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| Line |
Allele |
Population |
% of individuals
that have the allele |
Allele
Frequency
(in_decimals) |
Sample
Size |
IMGT/HLA¹
Database |
Distribution² |
Haplotype³
Association |
Notesª |
| 1 |
A*02:17 |  | Belgium pop 3 | 0.3 | 0.0013 |  | 31,412 | See |  |  |
|
| 2 |
A*02:17 |  | Brazil Belo Horizonte Caucasian | 0.0 | 0 |  | 95 | See |  |  | |
| 3 |
A*02:17 |  | Brazil Mixed | | 0.0050 |  | 108 | See |  |  | |
| 4 |
A*02:17 |  | Bulgaria | | 0.0090 |  | 55 | See |  |  | |
| 5 |
A*02:17 |  | Cape Verde Northwestern Islands | | 0 |  | 62 | See |  |  | |
| 6 |
A*02:17 |  | Cape Verde Southeastern Islands | | 0.0080 |  | 62 | See |  |  | |
| 7 |
A*02:17 |  | China Beijing Shijiazhuang Tianjian Han | | 0.0010 |  | 618 | See |  |  | |
| 8 |
A*02:17 |  | China North Han | | 0 |  | 105 | See |  |  | |
| 9 |
A*02:17 |  | China Tibet Region Tibetan | | 0 |  | 158 | See |  |  | |
| 10 |
A*02:17 |  | Colombia Bogotá Cord Blood | 0.8 | 0.0041 |  | 1,463 | See |  |  | |
| 11 |
A*02:17 |  | Croatia | | 0.0030 |  | 150 | See |  |  | |
| 12 |
A*02:17 |  | Cuba Caucasian | 1.4 | 0.0070 |  | 70 | See |  |  | |
| 13 |
A*02:17 |  | Cuba Mixed Race | 0.0 | 0 |  | 42 | See |  |  | |
| 14 |
A*02:17 |  | Czech Republic | | 0 |  | 106 | See |  |  | |
| 15 |
A*02:17 |  | Czech Republic NMDR | | 0.0019 |  | 5,099 | See |  |  | |
| 16 |
A*02:17 |  | Georgia Tibilisi | | 0.0050 |  | 109 | See |  |  | |
| 17 |
A*02:17 |  | Germany DKMS - Austria minority | | 0.0012 |  | 1,698 | See |  |  | |
| 18 |
A*02:17 |  | Germany DKMS - China minority | | 0.0004 |  | 1,282 | See |  |  | |
| 19 |
A*02:17 |  | Germany DKMS - Croatia minority | | 0.0002 |  | 2,057 | See |  |  | |
| 20 |
A*02:17 |  | Germany DKMS - France minority | | 0.0004 |  | 1,406 | See |  |  | |
| 21 |
A*02:17 |  | Germany DKMS - German donors | | 0.0010 |  | 3,456,066 | See |  |  |
|
| 22 |
A*02:17 |  | Germany DKMS - Greece minority | | 0.0042 |  | 1,894 | See |  |  | |
| 23 |
A*02:17 |  | Germany DKMS - Italy minority | | 0.0035 |  | 1,159 | See |  |  | |
| 24 |
A*02:17 |  | Germany DKMS - Netherlands minority | | 0.0007 |  | 1,374 | See |  |  | |
| 25 |
A*02:17 |  | Germany DKMS - Romania minority | | 0.0032 |  | 1,234 | See |  |  | |
| 26 |
A*02:17 |  | Germany DKMS - Spain minority | | 0.0009 |  | 1,107 | See |  |  | |
| 27 |
A*02:17 |  | Germany DKMS - Turkey minority | | 0.0056 |  | 4,856 | See |  |  | |
| 28 |
A*02:17 |  | Germany pop 6 | | 0.0010 |  | 8,862 | See |  |  | |
| 29 |
A*02:17 |  | Germany pop 8 | | 0.0013 |  | 39,689 | See |  |  | |
| 30 |
A*02:17 |  | Guinea Bissau | | 0 |  | 65 | See |  |  | |
| 31 |
A*02:17 |  | Hong Kong Chinese | 0.0 | 0 |  | 569 | See |  |  | |
| 32 |
A*02:17 |  | India Delhi pop 2 | 1.1 | 0.0050 |  | 90 | See |  |  | |
| 33 |
A*02:17 |  | Ireland Northern | 0.1 | 0.0010 |  | 1,000 | See |  |  | |
| 34 |
A*02:17 |  | Israel Arab pop 2 | | 0.0028 |  | 12,301 | See |  |  |
