| PPM000215 | PGS000091 (eo_p) |
PSS000130| European Ancestry| 40,326 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Eosinophil percentage of white cells | — | — | Pearson correlation coefficent (r): 0.37643 | 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) | — |
| PPM000216 | PGS000092 (hct) |
PSS000157| European Ancestry| 81,622 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Hematocrit | — | — | Pearson correlation coefficent (r): 0.36874 | 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) |
| PPM000217 | PGS000092 (hct) |
PSS000131| European Ancestry| 40,340 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Hematocrit | — | — | Pearson correlation coefficent (r): 0.29832 | 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) | — |
| PPM000218 | PGS000093 (hgb) |
PSS000158| European Ancestry| 81,548 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Hemoglobin concentration | — | — | Pearson correlation coefficent (r): 0.37936 | 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) |
| PPM000219 | PGS000093 (hgb) |
PSS000132| European Ancestry| 40,329 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Hemoglobin concentration | — | — | Pearson correlation coefficent (r): 0.30254 | 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) | — |
| 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) | — |
| PPM000226 | PGS000097 (lymph) |
PSS000162| European Ancestry| 81,455 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Lymphocyte count | — | — | Pearson correlation coefficent (r): 0.40707 | 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) |
| PPM000227 | PGS000097 (lymph) |
PSS000136| European Ancestry| 39,191 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Lymphocyte count | — | — | Pearson correlation coefficent (r): 0.4055 | 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) | — |
| PPM000228 | PGS000098 (lymph_p) |
PSS000163| European Ancestry| 81,464 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Lymphocyte percentage of white cells | — | — | Pearson correlation coefficent (r): 0.33396 | 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) |
| PPM000229 | PGS000098 (lymph_p) |
PSS000137| European Ancestry| 39,178 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Lymphocyte percentage of white cells | — | — | Pearson correlation coefficent (r): 0.3313 | 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) | — |
| PPM000230 | PGS000099 (mch) |
PSS000164| European Ancestry| 81,303 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Mean corpuscular hemoglobin | — | — | Pearson correlation coefficent (r): 0.54504 | 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) |
| PPM000231 | PGS000099 (mch) |
PSS000138| European Ancestry| 40,108 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Mean corpuscular hemoglobin | — | — | Pearson correlation coefficent (r): 0.49689 | 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) | — |
| PPM000232 | PGS000100 (mchc) |
PSS000165| European Ancestry| 81,570 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Mean corpuscular hemoglobin concentration | — | — | Pearson correlation coefficent (r): 0.2805 | 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) |
| PPM000233 | PGS000100 (mchc) |
PSS000139| European Ancestry| 40,265 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Mean corpuscular hemoglobin concentration | — | — | Pearson correlation coefficent (r): 0.29105 | 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) | — |
| PPM000234 | PGS000101 (mcv) |
PSS000166| European Ancestry| 81,431 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Mean corpuscular volume | — | — | Pearson correlation coefficent (r): 0.5624 | 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) |
| PPM000235 | PGS000101 (mcv) |
PSS000140| European Ancestry| 40,080 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Mean corpuscular volume | — | — | Pearson correlation coefficent (r): 0.47754 | 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) | — |
| PPM000236 | PGS000102 (mono) |
PSS000167| European Ancestry| 80,799 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Monocyte count | — | — | Pearson correlation coefficent (r): 0.49849 | 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) |
| PPM000237 | PGS000102 (mono) |
PSS000141| European Ancestry| 39,177 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Monocyte count | — | — | Pearson correlation coefficent (r): 0.47594 | 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) | — |
| PPM000238 | PGS000103 (mono_p) |
PSS000168| European Ancestry| 80,627 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Monocyte percentage of white cells | — | — | Pearson correlation coefficent (r): 0.46271 | 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) |
| PPM000239 | PGS000103 (mono_p) |
PSS000142| European Ancestry| 39,189 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Monocyte percentage of white cells | — | — | Pearson correlation coefficent (r): 0.45879 | 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) | — |
| PPM000240 | PGS000104 (mpv) |
PSS000169| European Ancestry| 78,320 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Mean platelet volume | — | — | Pearson correlation coefficent (r): 0.61214 | 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) |
| PPM000241 | PGS000104 (mpv) |
PSS000143| European Ancestry| 37,224 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Mean platelet volume | — | — | Pearson correlation coefficent (r): 0.60875 | 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) | — |
| PPM000242 | PGS000105 (neut) |
PSS000170| European Ancestry| 81,358 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Neutrophil count | — | — | Pearson correlation coefficent (r): 0.36386 | 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) |
| PPM000243 | PGS000105 (neut) |
PSS000144| European Ancestry| 39,138 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Neutrophil count | — | — | Pearson correlation coefficent (r): 0.35194 | 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) | — |
| PPM000244 | PGS000106 (neut_p) |
PSS000171| European Ancestry| 81,423 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Neutrophil percentage of white cells | — | — | Pearson correlation coefficent (r): 0.32169 | 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) |
| PPM000245 | PGS000106 (neut_p) |
PSS000145| European Ancestry| 39,190 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Neutrophil percentage of white cells | — | — | Pearson correlation coefficent (r): 0.31935 | 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) | — |
| PPM000246 | PGS000107 (pct) |
PSS000172| European Ancestry| 78,161 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Plateletcrit | — | — | Pearson correlation coefficent (r): 0.49284 | 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) |
| PPM000247 | PGS000107 (pct) |
PSS000146| European Ancestry| 37,306 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Plateletcrit | — | — | Pearson correlation coefficent (r): 0.48865 | 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) | — |
| PPM000248 | PGS000108 (pdw) |
