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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*26:08 |  | Belgium pop 3 | 0.2 | 0.0012 |  | 31,412 | See |  |  |
|
| 2 |
A*26:08 |  | Brazil Belo Horizonte Caucasian | 1.1 | 0.0050 |  | 95 | See |  |  | |
| 3 |
A*26:08 |  | Brazil Vale do Ribeira Quilombos | 0.0100 | 0 |  | 144 | See |  |  | |
| 4 |
A*26:08 |  | Bulgaria | | 0 |  | 55 | See |  |  | |
| 5 |
A*26:08 |  | Cape Verde Northwestern Islands | | 0.0080 |  | 62 | See |  |  | |
| 6 |
A*26:08 |  | Cape Verde Southeastern Islands | | 0 |  | 62 | See |  |  | |
| 7 |
A*26:08 |  | Chile Santiago Mixed | 1.0 | 0.0050 |  | 70 | See |  |  | |
| 8 |
A*26:08 |  | China North Han | | 0 |  | 105 | See |  |  | |
| 9 |
A*26:08 |  | China Tibet Region Tibetan | | 0 |  | 158 | See |  |  | |
| 10 |
A*26:08 |  | China Yunnan Province Lisu | | 0.0060 |  | 111 | See |  |  | |
| 11 |
A*26:08 |  | Costa Rica Central Valley Mestizo (G) | 0.4 (*) | 0.0020 (*) |  | 221 | See |  |  |
|
| 12 |
A*26:08 |  | Croatia | | 0 |  | 150 | See |  |  | |
| 13 |
A*26:08 |  | Croatia pop 4 | | 0.0006 |  | 4,000 | See |  |  | |
| 14 |
A*26:08 |  | Cuba Caucasian | 0.0 | 0 |  | 70 | See |  |  | |
| 15 |
A*26:08 |  | Cuba Mixed Race | 0.0 | 0 |  | 42 | See |  |  | |
| 16 |
A*26:08 |  | Czech Republic | | 0 |  | 106 | See |  |  | |
| 17 |
A*26:08 |  | Czech Republic NMDR | | 0.0006 |  | 5,099 | See |  |  | |
| 18 |
A*26:08 |  | Ecuador Amerindians | | 0.0079 |  | 63 | See |  |  |
|
| 19 |
A*26:08 |  | Germany DKMS - Austria minority | | 0.0003 |  | 1,698 | See |  |  | |
| 20 |
A*26:08 |  | Germany DKMS - Bosnia and Herzegovina minority | | 0.0005 |  | 1,028 | See |  |  | |
| 21 |
A*26:08 |  | Germany DKMS - Croatia minority | | 0.0010 |  | 2,057 | See |  |  | |
| 22 |
A*26:08 |  | Germany DKMS - France minority | | 0.0007 |  | 1,406 | See |  |  | |
| 23 |
A*26:08 |  | Germany DKMS - German donors | | 0.0008 |  | 3,456,066 | See |  |  |
|
| 24 |
A*26:08 |  | Germany DKMS - Greece minority | | 0.0008 |  | 1,894 | See |  |  | |
| 25 |
A*26:08 |  | Germany DKMS - Italy minority | | 0.0013 |  | 1,159 | See |  |  | |
| 26 |
A*26:08 |  | Germany DKMS - Netherlands minority | | 0.0004 |  | 1,374 | See |  |  | |
| 27 |
A*26:08 |  | Germany DKMS - Portugal minority | | 0.0009 |  | 1,176 | See |  |  | |
| 28 |
A*26:08 |  | Germany DKMS - Spain minority | | 0.0005 |  | 1,107 | See |  |  | |
| 29 |
A*26:08 |  | Germany DKMS - Turkey minority | | 0.0002 |  | 4,856 | See |  |  | |
| 30 |
A*26:08 |  | Germany DKMS - United Kingdom minority | | 0.0010 |  | 1,043 | See |  |  | |
| 31 |
