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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*02:06 |  | American Samoa | | 0.1300 |  | 51 | See |  |  | |
| 2 |
A*02:06 |  | Armenia combined Regions | | 0.0050 |  | 100 | See |  |  | |
| 3 |
A*02:06 |  | Australia New South Wales Caucasian | | 0 |  | 134 | See |  |  | |
| 4 |
A*02:06 |  | Australia Yuendumu Aborigine | | 0 |  | 191 | See |  |  | |
| 5 |
A*02:06 |  | Austria | 0.5 | 0.0020 |  | 200 | See |  |  | |
| 6 |
A*02:06 |  | Azores Terceira Island | | 0.0040 |  | 130 | See |  |  | |
| 7 |
A*02:06 |  | Belgium pop 3 | 0.4 | 0.0018 |  | 31,412 | See |  |  |
|
| 8 |
A*02:06 |  | Brazil Belo Horizonte Caucasian | 0.0 | 0 |  | 95 | See |  |  | |
| 9 |
A*02:06 |  | Bulgaria | | 0 |  | 55 | See |  |  | |
| 10 |
A*02:06 |  | Chile Santiago Mixed | 1.0 | 0.0050 |  | 70 | See |  |  | |
| 11 |
A*02:06 |  | China Beijing | | 0.0480 |  | 67 | See |  |  | |
| 12 |
A*02:06 |  | China Beijing Shijiazhuang Tianjian Han | | 0.0470 |  | 618 | See |  |  | |
| 13 |
A*02:06 |  | China Canton Han | | 0.0380 |  | 264 | See |  |  | |
| 14 |
A*02:06 |  | China Guangxi Region Maonan | | 0.0460 |  | 108 | See |  |  | |
| 15 |
A*02:06 |  | China Guangzhou | | 0.0400 |  | 102 | See |  |  | |
| 16 |
A*02:06 |  | China Han HIV negative | | 0.0630 |  | 72 | See |  |  | |
| 17 |
A*02:06 |  | China Henan HIV negative | | 0.0630 |  | 16 | See |  |  | |
| 18 |
A*02:06 |  | China Hubei Han | 7.5 | 0.0376 |  | 3,732 | See |  |  |
|
| 19 |
A*02:06 |  | China Jiangsu Han | | 0.0560 |  | 3,238 | See |  |  | |
| 20 |
A*02:06 |  | China Jiangsu Province Han | | 0.0436 |  | 334 | See |  |  | |
| 21 |
A*02:06 |  | China North Han | | 0.0710 |  | 105 | See |  |  | |
| 22 |
A*02:06 |  | China Shanxi HIV negative | | 0.0450 |  | 22 | See |  |  | |
| 23 |
A*02:06 |  | China Sichuan HIV negative | | 0.0440 |  | 34 | See |  |  | |
| 24 |
A*02:06 |  | China South Han | | 0.0350 |  | 284 | See |  |  | |
| 25 |
A*02:06 |  | China Southwest Dai | | 0.0080 |  | 124 | See |  |  | |
| 26 |
A*02:06 |  | China Tibet Region Tibetan | | 0 |  | 158 | See |  |  | |
| 27 |
A*02:06 |  | China Uyghur HIV negative | | 0.0530 |  | 19 | See |  |  | |
| 28 |
A*02:06 |  | China Yunnan Hani | | 0.0130 |  | 150 | See |  |  | |
| 29 |
A*02:06 |  | China Yunnan Province Han | | 0.0590 |  | 101 | See |  |  | |
| 30 |
A*02:06 |  | Colombia Bogotá Cord Blood | 0.1 | 0.0007 |  | 1,463 | See |  |  | |
| 31 |
A*02:06 |  | Croatia | | 0.0030 |  | 150 | See |  |  | |
| 32 |
A*02:06 |  | Croatia pop 4 | | 0.0016 |  | 4,000 | See |  |  | |
| 33 |
A*02:06 |  | Cuba Caucasian | 0.0 | 0 |  | 70 | See |  |  | |
| 34 |