PSS000173| European Ancestry| 78,290 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Platelet distribution width | — | — | Pearson correlation coefficent (r): 0.49624 | 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) |
| PPM000249 | PGS000108 (pdw) |
PSS000147| European Ancestry| 37,262 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Platelet distribution width | — | — | Pearson correlation coefficent (r): 0.28359 | 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) | — |
| 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) | — |
| PPM000252 | PGS000110 (rbc) |
PSS000175| European Ancestry| 81,614 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Red blood cell count | — | — | Pearson correlation coefficent (r): 0.45067 | age, sex, 10 PCs of ancestry, lifestyle factors (diet, smoking, alcohol consumption), technical covariates (the time between venepuncture and full blood cell analysis, seasonal effects, centre of sample collection, time dependent drift of equipment, systematic differences in equipment) | UKB Testing Set - these samples were held out from Score Development (regression training) but overlap with the samples used for variant selection (GWAS) |
| PPM000253 | PGS000110 (rbc) |
PSS000149| European Ancestry| 40,262 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: Red blood cell count | — | — | Pearson correlation coefficent (r): 0.42574 | age, sex, 10 PCs of ancestry, lifestyle factors (diet, smoking, alcohol consumption), technical covariates (the time between venepuncture and full blood cell analysis, seasonal effects, centre of sample collection, time dependent drift of equipment, systematic differences in equipment) | — |
| 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) | — |
| PPM000258 | PGS000113 (wbc) |
PSS000178| European Ancestry| 81,606 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: White blood cell count | — | — | Pearson correlation coefficent (r): 0.39876 | 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) |
| PPM000259 | PGS000113 (wbc) |
PSS000152| European Ancestry| 40,466 individuals |
PGP000051 | Xu Y et al. Cell Genom (2022) |
Reported Trait: White blood cell count | — | — | Pearson correlation coefficent (r): 0.38866 | 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) | — |
| PPM000407 | PGS000127 (GS-E-EUR) |
PSS000236| European Ancestry| 37,357 individuals |
PGP000064 | Wheeler E et al. PLoS Med (2017) |
Reported Trait: Incident type 2 diabetes | OR: 1.0 [0.99, 1.01] | — | — | age, sex | — |
| PPM000408 | PGS000128 (GS-E-AFR) |
PSS000234| African Ancestry| 1,906 individuals |
PGP000064 | Wheeler E et al. PLoS Med (2017) |
Reported Trait: Incident type 2 diabetes | OR: 0.98 [0.96, 1.0] | — | — | age, sex | — |
| PPM000409 | PGS000129 (GS-E-EAS) |
PSS000235| East Asian Ancestry| 5,073 individuals |
PGP000064 | Wheeler E et al. PLoS Med (2017) |
Reported Trait: Incident type 2 diabetes | OR: 1.02 [0.99, 1.05] | — | — | age, sex | — |
| PPM000410 | PGS000130 (GS-G-EUR) |
PSS000236| European Ancestry| 37,357 individuals |
PGP000064 | Wheeler E et al. PLoS Med (2017) |
Reported Trait: Incident type 2 diabetes | OR: 1.05 [1.04, 1.06] | — | — | age, sex | — |
| PPM000411 | PGS000131 (GS-G-AFR) |
PSS000234| African Ancestry| 1,906 individuals |
PGP000064 | Wheeler E et al. PLoS Med (2017) |
Reported Trait: Incident type 2 diabetes | OR: 1.0 [0.95, 1.05] | — | — | age, sex | — |
| PPM000412 | PGS000132 (GS-G-EAS) |
PSS000235| East Asian Ancestry| 5,073 individuals |
PGP000064 | Wheeler E et al. PLoS Med (2017) |
Reported Trait: Incident type 2 diabetes | OR: 1.05 [1.02, 1.07] | — | — | age, sex | — |
| PPM000546 | PGS000163 (baso) |
PSS000290| European Ancestry| 2,314 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Basophil count | — | — | R²: 0.0089 | sex, age, 10 genetic PCs | — |
| PPM000519 | PGS000163 (baso) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Basophil count | — | — | R²: 0.02691 | sex, age, 10 genetic PCs | — |
| PPM000520 | PGS000164 (baso_p) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Basophil percentage of white cells | — | — | R²: 0.02544 | sex, age, 10 genetic PCs | — |
| PPM000547 | PGS000165 (eo) |
PSS000290| European Ancestry| 2,314 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Eosinophil count | — | — | R²: 0.06931 | sex, age, 10 genetic PCs | — |
| PPM000521 | PGS000165 (eo) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Eosinophil count | — | — | R²: 0.11155 | sex, age, 10 genetic PCs | — |
| PPM000522 | PGS000166 (eo_p) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Eosinophil percentage of white cells | — | — | R²: 0.0979 | sex, age, 10 genetic PCs | — |
| PPM001777 | PGS000167 (hct) |
PSS000911| Greater Middle Eastern Ancestry| 13,989 individuals |
PGP000147 | Thareja G et al. Nat Commun (2021) |Ext. |
Reported Trait: Hematocrit | — | — | Pearson correlation coefficent (r): 0.15 | — | — |
| PPM000548 | PGS000167 (hct) |
PSS000290| European Ancestry| 2,314 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Hematocrit | — | — | R²: 0.05147 | sex, age, 10 genetic PCs | — |
| PPM000523 | PGS000167 (hct) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Hematocrit | — | — | R²: 0.04931 | sex, age, 10 genetic PCs | — |
| PPM001778 | PGS000168 (hgb) |
PSS000911| Greater Middle Eastern Ancestry| 13,989 individuals |
PGP000147 | Thareja G et al. Nat Commun (2021) |Ext. |
Reported Trait: Hemoglobin | — | — | Pearson correlation coefficent (r): 0.14 | — | — |
| PPM000549 | PGS000168 (hgb) |
PSS000290| European Ancestry| 2,314 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Hemoglobin concentration | — | — | R²: 0.0646 | sex, age, 10 genetic PCs | — |
| PPM000524 | PGS000168 (hgb) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Hemoglobin concentration | — | — | R²: 0.05697 | sex, age, 10 genetic PCs | — |
| 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 | — |
| PPM000550 | PGS000172 (lymph) |
PSS000290| European Ancestry| 2,314 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Lymphocyte count | — | — | R²: 0.03217 | sex, age, 10 genetic PCs | — |
| PPM000528 | PGS000172 (lymph) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Lymphocyte count | — | — | R²: 0.10555 | sex, age, 10 genetic PCs | — |
| PPM000529 | PGS000173 (lymph_p) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Lymphocyte percentage of white cells | — | — | R²: 0.06965 | sex, age, 10 genetic PCs | — |
| PPM000552 | PGS000174 (mch) |
PSS000290| European Ancestry| 2,314 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Mean corpuscular hemoglobin | — | — | R²: 0.17483 | sex, age, 10 genetic PCs | — |
| PPM000530 | PGS000174 (mch) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Mean corpuscular hemoglobin | — | — | R²: 0.18282 | sex, age, 10 genetic PCs | — |
| PPM001773 | PGS000174 (mch) |
PSS000911| Greater Middle Eastern Ancestry| 13,989 individuals |
PGP000147 | Thareja G et al. Nat Commun (2021) |Ext. |
Reported Trait: Mean corpuscular hemoglobin | — | — | Pearson correlation coefficent (r): 0.22 | — | — |
| PPM000551 | PGS000175 (mchc) |
PSS000290| European Ancestry| 2,314 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Mean corpuscular hemoglobin concentration | — | — | R²: 0.04796 | sex, age, 10 genetic PCs | — |