A*26:08 |  | Germany pop 6 | | 0.0008 |  | 8,862 | See |  |  | |
| 32 |
A*26:08 |  | Germany pop 8 | | 0.0009 |  | 39,689 | See |  |  | |
| 33 |
A*26:08 |  | Guinea Bissau | | 0 |  | 65 | See |  |  | |
| 34 |
A*26:08 |  | Hong Kong Chinese | 0.0 | 0 |  | 569 | See |  |  | |
| 35 |
A*26:08 |  | India Khandesh Region Pawra | | 0 |  | 50 | See |  |  | |
| 36 |
A*26:08 |  | India Mumbai Maratha | | 0 |  | 91 | See |  |  | |
| 37 |
A*26:08 |  | India West Bhil | | 0 |  | 50 | See |  |  | |
| 38 |
A*26:08 |  | India West Coast Parsi | | 0.0100 |  | 50 | See |  |  | |
| 39 |
A*26:08 |  | Iran Yazd | | 0.0089 |  | 56 | See |  |  |
|
| 40 |
A*26:08 |  | Ireland Northern | 0.1 | 0.0010 |  | 1,000 | See |  |  | |
| 41 |
A*26:08 |  | Israel Argentina Jews | | 0.0001 |  | 4,307 | See |  |  |
|
| 42 |
A*26:08 |  | Israel Ashkenazi Jews pop 3 | | 0.0003 |  | 4,625 | See |  |  |
|
| 43 |
A*26:08 |  | Israel Bukhara Jews | | 0.0000720 |  | 2,317 | See |  |  |
|
| 44 |
A*26:08 |  | Israel Georgia Jews | | 0.0001 |  | 4,471 | See |  |  |
|
| 45 |
A*26:08 |  | Israel Iraq Jews | | 0.0000380 |  | 13,270 | See |  |  |
|
| 46 |
A*26:08 |  | Israel Libya Jews | | 0.0000450 |  | 3,739 | See |  |  |
|
| 47 |
A*26:08 |  | Israel Poland Jews | | 0.0000600 |  | 13,871 | See |  |  |
|
| 48 |
A*26:08 |  | Israel USA Jews | | 0.0000280 |  | 6,058 | See |  |  |
|
| 49 |
A*26:08 |  | Israel USSR Jews | | 0.0000660 |  | 45,681 | See |  |  |
|
| 50 |
A*26:08 |  | Israel YemenJews | | 0.0000210 |  | 15,542 | See |  |  |
|
| 51 |
A*26:08 |  | Italy North pop 3 | 3.8 | 0.0190 |  | 97 | See |  |  | |
| 52 |
A*26:08 |  | Italy pop 5 | | 0.0020 |  | 975 | See |  |  | |
| 53 |
A*26:08 |  | Japan Okinawa Ryukyuan | | 0.0040 |  | 143 | See |  |  | |
| 54 |
A*26:08 |  | Kenya Luo | | 0 |  | 265 | See |  |  | |
| 55 |
A*26:08 |  | Kenya Nandi | | 0 |  | 240 | See |  |  | |
| 56 |
A*26:08 |  | Mali Bandiagara | | 0 |  | 138 | See |  |  | |
| 57 |
A*26:08 |  | Mexico Mestizo | 0.0 | 0 |  | 41 | See |  |  | |
| 58 |
A*26:08 |  | Morocco Nador Metalsa pop 2 | | 0 |  | 73 | See |  |  | |
| 59 |
A*26:08 |  | Morocco Settat Chaouya | 0.0 | 0 |  | 98 | See |  |  | |
| 60 |
A*26:08 |  | Netherlands Leiden | | 0.0010 |  | 1,305 | See |  |  | |
| 61 |
A*26:08 |  | Oman | 0.0 | 0 |  | 118 | See |  |  | |
| 62 |
A*26:08 |  | Pakistan Baloch | | 0 |  | 66 | See |  |  | |
| 63 |
A*26:08 |  | Pakistan Brahui | | 0 |  | 104 | See |  |  | |
| 64 |
A*26:08 |  | Pakistan Burusho | | 0 |  | 92 | See |  |  | |
| 65 |
A*26:08 |  | Pakistan Kalash | | 0 |  | 69 | See |  |  | |
| 66 |
A*26:08 |  | Pakistan Karachi Parsi | | 0 |  | 91 | See |  |  | |
| 67 |