A*02:06 |  | Cuba Mixed Race | 0.0 | 0 |  | 42 | See |  |  | |
| 35 |
A*02:06 |  | Czech Republic | | 0.0050 |  | 106 | See |  |  | |
| 36 |
A*02:06 |  | Czech Republic NMDR | | 0.0021 |  | 5,099 | See |  |  | |
| 37 |
A*02:06 |  | Germany DKMS - Austria minority | | 0.0021 |  | 1,698 | See |  |  | |
| 38 |
A*02:06 |  | Germany DKMS - China minority | | 0.0543 |  | 1,282 | See |  |  | |
| 39 |
A*02:06 |  | Germany DKMS - Croatia minority | | 0.0015 |  | 2,057 | See |  |  | |
| 40 |
A*02:06 |  | Germany DKMS - France minority | | 0.0023 |  | 1,406 | See |  |  | |
| 41 |
A*02:06 |  | Germany DKMS - German donors | | 0.0019 |  | 3,456,066 | See |  |  |
|
| 42 |
A*02:06 |  | Germany DKMS - Greece minority | | 0.0005 |  | 1,894 | See |  |  | |
| 43 |
A*02:06 |  | Germany DKMS - Italy minority | | 0.0004 |  | 1,159 | See |  |  | |
| 44 |
A*02:06 |  | Germany DKMS - Netherlands minority | | 0.0022 |  | 1,374 | See |  |  | |
| 45 |
A*02:06 |  | Germany DKMS - Portugal minority | | 0.0006 |  | 1,176 | See |  |  | |
| 46 |
A*02:06 |  | Germany DKMS - Romania minority | | 0.0012 |  | 1,234 | See |  |  | |
| 47 |
A*02:06 |  | Germany DKMS - Turkey minority | | 0.0058 |  | 4,856 | See |  |  | |
| 48 |
A*02:06 |  | Germany DKMS - United Kingdom minority | | 0.0010 |  | 1,043 | See |  |  | |
| 49 |
A*02:06 |  | Germany pop 6 | | 0.0025 |  | 8,862 | See |  |  | |
| 50 |
A*02:06 |  | Germany pop 8 | | 0.0021 |  | 39,689 | See |  |  | |
| 51 |
A*02:06 |  | Ghana Ga-Adangbe | 0.8 | 0.0038 |  | 131 | See |  |  | |
| 52 |
A*02:06 |  | Guinea Bissau Balanta | | 0 |  | 48 | See |  |  | |
| 53 |
A*02:06 |  | Guinea Bissau Bijago | | 0.0220 |  | 23 | See |  |  | |
| 54 |
A*02:06 |  | Guinea Bissau Fula | | 0 |  | 31 | See |  |  | |
| 55 |
A*02:06 |  | Guinea Bissau Papel | | 0 |  | 25 | See |  |  | |
| 56 |
A*02:06 |  | Hong Kong Chinese | 9.3 | 0.0470 |  | 569 | See |  |  | |
| 57 |
A*02:06 |  | Hong Kong Chinese BMDR | | 0.0417 |  | 7,595 | See |  |  |
|
| 58 |
A*02:06 |  | Hong Kong Chinese cord blood registry | | 0.0388 |  | 3,892 | See |  |  |
|
| 59 |
A*02:06 |  | India Andhra Pradesh Golla | | 0.0280 |  | 111 | See |  |  | |
| 60 |
A*02:06 |  | India Central UCBB | 4.7 | 0.0237 |  | 4,204 | See |  |  |
|
| 61 |
A*02:06 |  | India Delhi pop 2 | 14.4 | 0.0770 |  | 90 | See |  |  | |
| 62 |
A*02:06 |  | India East UCBB | 2.8 | 0.0142 |  | 2,403 | See |  |  |
|
| 63 |
A*02:06 |  | India New Delhi | | 0.0300 |  | 71 | See |  |  | |
| 64 |
A*02:06 |  | India North pop 2 | | 0.0290 |  | 72 | See |  |  | |
| 65 |
A*02:06 |  | India North UCBB | 5.3 | 0.0262 |  | 5,849 | See |  |  |
|
| 66 |
A*02:06 |  | India Northeast UCBB | 3.7 | 0.0186 |  | 296 | See |  |  |