| PPM000531 | PGS000175 (mchc) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Mean corpuscular hemoglobin concentration | — | — | R²: 0.05159 | sex, age, 10 genetic PCs | — |
| PPM001772 | PGS000175 (mchc) |
PSS000911| Greater Middle Eastern Ancestry| 13,989 individuals |
PGP000147 | Thareja G et al. Nat Commun (2021) |Ext. |
Reported Trait: Mean cell hemoglobin concentration | — | — | Pearson correlation coefficent (r): 0.12 | — | — |
| PPM000553 | PGS000176 (mcv) |
PSS000290| European Ancestry| 2,314 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Mean corpuscular volume | — | — | R²: 0.1665 | sex, age, 10 genetic PCs | — |
| PPM000532 | PGS000176 (mcv) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Mean corpuscular volume | — | — | R²: 0.15931 | sex, age, 10 genetic PCs | — |
| PPM001774 | PGS000176 (mcv) |
PSS000911| Greater Middle Eastern Ancestry| 13,989 individuals |
PGP000147 | Thareja G et al. Nat Commun (2021) |Ext. |
Reported Trait: Mean corpuscular volume | — | — | Pearson correlation coefficent (r): 0.23 | — | — |
| PPM000554 | PGS000177 (mono) |
PSS000290| European Ancestry| 2,314 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Monocyte count | — | — | R²: 0.09474 | sex, age, 10 genetic PCs | — |
| PPM000533 | PGS000177 (mono) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Monocyte count | — | — | R²: 0.15859 | sex, age, 10 genetic PCs | — |
| PPM000534 | PGS000178 (mono_p) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Monocyte percentage of white cells | — | — | R²: 0.14461 | sex, age, 10 genetic PCs | — |
| PPM000555 | PGS000179 (mpv) |
PSS000290| European Ancestry| 2,314 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Mean platelet volume | — | — | R²: 0.19379 | sex, age, 10 genetic PCs | — |
| PPM000535 | PGS000179 (mpv) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Mean platelet volume | — | — | R²: 0.27306 | sex, age, 10 genetic PCs | — |
| PPM001776 | PGS000179 (mpv) |
PSS000911| Greater Middle Eastern Ancestry| 13,989 individuals |
PGP000147 | Thareja G et al. Nat Commun (2021) |Ext. |
Reported Trait: Mean platelet volume | — | — | Pearson correlation coefficent (r): 0.51 | — | — |
| PPM000556 | PGS000182 (neut) |
PSS000290| European Ancestry| 2,314 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Neutrophil count | — | — | R²: 0.06859 | sex, age, 10 genetic PCs | — |
| PPM000536 | PGS000182 (neut) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Neutrophil count | — | — | R²: 0.08009 | sex, age, 10 genetic PCs | — |
| PPM000537 | PGS000183 (neut_p) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Neutrophil percentage of white cells | — | — | R²: 0.06432 | sex, age, 10 genetic PCs | — |
| PPM000538 | PGS000184 (pct) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Plateletcrit | — | — | R²: 0.1555 | sex, age, 10 genetic PCs | — |
| PPM000539 | PGS000185 (pdw) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Platelet distribution width | — | — | R²: 0.05996 | sex, age, 10 genetic PCs | — |
| 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 | — |
| PPM000558 | PGS000187 (rbc) |
PSS000290| European Ancestry| 2,314 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Red blood cell count | — | — | R²: 0.06798 | sex, age, 10 genetic PCs | — |
| PPM000541 | PGS000187 (rbc) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Red blood cell count | — | — | R²: 0.11765 | sex, age, 10 genetic PCs | — |
| PPM001771 | PGS000187 (rbc) |
PSS000911| Greater Middle Eastern Ancestry| 13,989 individuals |
PGP000147 | Thareja G et al. Nat Commun (2021) |Ext. |
Reported Trait: Red blood cell count | — | — | Pearson correlation coefficent (r): 0.22 | — | — |
| PPM000559 | PGS000188 (rdw) |
PSS000290| European Ancestry| 2,314 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Red cell distribution width | — | — | R²: 0.07409 | sex, age, 10 genetic PCs | — |
| PPM000542 | PGS000188 (rdw) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: Red cell distribution width | — | — | R²: 0.09519 | 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 | — |
| PPM000560 | PGS000191 (wbc) |
PSS000290| European Ancestry| 2,314 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: White blood cell count | — | — | R²: 0.06336 | sex, age, 10 genetic PCs | — |
| PPM000545 | PGS000191 (wbc) |
PSS000291| European Ancestry| 39,260 individuals |
PGP000078 | Vuckovic D et al. Cell (2020) |
Reported Trait: White blood cell count | — | — | R²: 0.08672 | sex, age, 10 genetic PCs | — |
| PPM001770 | PGS000191 (wbc) |
PSS000911| Greater Middle Eastern Ancestry| 13,989 individuals |
PGP000147 | Thareja G et al. Nat Commun (2021) |Ext. |
Reported Trait: White blood cell count | — | — | Pearson correlation coefficent (r): 0.19 | — | — |
| PPM000774 | PGS000304 (GRS43_HbA1c) |
PSS000376| European Ancestry| 1,354 individuals |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Reported Trait: HbA1c (%) | — | — | R²: 0.0283 | Sex, age, age^2 | — |
| PPM000803 | PGS000304 (GRS43_HbA1c) |
PSS000371| European Ancestry| 288 individuals |
PGP000092 | Xie T et al. Circ Genom Precis Med (2020) |
Reported Trait: HbA1c (%) | — | — | R²: 0.0277 | Sex, age, age^2 | — |
| PPM001413 | PGS000685 (snpnet.Glycated_haemoglobin_HbA1c) |
PSS000704| African Ancestry| 4,847 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: HbA1c [mmol/mol] | — | — | R²: 0.07974 Spearman's ρ: 0.132 |
Age, sex, PCs(1-40) | — |
| PPM001448 | PGS000685 (snpnet.Glycated_haemoglobin_HbA1c) |
PSS000705| East Asian Ancestry| 1,032 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: HbA1c [mmol/mol] | — | — | R²: 0.16979 Spearman's ρ: 0.285 |
Age, sex, PCs(1-40) | — |
| PPM001483 | PGS000685 (snpnet.Glycated_haemoglobin_HbA1c) |
PSS000706| European Ancestry| 22,518 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: HbA1c [mmol/mol] | — | — | R²: 0.17335 Spearman's ρ: 0.367 |
Age, sex, PCs(1-40) | — |
| PPM001518 | PGS000685 (snpnet.Glycated_haemoglobin_HbA1c) |
PSS000707| South Asian Ancestry| 6,895 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: HbA1c [mmol/mol] | — | — | R²: 0.12743 Spearman's ρ: 0.268 |
Age, sex, PCs(1-40) | — |
| PPM001553 | PGS000685 (snpnet.Glycated_haemoglobin_HbA1c) |
PSS000708| European Ancestry| 60,920 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: HbA1c [mmol/mol] | — | — | R²: 0.16381 Spearman's ρ: 0.375 |
Age, sex, PCs(1-40) | — |
| PPM001585 | PGS000685 (snpnet.Glycated_haemoglobin_HbA1c) |
PSS000817| European Ancestry| 1,995 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: HbA1c [mmol/mol] | — | — | Spearman's ρ: 0.217 | Age, sex | — |
| PPM007350 | PGS000685 (snpnet.Glycated_haemoglobin_HbA1c) |
PSS007156| African Ancestry| 5,219 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |Ext. |
Reported Trait: Glycated haemoglobin (HbA1c) | — | — | R²: 0.05396 [0.04328, 0.06464] Incremental R2 (full-covars): 0.00054 PGS R2 (no covariates): 0.00619 [0.00239, 0.00998] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007351 | PGS000685 (snpnet.Glycated_haemoglobin_HbA1c) |
PSS007157| East Asian Ancestry| 1,622 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |Ext. |