A*26:08 |  | Pakistan Mixed Pathan | | 0 |  | 100 | See |  |  | |
| 68 |
A*26:08 |  | Pakistan Mixed Sindhi | | 0 |  | 101 | See |  |  | |
| 69 |
A*26:08 |  | Philippines Ivatan | 0.0 | 0 |  | 50 | See |  |  | |
| 70 |
A*26:08 |  | Poland | | 0.0030 |  | 200 | See |  |  | |
| 71 |
A*26:08 |  | Poland BMR | 0.1 | 0.0007 |  | 23,595 | See |  |  |
|
| 72 |
A*26:08 |  | Poland DKMS | | 0.0007 |  | 20,653 | See |  |  | |
| 73 |
A*26:08 |  | Portugal Center | | 0 |  | 50 | See |  |  | |
| 74 |
A*26:08 |  | Portugal North | | 0.0110 |  | 46 | See |  |  | |
| 75 |
A*26:08 |  | Portugal South | | 0 |  | 49 | See |  |  | |
| 76 |
A*26:08 |  | Romania | 0.0 | 0 |  | 348 | See |  |  | |
| 77 |
A*26:08 |  | Russia Nizhny Novgorod, Russians | 0.1 | 0.0007 |  | 1,510 | See |  |  |
|
| 78 |
A*26:08 |  | Saudi Arabia pop 6 (G) | | 0.0000170 (*) |  | 28,927 | See |  |  | |
| 79 |
A*26:08 |  | Singapore Chinese | 0.0 | 0 |  | 149 | See |  |  | |
| 80 |
A*26:08 |  | South Africa Natal Zulu | 0.0 | 0 |  | 100 | See |  |  | |
| 81 |
A*26:08 |  | South Korea pop 3 | | 0 |  | 485 | See |  |  | |
| 82 |
A*26:08 |  | Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, | 0.4 | 0.0017 |  | 4,335 | See |  |  |
|
| 83 |
A*26:08 |  | Sweden Northern Sami | | 0.0030 |  | 154 | See |  |  | |
| 84 |
A*26:08 |  | Switzerland Aargau-Solothurn | | 0.0082 |  | 1,838 | See |  |  | |
| 85 |
A*26:08 |  | Switzerland Basel | | 0.0067 |  | 1,888 | See |  |  | |
| 86 |
A*26:08 |  | Switzerland Bern | | 0.0041 |  | 3,545 | See |  |  | |
| 87 |
A*26:08 |  | Switzerland Geneva pop 2 | | 0.0143 |  | 1,267 | See |  |  | |
| 88 |
A*26:08 |  | Switzerland Graubunden | | 0.0037 |  | 759 | See |  |  | |
| 89 |
A*26:08 |  | Switzerland Lausanne | | 0.0045 |  | 993 | See |  |  | |
| 90 |
A*26:08 |  | Switzerland Lugano | | 0 |  | 1,169 | See |  |  | |
| 91 |
A*26:08 |  | Switzerland Luzern | | 0 |  | 1,553 | See |  |  | |
| 92 |
A*26:08 |  | Switzerland Sion | | 0 |  | 832 | See |  |  | |
| 93 |
A*26:08 |  | Switzerland St Gallen | | 0 |  | 2,113 | See |  |  | |
| 94 |
A*26:08 |  | Switzerland Zurich | | 0.0024 |  | 4,875 | See |  |  | |
| 95 |
A*26:08 |  | Taiwan Ami | 0.0 | 0 |  | 98 | See |  |  | |
| 96 |
A*26:08 |  | Taiwan Atayal | 0.0 | 0 |  | 106 | See |  |  | |
| 97 |
A*26:08 |  | Taiwan Bunun | 0.0 | 0 |  | 101 | See |  |  | |
| 98 |
A*26:08 |  | Taiwan Hakka | 0.0 | 0 |  | 55 | See |  |  | |
| 99 |
A*26:08 |  | Taiwan Minnan pop 1 | 0.0 | 0 |  | 102 | See |  |  | |
| 100 |
A*26:08 |  | Taiwan Paiwan | 0.0 | 0 |  | 51 | 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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