|
| 67 |
A*02:06 |  | India South UCBB | 3.3 | 0.0165 |  | 11,446 | See |  |  |
|
| 68 |
A*02:06 |  | India Tamil Nadu | | 0.0156 |  | 2,492 | See |  |  |
|
| 69 |
A*02:06 |  | India West UCBB | 3.9 | 0.0193 |  | 5,829 | See |  |  |
|
| 70 |
A*02:06 |  | Indonesia Java Western | 6.8 | 0.0350 |  | 236 | See |  |  | |
| 71 |
A*02:06 |  | Iran Baloch | | 0.0110 |  | 100 | See |  |  | |
| 72 |
A*02:06 |  | Ireland Northern | 0.0 | 0 |  | 1,000 | See |  |  | |
| 73 |
A*02:06 |  | Israel Arab pop 2 | | 0.0003 |  | 12,301 | See |  |  |
|
| 74 |
A*02:06 |  | Israel Argentina Jews | | 0.0009 |  | 4,307 | See |  |  |
|
| 75 |
A*02:06 |  | Israel Ashkenazi and Non Ashkenazi Jews | | 0.0040 |  | 146 | See |  |  | |
| 76 |
A*02:06 |  | Israel Ashkenazi Jews pop 3 | | 0.0014 |  | 4,625 | See |  |  |
|
| 77 |
A*02:06 |  | Israel Ethiopia Jews | | 0.0003 |  | 5,928 | See |  |  |
|
| 78 |
A*02:06 |  | Israel Georgia Jews | | 0.0002 |  | 4,471 | See |  |  |
|
| 79 |
A*02:06 |  | Israel Kavkazi Jews | | 0.0005 |  | 2,840 | See |  |  |
|
| 80 |
A*02:06 |  | Israel Morocco Jews | | 0.0000270 |  | 36,718 | See |  |  |
|
| 81 |
A*02:06 |  | Israel Poland Jews | | 0.0019 |  | 13,871 | See |  |  |
|
| 82 |
A*02:06 |  | Israel Tunisia Jews | | 0.0002 |  | 9,070 | See |  |  |
|
| 83 |
A*02:06 |  | Israel USA Jews | | 0.0012 |  | 6,058 | See |  |  |
|
| 84 |
A*02:06 |  | Israel USSR Jews | | 0.0014 |  | 45,681 | See |  |  |
|
| 85 |
A*02:06 |  | Israel YemenJews | | 0.0000640 |  | 15,542 | See |  |  |
|
| 86 |
A*02:06 |  | Italy Bergamo | 0.0 | 0 |  | 101 | See |  |  | |
| 87 |
A*02:06 |  | Italy North pop 3 | 0.0 | 0 |  | 97 | See |  |  | |
| 88 |
A*02:06 |  | Italy pop 5 | | 0.0030 |  | 975 | See |  |  | |
| 89 |
A*02:06 |  | Japan Central | | 0.0770 |  | 371 | See |  |  | |
| 90 |
A*02:06 |  | Japan Hokkaido Ainu | | 0.2000 |  | 50 | See |  |  | |
| 91 |
A*02:06 |  | Japan Okinawa Ryukyuan | | 0.1830 |  | 143 | See |  |  | |
| 92 |
A*02:06 |  | Japan pop 16 | | 0.0908 |  | 18,604 | See |  |  | |
| 93 |
A*02:06 |  | Japan pop 3 | | 0.0870 |  | 1,018 | See |  |  | |
| 94 |
A*02:06 |  | Japan pop 5 | | 0.0840 |  | 117 | See |  |  | |
| 95 |
A*02:06 |  | Kenya Luo | | 0 |  | 265 | See |  |  | |
| 96 |
A*02:06 |  | Kenya Nandi | | 0 |  | 240 | See |  |  | |
| 97 |
A*02:06 |  | Kosovo | 1.6 | 0.0081 |  | 124 | See |  |  |
|
| 98 |
A*02:06 |  | Malaysia Champa | 6.9 | 0.0340 |  | 29 | See |  |  |
|
| 99 |
A*02:06 |  | Malaysia Mandailing | 3.7 | 0.0190 |  | 27 | See |  |  |
|
| 100 |
A*02:06 |  | Malaysia Pahang Semai | 2.6 | 0.0130 |  | 38 | 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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