Reported Trait: Glycated haemoglobin (HbA1c) | — | — | R²: 0.1264 [0.09696, 0.15583] Incremental R2 (full-covars): 0.00207 PGS R2 (no covariates): 0.04145 [0.02295, 0.05994] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007352 | PGS000685 (snpnet.Glycated_haemoglobin_HbA1c) |
PSS007158| European Ancestry| 23,762 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |Ext. |
Reported Trait: Glycated haemoglobin (HbA1c) | — | — | R²: 0.06205 [0.05625, 0.06785] Incremental R2 (full-covars): 0.00348 PGS R2 (no covariates): 0.06567 [0.05972, 0.07162] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007353 | PGS000685 (snpnet.Glycated_haemoglobin_HbA1c) |
PSS007159| South Asian Ancestry| 7,345 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |Ext. |
Reported Trait: Glycated haemoglobin (HbA1c) | — | — | R²: 0.05344 [0.04375, 0.06313] Incremental R2 (full-covars): 0.00135 PGS R2 (no covariates): 0.03576 [0.02769, 0.04383] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007354 | PGS000685 (snpnet.Glycated_haemoglobin_HbA1c) |
PSS007160| European Ancestry| 64,432 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |Ext. |
Reported Trait: Glycated haemoglobin (HbA1c) | — | — | R²: 0.05264 [0.04936, 0.05592] Incremental R2 (full-covars): 0.00369 PGS R2 (no covariates): 0.06933 [0.06563, 0.07303] |
age, sex, UKB array type, Genotype PCs | — |
| PPM001426 | PGS000698 (snpnet.Total_protein) |
PSS000767| African Ancestry| 5,573 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: Total protein [g/L] | — | — | R²: 0.04363 Spearman's ρ: 0.144 |
Age, sex, PCs(1-40) | — |
| PPM001531 | PGS000698 (snpnet.Total_protein) |
PSS000770| South Asian Ancestry| 6,687 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: Total protein [g/L] | — | — | R²: 0.10522 Spearman's ρ: 0.258 |
Age, sex, PCs(1-40) | — |
| PPM001566 | PGS000698 (snpnet.Total_protein) |
PSS000771| European Ancestry| 58,196 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: Total protein [g/L] | — | — | R²: 0.11218 Spearman's ρ: 0.284 |
Age, sex, PCs(1-40) | — |
| PPM001461 | PGS000698 (snpnet.Total_protein) |
PSS000768| East Asian Ancestry| 984 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: Total protein [g/L] | — | — | R²: 0.09275 Spearman's ρ: 0.247 |
Age, sex, PCs(1-40) | — |
| PPM001496 | PGS000698 (snpnet.Total_protein) |
PSS000769| European Ancestry| 21,516 individuals |
PGP000128 | Sinnott-Armstrong N et al. Nat Genet (2021) |
Reported Trait: Total protein [g/L] | — | — | R²: 0.11654 Spearman's ρ: 0.282 |
Age, sex, PCs(1-40) | — |
| PPM007415 | PGS000698 (snpnet.Total_protein) |
PSS007201| African Ancestry| 5,659 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |Ext. |
Reported Trait: Total protein | — | — | R²: 0.01038 [0.00548, 0.01528] Incremental R2 (full-covars): 0.00061 PGS R2 (no covariates): 0.02117 [0.01425, 0.0281] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007416 | PGS000698 (snpnet.Total_protein) |
PSS007202| East Asian Ancestry| 1,474 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |Ext. |
Reported Trait: Total protein | — | — | R²: 0.04549 [0.0262, 0.06478] Incremental R2 (full-covars): 0.00107 PGS R2 (no covariates): 0.05677 [0.03548, 0.07807] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007417 | PGS000698 (snpnet.Total_protein) |
PSS007203| European Ancestry| 21,730 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |Ext. |
Reported Trait: Total protein | — | — | R²: 0.01493 [0.01194, 0.01792] Incremental R2 (full-covars): 0.00167 PGS R2 (no covariates): 0.07937 [0.07293, 0.08581] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007418 | PGS000698 (snpnet.Total_protein) |
PSS007204| South Asian Ancestry| 6,788 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |Ext. |
Reported Trait: Total protein | — | — | R²: 0.01363 [0.00853, 0.01873] Incremental R2 (full-covars): 0.00134 PGS R2 (no covariates): 0.0679 [0.05715, 0.07866] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007419 | PGS000698 (snpnet.Total_protein) |
PSS007205| European Ancestry| 59,024 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |Ext. |
Reported Trait: Total protein | — | — | R²: 0.00668 [0.00545, 0.0079] Incremental R2 (full-covars): 0.00176 PGS R2 (no covariates): 0.08081 [0.07687, 0.08476] |
age, sex, UKB array type, Genotype 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 | — |
| PPM008138 | PGS001076 (GBE_INI30210) |
PSS007006| African Ancestry| 6,120 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Eosinophill % | — | — | R²: 0.02749 [0.01965, 0.03533] Incremental R2 (full-covars): 0.01358 PGS R2 (no covariates): 0.01502 [0.00915, 0.02088] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008139 | PGS001076 (GBE_INI30210) |
PSS007007| East Asian Ancestry| 1,654 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Eosinophill % | — | — | R²: 0.0678 [0.0448, 0.0908] Incremental R2 (full-covars): 0.03179 PGS R2 (no covariates): 0.03326 [0.01655, 0.04996] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008140 | PGS001076 (GBE_INI30210) |
PSS007008| European Ancestry| 24,130 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Eosinophill % | — | — | R²: 0.10724 [0.09998, 0.1145] Incremental R2 (full-covars): 0.09158 PGS R2 (no covariates): 0.09579 [0.08884, 0.10274] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008141 | PGS001076 (GBE_INI30210) |
PSS007009| South Asian Ancestry| 7,491 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Eosinophill % | — | — | R²: 0.08004 [0.06852, 0.09157] Incremental R2 (full-covars): 0.0618 PGS R2 (no covariates): 0.06258 [0.05219, 0.07296] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008142 | PGS001076 (GBE_INI30210) |
PSS007010| European Ancestry| 65,520 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Eosinophill % | — | — | R²: 0.10364 [0.09929, 0.108] Incremental R2 (full-covars): 0.09566 PGS R2 (no covariates): 0.09594 [0.09171, 0.10016] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008143 | PGS001077 (GBE_INI30200) |
PSS007001| African Ancestry| 6,120 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Neutrophill % | — | — | Incremental R2 (full-covars): 0.01344 R²: 0.04156 [0.03206, 0.05106] PGS R2 (no covariates): 0.01383 [0.00819, 0.01946] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008144 | PGS001077 (GBE_INI30200) |
PSS007002| East Asian Ancestry| 1,654 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Neutrophill % | — | — | R²: 0.07662 [0.0524, 0.10084] Incremental R2 (full-covars): 0.04345 PGS R2 (no covariates): 0.04564 [0.02632, 0.06496] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008145 | PGS001077 (GBE_INI30200) |
PSS007003| European Ancestry| 24,130 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Neutrophill % | — | — | R²: 0.07418 [0.06792, 0.08044] Incremental R2 (full-covars): 0.07151 PGS R2 (no covariates): 0.07289 [0.06667, 0.0791] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008146 | PGS001077 (GBE_INI30200) |
PSS007004| South Asian Ancestry| 7,491 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Neutrophill % | — | — | R²: 0.05036 [0.04093, 0.0598] Incremental R2 (full-covars): 0.04554 PGS R2 (no covariates): 0.04441 [0.03549, 0.05333] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008147 | PGS001077 (GBE_INI30200) |