|
| 35 |
A*02:17 |  | Israel Argentina Jews | | 0.0007 |  | 4,307 | See |  |  |
|
| 36 |
A*02:17 |  | Israel Ashkenazi and Non Ashkenazi Jews | | 0.0090 |  | 146 | See |  |  | |
| 37 |
A*02:17 |  | Israel Ashkenazi Jews pop 3 | | 0.0241 |  | 4,625 | See |  |  |
|
| 38 |
A*02:17 |  | Israel Bukhara Jews | | 0.0062 |  | 2,317 | See |  |  |
|
| 39 |
A*02:17 |  | Israel Druze | | 0.0004 |  | 5,914 | See |  |  |
|
| 40 |
A*02:17 |  | Israel Ethiopia Jews | | 0.0024 |  | 5,928 | See |  |  |
|
| 41 |
A*02:17 |  | Israel Iran Jews | | 0.0541 |  | 8,153 | See |  |  |
|
| 42 |
A*02:17 |  | Israel Iraq Jews | | 0.0717 |  | 13,270 | See |  |  |
|
| 43 |
A*02:17 |  | Israel Kavkazi Jews | | 0.0018 |  | 2,840 | See |  |  |
|
| 44 |
A*02:17 |  | Israel Libya Jews | | 0.0064 |  | 3,739 | See |  |  |
|
| 45 |
A*02:17 |  | Israel Morocco Jews | | 0.0038 |  | 36,718 | See |  |  |
|
| 46 |
A*02:17 |  | Israel Poland Jews | | 0.0028 |  | 13,871 | See |  |  |
|
| 47 |
A*02:17 |  | Israel Tunisia Jews | | 0.0057 |  | 9,070 | See |  |  |
|
| 48 |
A*02:17 |  | Israel USA Jews | | 0.0005 |  | 6,058 | See |  |  |
|
| 49 |
A*02:17 |  | Israel USSR Jews | | 0.0028 |  | 45,681 | See |  |  |
|
| 50 |
A*02:17 |  | Israel YemenJews | | 0.0582 |  | 15,542 | See |  |  |
|
| 51 |
A*02:17 |  | Italy Bergamo | 1.0 | 0.0060 |  | 101 | See |  |  | |
| 52 |
A*02:17 |  | Italy North pop 3 | 0.0 | 0 |  | 97 | See |  |  | |
| 53 |
A*02:17 |  | Italy pop 5 | | 0.0060 |  | 975 | See |  |  | |
| 54 |
A*02:17 |  | Kenya Luo | | 0 |  | 265 | See |  |  | |
| 55 |
A*02:17 |  | Kenya Nandi | | 0 |  | 240 | See |  |  | |
| 56 |
A*02:17 |  | Mali Bandiagara | | 0.0040 |  | 138 | See |  |  | |
| 57 |
A*02:17 |  | Mexico Mestizo | 0.0 | 0 |  | 41 | See |  |  | |
| 58 |
A*02:17 |  | Morocco Nador Metalsa pop 2 | | 0 |  | 73 | See |  |  | |
| 59 |
A*02:17 |  | Morocco Settat Chaouya | 0.0 | 0 |  | 98 | See |  |  | |
| 60 |
A*02:17 |  | Netherlands Leiden | | 0 |  | 1,305 | See |  |  | |
| 61 |
A*02:17 |  | Nicaragua Managua | 0.3 | 0.0015 |  | 339 | See |  |  |
|
| 62 |
A*02:17 |  | Oman | 0.0 | 0 |  | 118 | See |  |  | |
| 63 |
A*02:17 |  | Pakistan Baloch | | 0 |  | 66 | See |  |  | |
| 64 |
A*02:17 |  | Pakistan Brahui | | 0 |  | 104 | See |  |  | |
| 65 |
A*02:17 |  | Pakistan Burusho | | 0 |  | 92 | See |  |  | |
| 66 |
A*02:17 |  | Pakistan Kalash | | 0 |  | 69 | See |  |  | |
| 67 |
A*02:17 |  | Pakistan Karachi Parsi | | 0 |  | 91 | See |  |  | |
| 68 |
A*02:17 |  | Pakistan Mixed Pathan | | 0 |  | 100 | See |  |  | |
| 69 |
A*02:17 |  | Pakistan Mixed Sindhi | | 0 |  | 101 | See |  |  | |
| 70 |
A*02:17 |  | Panama | | 0.0079 |  | 462 | See |  |  |
|
| 71 |
A*02:17 |  | Philippines Ivatan | 0.0 | 0 |  | 50 | See |  |  | |
| 72 |
A*02:17 |  | Poland DKMS | | 0.0017 |  | 20,653 | See |  |  | |
| 73 |
A*02:17 |  | Romania | 0.3 | 0.0010 |  | 348 | See |  |  | |
| 74 |
A*02:17 |  | Russia Karelia | | 0.0005 |  | 1,075 | See |  |  |
