Please specify your search by selecting options from boxes. Then, click "Search" to find HLA allele frequencies
that match your criteria. Remember at least one option must be selected.
Line |
Allele |
Population |
% of individuals
that have the allele |
Allele
Frequency
(in_decimals) |
Sample
Size |
IMGT/HLA¹
Database |
Distribution² |
Haplotype³
Association |
Notesª |
1 |
A*11:01 | | American Samoa | | 0.1600 | | 51 | See | | | |
2 |
A*11:01 | | Argentina Rosario Toba | 1.2 | 0.0060 | | 86 | See | | | |
3 |
A*11:01 | | Armenia combined Regions | | 0.0800 | | 100 | See | | | |
4 |
A*11:01 | | Australia Cape York Peninsula Aborigine | | 0.1800 | | 103 | See | | | |
5 |
A*11:01 | | Australia Groote Eylandt Aborigine | | 0.2400 | | 75 | See | | | |
6 |
A*11:01 | | Australia Kimberly Aborigine | | 0.0970 | | 41 | See | | | |
7 |
A*11:01 | | Australia New South Wales Caucasian | | 0.0670 | | 134 | See | | | |
8 |
A*11:01 | | Australia Yuendumu Aborigine | | 0.0760 | | 191 | See | | | |
9 |
A*11:01 | | Austria | 6.5 | 0.0320 | | 200 | See | | | |
10 |
A*11:01 | | Azores Central Islands | | 0.0540 | | 59 | See | | | |
11 |
A*11:01 | | Azores Oriental Islands | | 0.0380 | | 43 | See | | | |
12 |
A*11:01 | | Azores Terceira Island | | 0.0700 | | 130 | See | | | |
13 |
A*11:01 | | Belgium | 9.4 | 0.0470 | | 99 | See | | | |
14 |
A*11:01 | | Brazil Puyanawa | 10.7 | 0.0530 | | 150 | See | | |
|
15 |
A*11:01 | | Brazil Belo Horizonte Caucasian | 4.2 | 0.0260 | | 95 | See | | | |
16 |
A*11:01 | | Brazil Mixed | | 0.0610 | | 108 | See | | | |
17 |
A*11:01 | | Brazil Vale do Ribeira Quilombos | 0.0310 | 0 | | 144 | See | | | |
18 |
A*11:01 | | Bulgaria Romani | | 0.2080 | | 13 | See | | | |
19 |
A*11:01 | | Chile Easter Island | | 0.3810 | | 21 | See | | | |
20 |
A*11:01 | | Chile Mapuche | | 0.0154 | | 66 | See | | |
|
21 |
A*11:01 | | Chile Santiago Mixed | 2.0 | 0.0100 | | 70 | See | | | |
22 |
A*11:01 | | China Beijing | | 0.1640 | | 67 | See | | | |
23 |
A*11:01 | | China Beijing Shijiazhuang Tianjian Han | | 0.2020 | | 618 | See | | | |
24 |
A*11:01 | | China Canton Han | | 0.2670 | | 264 | See | | | |
25 |
A*11:01 | | China Guangxi Region Maonan | | 0.3520 | | 108 | See | | | |
26 |
A*11:01 | | China Guangzhou | | 0.3380 | | 102 | See | | | |
27 |
A*11:01 | | China Guizhou Province Bouyei | | 0.3140 | | 109 | See | | | |
28 |
A*11:01 | | China Guizhou Province Miao pop 2 | | 0.3590 | | 85 | See | | | |
29 |
A*11:01 | | China Guizhou Province Shui | | 0.2950 | | 153 | See | | | |
30 |
A*11:01 | | China Han HIV negative | | 0.0940 | | 72 | See | | | |
31 |
A*11:01 | | China Henan HIV negative | | 0.0940 | | 16 | See | | | |