PSS007005| European Ancestry| 65,520 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Neutrophill % | — | — | R²: 0.08175 [0.07779, 0.08572] Incremental R2 (full-covars): 0.07935 PGS R2 (no covariates): 0.07934 [0.07542, 0.08325] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008148 | PGS001078 (GBE_INI30190) |
PSS006996| African Ancestry| 6,120 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Monocyte % | — | — | R²: 0.03107 [0.02277, 0.03938] Incremental R2 (full-covars): 0.01068 PGS R2 (no covariates): 0.01162 [0.00644, 0.0168] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008149 | PGS001078 (GBE_INI30190) |
PSS006997| East Asian Ancestry| 1,654 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Monocyte % | — | — | R²: 0.10068 [0.07364, 0.12772] Incremental R2 (full-covars): 0.04628 PGS R2 (no covariates): 0.04808 [0.0283, 0.06786] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008150 | PGS001078 (GBE_INI30190) |
PSS006998| European Ancestry| 24,130 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Monocyte % | — | — | R²: 0.12442 [0.11675, 0.13209] Incremental R2 (full-covars): 0.08036 PGS R2 (no covariates): 0.08169 [0.07518, 0.08821] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008151 | PGS001078 (GBE_INI30190) |
PSS006999| South Asian Ancestry| 7,491 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Monocyte % | — | — | R²: 0.12434 [0.11066, 0.13801] Incremental R2 (full-covars): 0.05529 PGS R2 (no covariates): 0.05423 [0.04448, 0.06398] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008152 | PGS001078 (GBE_INI30190) |
PSS007000| European Ancestry| 65,520 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Monocyte % | — | — | R²: 0.12757 [0.12287, 0.13228] Incremental R2 (full-covars): 0.08527 PGS R2 (no covariates): 0.08574 [0.0817, 0.08978] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008153 | PGS001079 (GBE_INI30110) |
PSS006961| African Ancestry| 6,139 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Platelet distribution width | — | — | R²: 0.08809 [0.07494, 0.10125] Incremental R2 (full-covars): 0.05017 PGS R2 (no covariates): 0.05279 [0.04222, 0.06337] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008154 | PGS001079 (GBE_INI30110) |
PSS006962| East Asian Ancestry| 1,655 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Platelet distribution width | — | — | R²: 0.1275 [0.09798, 0.15703] Incremental R2 (full-covars): 0.09522 PGS R2 (no covariates): 0.09877 [0.07193, 0.12561] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008155 | PGS001079 (GBE_INI30110) |
PSS006963| European Ancestry| 24,171 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Platelet distribution width | — | — | R²: 0.2279 [0.21875, 0.23705] Incremental R2 (full-covars): 0.20117 PGS R2 (no covariates): 0.2053 [0.19636, 0.21424] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008156 | PGS001079 (GBE_INI30110) |
PSS006964| South Asian Ancestry| 7,519 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Platelet distribution width | — | — | R²: 0.18488 [0.16936, 0.2004] Incremental R2 (full-covars): 0.16662 PGS R2 (no covariates): 0.16657 [0.15151, 0.18163] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008157 | PGS001079 (GBE_INI30110) |
PSS006965| European Ancestry| 65,601 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Platelet distribution width | — | — | R²: 0.22746 [0.2219, 0.23302] Incremental R2 (full-covars): 0.20559 PGS R2 (no covariates): 0.20528 [0.19985, 0.21072] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008482 | PGS001152 (GBE_INI30070) |
PSS006941| African Ancestry| 6,139 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell distribution width | — | — | R²: 0.02633 [0.01865, 0.03401] Incremental R2 (full-covars): 0.00466 PGS R2 (no covariates): 0.00617 [0.00238, 0.00997] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008483 | PGS001152 (GBE_INI30070) |
PSS006942| East Asian Ancestry| 1,655 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell distribution width | — | — | R²: 0.06947 [0.04623, 0.09271] Incremental R2 (full-covars): 0.04028 PGS R2 (no covariates): 0.04714 [0.02754, 0.06675] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008484 | PGS001152 (GBE_INI30070) |
PSS006943| European Ancestry| 24,175 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell distribution width | — | — | R²: 0.08241 [0.07587, 0.08895] Incremental R2 (full-covars): 0.07409 PGS R2 (no covariates): 0.0754 [0.06909, 0.0817] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008485 | PGS001152 (GBE_INI30070) |
PSS006944| South Asian Ancestry| 7,520 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell distribution width | — | — | R²: 0.06357 [0.05312, 0.07403] Incremental R2 (full-covars): 0.04077 PGS R2 (no covariates): 0.04137 [0.03274, 0.05] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008486 | PGS001152 (GBE_INI30070) |
PSS006945| European Ancestry| 65,638 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell distribution width | — | — | R²: 0.0852 [0.08117, 0.08923] Incremental R2 (full-covars): 0.07926 PGS R2 (no covariates): 0.07945 [0.07553, 0.08337] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008537 | PGS001163 (GBE_INI30130) |
PSS006971| African Ancestry| 6,120 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Monocyte count | — | — | R²: 0.02543 [0.01787, 0.03298] Incremental R2 (full-covars): 0.01339 PGS R2 (no covariates): 0.01659 [0.01043, 0.02274] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008538 | PGS001163 (GBE_INI30130) |
PSS006972| East Asian Ancestry| 1,654 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Monocyte count | — | — | R²: 0.10427 [0.07686, 0.13168] Incremental R2 (full-covars): 0.03555 PGS R2 (no covariates): 0.04025 [0.022, 0.0585] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008539 | PGS001163 (GBE_INI30130) |
PSS006973| European Ancestry| 24,129 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Monocyte count | — | — | R²: 0.12792 [0.12017, 0.13567] Incremental R2 (full-covars): 0.0805 PGS R2 (no covariates): 0.08361 [0.07703, 0.09019] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008540 | PGS001163 (GBE_INI30130) |
PSS006974| South Asian Ancestry| 7,491 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Monocyte count | — | — | R²: 0.09808 [0.08557, 0.11059] Incremental R2 (full-covars): 0.05583 PGS R2 (no covariates): 0.05525 [0.04542, 0.06508] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008541 | PGS001163 (GBE_INI30130) |
PSS006975| European Ancestry| 65,520 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Monocyte count | — | — | R²: 0.11973 [0.11513, 0.12432] Incremental R2 (full-covars): 0.081 PGS R2 (no covariates): 0.08138 [0.07742, 0.08533] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008570 | PGS001172 (GBE_INI30150) |
PSS006981| African Ancestry| 6,120 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Eosinophill count | — | — | R²: 0.02165 [0.01465, 0.02865] Incremental R2 (full-covars): 0.01273 PGS R2 (no covariates): 0.01483 [0.009, 0.02067] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008571 | PGS001172 (GBE_INI30150) |
PSS006982| East Asian Ancestry| 1,654 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Eosinophill count | — | — | R²: 0.07017 [0.04683, 0.09352] Incremental R2 (full-covars): 0.02406 PGS R2 (no covariates): 0.02686 [0.01175, 0.04197] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008572 | PGS001172 (GBE_INI30150) |