|
| 75 |
A*02:17 |  | Russia Tuva pop 2 | | 0.0030 |  | 169 | See |  |  | |
| 76 |
A*02:17 |  | Sao Tome Island Angolar | | 0 |  | 32 | See |  |  | |
| 77 |
A*02:17 |  | Sao Tome Island Forro | | 0.0080 |  | 66 | See |  |  | |
| 78 |
A*02:17 |  | Scotland Orkney | 0.0 | 0 |  | 99 | See |  |  | |
| 79 |
A*02:17 |  | Singapore Chinese | 0.0 | 0 |  | 149 | See |  |  | |
| 80 |
A*02:17 |  | South Africa Caucasians | | 0.0050 |  | 102 | See |  |  | |
| 81 |
A*02:17 |  | South Africa Natal Zulu | 0.0 | 0 |  | 100 | See |  |  | |
| 82 |
A*02:17 |  | Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, | 0.3 | 0.0013 |  | 4,335 | See |  |  |
|
| 83 |
A*02:17 |  | Taiwan Ami | 0.0 | 0 |  | 98 | See |  |  | |
| 84 |
A*02:17 |  | Taiwan Atayal | 0.0 | 0 |  | 106 | See |  |  | |
| 85 |
A*02:17 |  | Taiwan Bunun | 0.0 | 0 |  | 101 | See |  |  | |
| 86 |
A*02:17 |  | Taiwan Hakka | 0.0 | 0 |  | 55 | See |  |  | |
| 87 |
A*02:17 |  | Taiwan Minnan pop 1 | 0.0 | 0 |  | 102 | See |  |  | |
| 88 |
A*02:17 |  | Taiwan Paiwan | 0.0 | 0 |  | 51 | See |  |  | |
| 89 |
A*02:17 |  | Taiwan Pazeh | 0.0 | 0 |  | 55 | See |  |  | |
| 90 |
A*02:17 |  | Taiwan Puyuma | 0.0 | 0 |  | 50 | See |  |  | |
| 91 |
A*02:17 |  | Taiwan Rukai | 0.0 | 0 |  | 50 | See |  |  | |
| 92 |
A*02:17 |  | Taiwan Saisiat | 0.0 | 0 |  | 51 | See |  |  | |
| 93 |
A*02:17 |  | Taiwan Siraya | 0.0 | 0 |  | 51 | See |  |  | |
| 94 |
A*02:17 |  | Taiwan Tao | 0.0 | 0 |  | 50 | See |  |  | |
| 95 |
A*02:17 |  | Taiwan Taroko | 0.0 | 0 |  | 55 | See |  |  | |
| 96 |
A*02:17 |  | Taiwan Thao | 0.0 | 0 |  | 30 | See |  |  | |
| 97 |
A*02:17 |  | Taiwan Tsou | 0.0 | 0 |  | 51 | See |  |  | |
| 98 |
A*02:17 |  | Turkey pop 5 | | 0.0070 |  | 142 | See |  |  | |
| 99 |
A*02:17 |  | Uganda Kampala | | 0 |  | 161 | See |  |  | |
| 100 |
A*02:17 |  | United Arab Emirates Pop 1 | | 0.0040 |  | 570 | See |  |  |
|
Notes:
* Allele Frequency: Total number of copies of the allele in the population sample (Alleles / 2n) in decimal format.
Important: This field has been expanded to four decimals to better represent frequencies of large datasets (e.g. where sample size > 1000 individuals)
* % of individuals that have the allele: Percentage of individuals who have the allele in the population (Individuals / n).
* Allele Frequencies shown in
green were calculated from Phenotype Frequencies assuming Hardy-Weinberg proportions.
AF = 1-square_root(1-PF)
PF = 1-(1-AF)
2
AF = Allele Frequency; PF = Phenotype Frequency, i.e. (%) of the individuals carrying the allele.
* Allele Frequencies marked with (*) were calculated from all alleles in the corresponding
G group.
¹ IMGT/HLA Database - For more details of the allele.
² Distribution - Graphical distribution of the allele.
³ Haplotype Association - Find HLA haplotypes with this allele.
ª Notes - See notes for ambiguous combinations of alleles.
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