32 |
A*11:01 | | China Hubei Han | 52.3 | 0.2617 | | 3,732 | See | | |
|
33 |
A*11:01 | | China Inner Mongolia Region | | 0.1620 | | 102 | See | | | |
34 |
A*11:01 | | China Jiangsu Han | | 0.1650 | | 3,238 | See | | | |
35 |
A*11:01 | | China Jiangsu Province Han | | 0.1777 | | 334 | See | | | |
36 |
A*11:01 | | China North Han | | 0 | | 105 | See | | | |
37 |
A*11:01 | | China Qinghai Province Hui | | 0.1590 | | 110 | See | | | |
38 |
A*11:01 | | China Shanxi HIV negative | | 0.1820 | | 22 | See | | | |
39 |
A*11:01 | | China Sichuan HIV negative | | 0.1760 | | 34 | See | | | |
40 |
A*11:01 | | China South Han | | 0.2770 | | 284 | See | | | |
41 |
A*11:01 | | China Southwest Dai | | 0.3910 | | 124 | See | | | |
42 |
A*11:01 | | China Uyghur HIV negative | | 0.1050 | | 19 | See | | | |
43 |
A*11:01 | | China Yunnan Bulang | | 0.5430 | | 116 | See | | | |
44 |
A*11:01 | | China Yunnan Hani | | 0.6130 | | 150 | See | | | |
45 |
A*11:01 | | China Yunnan Province Han | | 0.3170 | | 101 | See | | | |
46 |
A*11:01 | | Colombia Bogotá Cord Blood | 8.5 | 0.0427 | | 1,463 | See | | | |
47 |
A*11:01 | | Colombia North Wiwa El Encanto | | 0.0192 | | 52 | See | | |
|
48 |
A*11:01 | | Croatia | | 0.0400 | | 150 | See | | | |
49 |
A*11:01 | | Croatia pop 4 | | 0.0691 | | 4,000 | See | | | |
50 |
A*11:01 | | Cuba Caucasian | 10.0 | 0.0570 | | 70 | See | | | |
51 |
A*11:01 | | Cuba Mixed Race | 0.0 | 0 | | 42 | See | | | |
52 |
A*11:01 | | Czech Republic | | 0.0330 | | 106 | See | | | |
53 |
A*11:01 | | Czech Republic NMDR | | 0.0566 | | 5,099 | See | | | |
54 |
A*11:01 | | Ecuador Amerindians | | 0.0476 | | 63 | See | | |
|
55 |
A*11:01 | | England North West | 13.1 | 0.0700 | | 298 | See | | | |
56 |
A*11:01 | | Finland | | 0.0500 | | 91 | See | | | |
57 |
A*11:01 | | France French Bone Marrow Donor Registry | | 0.0500 | | 42,623 | See | | | |
58 |
A*11:01 | | France Southeast | 8.5 | 0.0430 | | 130 | See | | | |
59 |
A*11:01 | | Gaza | 14.3 | 0.0714 | | 42 | See | | |
|
60 |
A*11:01 | | Georgia Svaneti Region Svan | | 0.1250 | | 80 | See | | | |
61 |
A*11:01 | | Georgia Tibilisi | | 0.0620 | | 109 | See | | | |
62 |
A*11:01 | | Georgia Tibilisi Kurd | | 0.1000 | | 31 | See | | | |
63 |
A*11:01 | | Germany DKMS - Austria minority | | 0.0558 | | 1,698 | See | | | |
64 |
A*11:01 | | Germany DKMS - Bosnia and Herzegovina minority | | 0.0627 | | 1,028 | See | | | |
65 |
A*11:01 | | Germany DKMS - China minority | | 0.1929 | | 1,282 | See | | | |
66 |
A*11:01 | | Germany DKMS - Croatia minority | | 0.0756 | | 2,057 | See | | | |
67 |
A*11:01 | | Germany DKMS - France minority | | 0.0594 | | 1,406 | See | | | |