PSS006983| European Ancestry| 24,129 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Eosinophill count | — | — | R²: 0.10592 [0.09869, 0.11315] Incremental R2 (full-covars): 0.08944 PGS R2 (no covariates): 0.0939 [0.08701, 0.1008] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008573 | PGS001172 (GBE_INI30150) |
PSS006984| South Asian Ancestry| 7,491 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Eosinophill count | — | — | R²: 0.06486 [0.05432, 0.07541] Incremental R2 (full-covars): 0.05229 PGS R2 (no covariates): 0.05348 [0.04379, 0.06318] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008574 | PGS001172 (GBE_INI30150) |
PSS006985| European Ancestry| 65,520 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Eosinophill count | — | — | R²: 0.10264 [0.0983, 0.10698] Incremental R2 (full-covars): 0.09343 PGS R2 (no covariates): 0.09398 [0.08978, 0.09817] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008575 | PGS001173 (GBE_INI30140) |
PSS006976| African Ancestry| 6,120 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Neutrophill count | — | — | R²: 0.06347 [0.052, 0.07494] Incremental R2 (full-covars): 0.00644 PGS R2 (no covariates): 0.01221 [0.00691, 0.01752] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008576 | PGS001173 (GBE_INI30140) |
PSS006977| East Asian Ancestry| 1,654 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Neutrophill count | — | — | R²: 0.05754 [0.03611, 0.07896] Incremental R2 (full-covars): 0.037 PGS R2 (no covariates): 0.0354 [0.0182, 0.0526] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008577 | PGS001173 (GBE_INI30140) |
PSS006978| European Ancestry| 24,129 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Neutrophill count | — | — | R²: 0.08794 [0.08123, 0.09466] Incremental R2 (full-covars): 0.07899 PGS R2 (no covariates): 0.08282 [0.07627, 0.08938] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008578 | PGS001173 (GBE_INI30140) |
PSS006979| South Asian Ancestry| 7,491 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Neutrophill count | — | — | R²: 0.07553 [0.06428, 0.08677] Incremental R2 (full-covars): 0.0671 PGS R2 (no covariates): 0.06762 [0.05688, 0.07835] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008579 | PGS001173 (GBE_INI30140) |
PSS006980| European Ancestry| 65,520 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Neutrophill count | — | — | R²: 0.09385 [0.08966, 0.09804] Incremental R2 (full-covars): 0.08871 PGS R2 (no covariates): 0.08935 [0.08524, 0.09346] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008616 | PGS001199 (GBE_INI30120) |
PSS006968| European Ancestry| 24,129 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Lymphocyte count | — | — | R²: 0.04047 [0.03568, 0.04526] Incremental R2 (full-covars): 0.03437 PGS R2 (no covariates): 0.03502 [0.03053, 0.0395] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008614 | PGS001199 (GBE_INI30120) |
PSS006966| African Ancestry| 6,120 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Lymphocyte count | — | — | R²: 0.01509 [0.00921, 0.02097] Incremental R2 (full-covars): 0.0048 PGS R2 (no covariates): 0.00655 [0.00264, 0.01046] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008615 | PGS001199 (GBE_INI30120) |
PSS006967| East Asian Ancestry| 1,654 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Lymphocyte count | — | — | R²: 0.07751 [0.05317, 0.10185] Incremental R2 (full-covars): 0.02783 PGS R2 (no covariates): 0.0308 [0.01468, 0.04692] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008617 | PGS001199 (GBE_INI30120) |
PSS006969| South Asian Ancestry| 7,491 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Lymphocyte count | — | — | R²: 0.04041 [0.03187, 0.04896] Incremental R2 (full-covars): 0.02891 PGS R2 (no covariates): 0.02928 [0.02192, 0.03663] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008618 | PGS001199 (GBE_INI30120) |
PSS006970| European Ancestry| 65,520 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Lymphocyte count | — | — | R²: 0.02566 [0.0233, 0.02801] Incremental R2 (full-covars): 0.02051 PGS R2 (no covariates): 0.02072 [0.01859, 0.02285] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008619 | PGS001200 (GBE_INI30100) |
PSS006956| African Ancestry| 6,139 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean platelet volume | — | — | R²: 0.11523 [0.10064, 0.12983] Incremental R2 (full-covars): 0.10713 PGS R2 (no covariates): 0.10764 [0.09341, 0.12187] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008620 | PGS001200 (GBE_INI30100) |
PSS006957| East Asian Ancestry| 1,655 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean platelet volume | — | — | R²: 0.22982 [0.19483, 0.26481] Incremental R2 (full-covars): 0.1912 PGS R2 (no covariates): 0.20572 [0.17158, 0.23986] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008621 | PGS001200 (GBE_INI30100) |
PSS006958| European Ancestry| 24,175 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean platelet volume | — | — | R²: 0.36048 [0.35094, 0.37001] Incremental R2 (full-covars): 0.35332 PGS R2 (no covariates): 0.3577 [0.34816, 0.36724] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008622 | PGS001200 (GBE_INI30100) |
PSS006959| South Asian Ancestry| 7,520 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean platelet volume | — | — | R²: 0.26489 [0.24813, 0.28164] Incremental R2 (full-covars): 0.25606 PGS R2 (no covariates): 0.25974 [0.24303, 0.27644] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008623 | PGS001200 (GBE_INI30100) |
PSS006960| European Ancestry| 65,636 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean platelet volume | — | — | R²: 0.36177 [0.35598, 0.36757] Incremental R2 (full-covars): 0.35994 PGS R2 (no covariates): 0.36024 [0.35444, 0.36603] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008624 | PGS001218 (GBE_INI30060) |
PSS006936| African Ancestry| 6,139 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean corpuscular haemoglobin concentration | — | — | R²: 0.01334 [0.0078, 0.01888] Incremental R2 (full-covars): 0.0007 PGS R2 (no covariates): 0.00244 [0.00004, 0.00483] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008625 | PGS001218 (GBE_INI30060) |
PSS006937| East Asian Ancestry| 1,655 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean corpuscular haemoglobin concentration | — | — | R²: 0.05415 [0.03329, 0.07501] Incremental R2 (full-covars): 0.01409 PGS R2 (no covariates): 0.01986 [0.00677, 0.03295] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008626 | PGS001218 (GBE_INI30060) |
PSS006938| European Ancestry| 24,175 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean corpuscular haemoglobin concentration | — | — | R²: 0.02769 [0.02367, 0.03171] Incremental R2 (full-covars): 0.01601 PGS R2 (no covariates): 0.01701 [0.01382, 0.02019] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008627 | PGS001218 (GBE_INI30060) |
PSS006939| South Asian Ancestry| 7,520 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean corpuscular haemoglobin concentration | — | — | R²: 0.04592 [0.03687, 0.05498] Incremental R2 (full-covars): 0.01608 PGS R2 (no covariates): 0.01906 [0.01306, 0.02505] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008628 | PGS001218 (GBE_INI30060) |
PSS006940| European Ancestry| 65,635 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean corpuscular haemoglobin concentration | — | — | R²: 0.03753 [0.03472, 0.04035] Incremental R2 (full-covars): 0.02447 PGS R2 (no covariates): 0.02534 [0.023, 0.02768] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008629 | PGS001219 (GBE_INI30050) |
PSS006931| African Ancestry| 6,139 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean corpuscular haemoglobin | — | — | R²: 0.03354 [0.02494, 0.04215] Incremental R2 (full-covars): 0.00833 PGS R2 (no covariates): 0.01254 [0.00717, 0.01792] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008630 | PGS001219 (GBE_INI30050) |
PSS006932| East Asian Ancestry| 1,655 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean corpuscular haemoglobin | — | — | R²: 0.0892 [0.06342, 0.11498] Incremental R2 (full-covars): 0.03143 PGS R2 (no covariates): 0.0524 [0.03184, 0.07296] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008631 | PGS001219 (GBE_INI30050) |
PSS006933| European Ancestry| 24,175 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean corpuscular haemoglobin | — | — | R²: 0.16096 [0.1526, 0.16932] Incremental R2 (full-covars): 0.12049 PGS R2 (no covariates): 0.13012 [0.12233, 0.13791] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008632 | PGS001219 (GBE_INI30050) |
PSS006934| South Asian Ancestry| 7,520 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean corpuscular haemoglobin | — | — | R²: 0.11958 [0.1061, 0.13306] Incremental R2 (full-covars): 0.06684 PGS R2 (no covariates): 0.07101 [0.06005, 0.08197] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008633 | PGS001219 (GBE_INI30050) |
PSS006935| European Ancestry| 65,638 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean corpuscular haemoglobin | — | — | R²: 0.18797 [0.18266, 0.19328] Incremental R2 (full-covars): 0.1678 PGS R2 (no covariates): 0.1703 [0.16513, 0.17547] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008634 | PGS001220 (GBE_INI30040) |
PSS006926| African Ancestry| 6,139 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean corpuscular volume | — | — | R²: 0.03909 [0.02986, 0.04833] Incremental R2 (full-covars): 0.01317 PGS R2 (no covariates): 0.01523 [0.00932, 0.02114] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008635 | PGS001220 (GBE_INI30040) |
PSS006927| East Asian Ancestry| 1,655 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean corpuscular volume | — | — | R²: 0.09134 [0.06532, 0.11737] Incremental R2 (full-covars): 0.03736 PGS R2 (no covariates): 0.05987 [0.03807, 0.08167] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008636 | PGS001220 (GBE_INI30040) |
PSS006928| European Ancestry| 24,175 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean corpuscular volume | — | — | R²: 0.20688 [0.19792, 0.21584] Incremental R2 (full-covars): 0.15861 PGS R2 (no covariates): 0.17414 [0.16558, 0.1827] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008637 | PGS001220 (GBE_INI30040) |
PSS006929| South Asian Ancestry| 7,520 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean corpuscular volume | — | — | R²: 0.12834 [0.11451, 0.14216] Incremental R2 (full-covars): 0.07837 PGS R2 (no covariates): 0.08395 [0.0722, 0.0957] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008638 | PGS001220 (GBE_INI30040) |
PSS006930| European Ancestry| 65,638 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Mean corpuscular volume | — | — | R²: 0.21614 [0.21064, 0.22164] Incremental R2 (full-covars): 0.19948 PGS R2 (no covariates): 0.20189 [0.19648, 0.2073] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008639 | PGS001225 (GBE_INI30030) |
PSS006921| African Ancestry| 6,139 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Haematocrit % | — | — | Incremental R2 (full-covars): 0.01035 R²: 0.39181 [0.37331, 0.41032] PGS R2 (no covariates): 0.01326 [0.00774, 0.01879] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008640 | PGS001225 (GBE_INI30030) |
PSS006922| East Asian Ancestry| 1,655 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Haematocrit % | — | — | R²: 0.4128 [0.37705, 0.44856] Incremental R2 (full-covars): 0.02196 PGS R2 (no covariates): 0.02063 [0.0073, 0.03396] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008641 | PGS001225 (GBE_INI30030) |
PSS006923| European Ancestry| 24,175 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Haematocrit % | — | — | R²: 0.396 [0.38656, 0.40544] Incremental R2 (full-covars): 0.05878 PGS R2 (no covariates): 0.06263 [0.0568, 0.06846] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008642 | PGS001225 (GBE_INI30030) |
PSS006924| South Asian Ancestry| 7,520 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Haematocrit % | — | — | R²: 0.4249 [0.4083, 0.4415] Incremental R2 (full-covars): 0.02482 PGS R2 (no covariates): 0.0222 [0.01575, 0.02865] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008643 | PGS001225 (GBE_INI30030) |
PSS006925| European Ancestry| 65,638 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Haematocrit % | — | — | R²: 0.39123 [0.38548, 0.39698] Incremental R2 (full-covars): 0.06504 PGS R2 (no covariates): 0.06544 [0.06183, 0.06904] |
age, sex, UKB array type, Genotype 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 | — |
| PPM008704 | PGS001239 (GBE_INI30000) |
PSS006891| African Ancestry| 6,139 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: White blood cell count | — | — | R²: 0.05282 [0.04224, 0.0634] Incremental R2 (full-covars): 0.00963 PGS R2 (no covariates): 0.01451 [0.00874, 0.02028] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008705 | PGS001239 (GBE_INI30000) |
PSS006892| East Asian Ancestry| 1,655 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: White blood cell count | — | — | R²: 0.07596 [0.05182, 0.10009] Incremental R2 (full-covars): 0.0496 PGS R2 (no covariates): 0.05069 [0.03044, 0.07095] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008706 | PGS001239 (GBE_INI30000) |
PSS006893| European Ancestry| 24,174 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: White blood cell count | — | — | R²: 0.08839 [0.08166, 0.09513] Incremental R2 (full-covars): 0.07763 PGS R2 (no covariates): 0.08212 [0.07559, 0.08865] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008707 | PGS001239 (GBE_INI30000) |
PSS006894| South Asian Ancestry| 7,520 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: White blood cell count | — | — | R²: 0.07166 [0.06066, 0.08267] Incremental R2 (full-covars): 0.06404 PGS R2 (no covariates): 0.06438 [0.05387, 0.07489] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008708 | PGS001239 (GBE_INI30000) |
PSS006895| European Ancestry| 65,638 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: White blood cell count | — | — | R²: 0.0777 [0.07382, 0.08158] Incremental R2 (full-covars): 0.07177 PGS R2 (no covariates): 0.07264 [0.06887, 0.07641] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008709 | PGS001240 (GBE_INI30010) |