68 |
A*11:01 | | Germany DKMS - German donors | | 0.0528 | | 3,456,066 | See | | |
|
69 |
A*11:01 | | Germany DKMS - Greece minority | | 0.0628 | | 1,894 | See | | | |
70 |
A*11:01 | | Germany DKMS - Italy minority | | 0.0542 | | 1,159 | See | | | |
71 |
A*11:01 | | Germany DKMS - Netherlands minority | | 0.0510 | | 1,374 | See | | | |
72 |
A*11:01 | | Germany DKMS - Portugal minority | | 0.0689 | | 1,176 | See | | | |
73 |
A*11:01 | | Germany DKMS - Romania minority | | 0.0584 | | 1,234 | See | | | |
74 |
A*11:01 | | Germany DKMS - Spain minority | | 0.0628 | | 1,107 | See | | | |
75 |
A*11:01 | | Germany DKMS - Turkey minority | | 0.0748 | | 4,856 | See | | | |
76 |
A*11:01 | | Germany DKMS - United Kingdom minority | | 0.0647 | | 1,043 | See | | | |
77 |
A*11:01 | | Germany pop 6 | | 0.0507 | | 8,862 | See | | | |
78 |
A*11:01 | | Germany pop 8 | | 0.0563 | | 39,689 | See | | | |
79 |
A*11:01 | | Greece pop 6 | | 0.0682 | | 242 | See | | | |
80 |
A*11:01 | | Greece pop 8 | 12.1 | 0.0723 | | 83 | See | | | |
81 |
A*11:01 | | Hong Kong Chinese | 48.8 | 0.2870 | | 569 | See | | | |
82 |
A*11:01 | | Hong Kong Chinese BMDR | | 0.2968 | | 7,595 | See | | |
|
83 |
A*11:01 | | Hong Kong Chinese cord blood registry | | 0.2978 | | 3,892 | See | | |
|
84 |
A*11:01 | | India Andhra Pradesh Golla | | 0.1190 | | 111 | See | | | |
85 |
A*11:01 | | India Central UCBB | 30.2 | 0.1509 | | 4,204 | See | | |
|
86 |
A*11:01 | | India Delhi pop 2 | 18.9 | 0.0940 | | 90 | See | | | |
87 |
A*11:01 | | India East UCBB | 33.0 | 0.1825 | | 2,403 | See | | |
|
88 |
A*11:01 | | India Mumbai Maratha | | 0.1230 | | 91 | See | | | |
89 |
A*11:01 | | India New Delhi | | 0.2350 | | 71 | See | | | |
90 |
A*11:01 | | India North pop 2 | | 0.1250 | | 72 | See | | | |
91 |
A*11:01 | | India North UCBB | 29.0 | 0.1588 | | 5,849 | See | | |
|
92 |
A*11:01 | | India Northeast UCBB | 54.7 | 0.3226 | | 296 | See | | |
|
93 |
A*11:01 | | India South UCBB | 26.8 | 0.1453 | | 11,446 | See | | |
|
94 |
A*11:01 | | India Tamil Nadu | | 0.1359 | | 2,492 | See | | |
|
95 |
A*11:01 | | India West UCBB | 27.4 | 0.1481 | | 5,829 | See | | |
|
96 |
A*11:01 | | Indonesia Java Western | 30.1 | 0.1640 | | 236 | See | | | |
97 |
A*11:01 | | Iran Gorgan | | 0.0550 | | 64 | See | | |
|
98 |
A*11:01 | | Iran Kurd pop 2 | | 0.0830 | | 60 | See | | |
|
99 |
A*11:01 | | Iran Saqqez-Baneh Kurds | | 0.0833 | | 60 | See | | |
|
100 |
A*11:01 | | Iran Tabriz Azeris | | 0.0619 | | 97 | 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.
Displaying 1 to 100
(from 386) records |
|
Pages: |
|
|
1 2 3 4 of 4
|
|
|
|
|
|
|