PSS006896| African Ancestry| 6,139 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell count | — | — | R²: 0.26906 [0.25063, 0.28749] Incremental R2 (full-covars): 0.01652 PGS R2 (no covariates): 0.01819 [0.01175, 0.02463] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008710 | PGS001240 (GBE_INI30010) |
PSS006897| East Asian Ancestry| 1,655 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell count | — | — | R²: 0.32546 [0.289, 0.36193] Incremental R2 (full-covars): 0.04519 PGS R2 (no covariates): 0.05665 [0.03538, 0.07793] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008711 | PGS001240 (GBE_INI30010) |
PSS006898| European Ancestry| 24,175 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell count | — | — | R²: 0.37954 [0.37005, 0.38904] Incremental R2 (full-covars): 0.10462 PGS R2 (no covariates): 0.11155 [0.10418, 0.11892] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008712 | PGS001240 (GBE_INI30010) |
PSS006899| South Asian Ancestry| 7,520 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell count | — | — | R²: 0.33598 [0.31894, 0.35302] Incremental R2 (full-covars): 0.05745 PGS R2 (no covariates): 0.05295 [0.0433, 0.0626] |
age, sex, UKB array type, Genotype PCs | — |
| PPM008713 | PGS001240 (GBE_INI30010) |
PSS006900| European Ancestry| 65,638 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Red blood cell count | — | — | R²: 0.37344 [0.36766, 0.37922] Incremental R2 (full-covars): 0.11681 PGS R2 (no covariates): 0.11784 [0.11327, 0.12241] |
age, sex, UKB array type, Genotype PCs | — |
| PPM005139 | PGS001352 (MAGICTA_EUR_PGS_HbA1c) |
PSS003594| European Ancestry| 61,820 individuals |
PGP000246 | Chen J et al. Nat Genet (2021) |
Reported Trait: Glycated haemoglobin levels (HbA1c) | — | — | R²: 0.178 | — | — |
| PPM005142 | PGS001352 (MAGICTA_EUR_PGS_HbA1c) |
PSS003591| African Ancestry| 6,647 individuals |
PGP000246 | Chen J et al. Nat Genet (2021) |
Reported Trait: Glycated haemoglobin levels (HbA1c) | — | — | R²: 0.012 | — | — |
| PPM005145 | PGS001352 (MAGICTA_EUR_PGS_HbA1c) |
PSS003593| East Asian Ancestry| 31,236 individuals |
PGP000246 | Chen J et al. Nat Genet (2021) |
Reported Trait: Glycated haemoglobin levels (HbA1c) | — | — | R²: 0.026 | — | — |
| PPM005146 | PGS001352 (MAGICTA_EUR_PGS_HbA1c) |
PSS003592| African Ancestry| 4,441 individuals |
PGP000246 | Chen J et al. Nat Genet (2021) |
Reported Trait: Glycated haemoglobin levels (HbA1c) | — | — | R²: 0.006 | — | — |
| PPM007058 | PGS001377 (GBE_INI30220) |
PSS007014| South Asian Ancestry| 7,491 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Basophill % | — | — | R²: 0.01668 [0.01106, 0.0223] Incremental R2 (full-covars): 0.01178 PGS R2 (no covariates): 0.01253 [0.00763, 0.01742] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007059 | PGS001377 (GBE_INI30220) |
PSS007015| European Ancestry| 65,520 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Basophill % | — | — | R²: 0.01674 [0.01482, 0.01866] Incremental R2 (full-covars): 0.01485 PGS R2 (no covariates): 0.01504 [0.01321, 0.01686] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007055 | PGS001377 (GBE_INI30220) |
PSS007011| African Ancestry| 6,120 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Basophill % | — | — | R²: 0.00639 [0.00253, 0.01025] Incremental R2 (full-covars): 0.00238 PGS R2 (no covariates): 0.00249 [0.00007, 0.00491] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007056 | PGS001377 (GBE_INI30220) |
PSS007012| East Asian Ancestry| 1,654 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Basophill % | — | — | R²: 0.01523 [0.00371, 0.02675] Incremental R2 (full-covars): 0.00867 PGS R2 (no covariates): 0.00896 [0.00007, 0.01786] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007057 | PGS001377 (GBE_INI30220) |
PSS007013| European Ancestry| 24,130 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Basophill % | — | — | R²: 0.01922 [0.01584, 0.0226] Incremental R2 (full-covars): 0.01406 PGS R2 (no covariates): 0.0152 [0.01219, 0.01822] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007045 | PGS001378 (GBE_INI30160) |
PSS006986| African Ancestry| 6,120 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Basophill count | — | — | R²: 0.0091 [0.0045, 0.01369] Incremental R2 (full-covars): 0.00051 PGS R2 (no covariates): 0.00175 [-0.00028, 0.00379] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007046 | PGS001378 (GBE_INI30160) |
PSS006987| East Asian Ancestry| 1,654 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Basophill count | — | — | R²: 0.01746 [0.00516, 0.02976] Incremental R2 (full-covars): 0.00946 PGS R2 (no covariates): 0.00963 [0.00042, 0.01883] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007047 | PGS001378 (GBE_INI30160) |
PSS006988| European Ancestry| 24,129 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Basophill count | — | — | R²: 0.01903 [0.01567, 0.0224] Incremental R2 (full-covars): 0.01496 PGS R2 (no covariates): 0.01602 [0.01293, 0.01911] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007048 | PGS001378 (GBE_INI30160) |
PSS006989| South Asian Ancestry| 7,491 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Basophill count | — | — | R²: 0.01814 [0.01228, 0.02399] Incremental R2 (full-covars): 0.01206 PGS R2 (no covariates): 0.01266 [0.00775, 0.01758] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007049 | PGS001378 (GBE_INI30160) |
PSS006990| European Ancestry| 65,520 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Basophill count | — | — | R²: 0.01717 [0.01523, 0.01911] Incremental R2 (full-covars): 0.01451 PGS R2 (no covariates): 0.01475 [0.01294, 0.01655] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007035 | PGS001400 (GBE_INI30020) |
PSS006901| African Ancestry| 6,139 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Haemoglobin concentration | — | — | R²: 0.38602 [0.36748, 0.40456] Incremental R2 (full-covars): 0.00491 PGS R2 (no covariates): 0.01221 [0.00691, 0.01752] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007036 | PGS001400 (GBE_INI30020) |
PSS006902| East Asian Ancestry| 1,655 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Haemoglobin concentration | — | — | R²: 0.40783 [0.37199, 0.44367] Incremental R2 (full-covars): 0.02084 PGS R2 (no covariates): 0.01558 [0.00394, 0.02723] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007037 | PGS001400 (GBE_INI30020) |
PSS006903| European Ancestry| 24,175 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Haemoglobin concentration | — | — | R²: 0.43532 [0.42607, 0.44457] Incremental R2 (full-covars): 0.06361 PGS R2 (no covariates): 0.06382 [0.05795, 0.06969] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007038 | PGS001400 (GBE_INI30020) |
PSS006904| South Asian Ancestry| 7,520 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Haemoglobin concentration | — | — | R²: 0.4337 [0.41719, 0.45022] Incremental R2 (full-covars): 0.02482 PGS R2 (no covariates): 0.01823 [0.01236, 0.0241] |
age, sex, UKB array type, Genotype PCs | — |
| PPM007039 | PGS001400 (GBE_INI30020) |
PSS006905| European Ancestry| 65,638 individuals |
PGP000244 | Tanigawa Y et al. PLoS Genet (2022) |
Reported Trait: Haemoglobin concentration | — | — | R²: 0.42918 [0.42353, 0.43482] Incremental R2 (full-covars): 0.06776 PGS R2 (no covariates): 0.06681 [0.06316, 0.07045] |
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): |