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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 |
B*46:01 | | Brazil Belo Horizonte Caucasian | 0.0 | 0 | | 95 | See | | | |
2 |
B*46:01 | | Bulgaria | | 0 | | 55 | See | | | |
3 |
B*46:01 | | Burkina Faso Fulani | | 0 | | 49 | See | | | |
4 |
B*46:01 | | Burkina Faso Mossi | | 0 | | 53 | See | | | |
5 |
B*46:01 | | Burkina Faso Rimaibe | | 0 | | 47 | See | | | |
6 |
B*46:01 | | China Beijing | | 0.0680 | | 67 | See | | | |
7 |
B*46:01 | | China Beijing Shijiazhuang Tianjian Han | | 0.0960 | | 618 | See | | | |
8 |
B*46:01 | | China Canton Han | | 0.1190 | | 264 | See | | | |
9 |
B*46:01 | | China Guangdong Province Meizhou Han | | 0.1000 | | 100 | See | | | |
10 |
B*46:01 | | China Guangxi Region Maonan | | 0.1340 | | 108 | See | | | |
11 |
B*46:01 | | China Guangzhou | | 0.1550 | | 102 | See | | | |
12 |
B*46:01 | | China Guangzhou Han | | 0.0940 | | 106 | See | | | |
13 |
B*46:01 | | China Guizhou Province Bouyei | | 0.1910 | | 109 | See | | | |
14 |
B*46:01 | | China Guizhou Province Miao pop 2 | | 0.2290 | | 85 | See | | | |
15 |
B*46:01 | | China Guizhou Province Shui | | 0.2360 | | 153 | See | | | |
16 |
B*46:01 | | China Han HIV negative | | 0.0630 | | 72 | See | | | |
17 |
B*46:01 | | China Henan HIV negative | | 0.0630 | | 16 | See | | | |
18 |
B*46:01 | | China Hubei Han | 30.0 | 0.1502 | | 3,732 | See | | |
|
19 |
B*46:01 | | China Inner Mongolia Region | | 0.0200 | | 102 | See | | | |
20 |
B*46:01 | | China Jiangsu Han | | 0.0890 | | 3,238 | See | | | |
21 |
B*46:01 | | China Jiangsu Province Han | | 0.0768 | | 334 | See | | | |
22 |
B*46:01 | | China North Han | | 0.0570 | | 105 | See | | | |
23 |
B*46:01 | | China Qinghai Province Hui | | 0.0590 | | 110 | See | | | |
24 |
B*46:01 | | China Shanxi HIV negative | | 0.0680 | | 22 | See | | | |
25 |
B*46:01 | | China Sichuan HIV negative | | 0.1760 | | 34 | See | | | |
26 |
B*46:01 | | China South Han | | 0.1150 | | 284 | See | | | |
27 |
B*46:01 | | China Southwest Dai | | 0.2540 | | 124 | See | | | |
28 |
B*46:01 | | China Tibet Region Tibetan | | 0.0130 | | 158 | See | | | |
29 |
B*46:01 | | China Uyghur HIV negative | | 0.0260 | | 19 | See | | | |
30 |
B*46:01 | | China Yunnan Bulang | | 0.0090 | | 116 | See | | | |
31 |
B*46:01 | | China Yunnan Hani | | 0.1630 | | 150 | See | | | |
32 |
B*46:01 | | China Yunnan Province Han | | 0.1980 | | 101 | See | | | |
33 |
B*46:01 | | China Yunnan Province Jinuo | | 0.1470 | | 109 | See | | | |
34 |
B*46:01 | | China Yunnan Province Lisu | | 0.0720 | | 111 | See | | | |
35 |
B*46:01 | | China Yunnan Province Nu | | 0.0900 | | 107 | See | | | |
36 |
B*46:01 | | China Yunnan Province Wa | | 0.0040 | | 119 | See | | | |
37 |
B*46:01 | | Cuba Caucasian | 1.4 | 0.0070 | | 70 | See | | | |
38 |
B*46:01 | | Cuba Mixed Race | 0.0 | 0 | | 42 | See | | | |
39 |
B*46:01 | | Czech Republic | | 0 | | 106 | See | | | |
40 |
B*46:01 | | Czech Republic NMDR | | 0.0004 | | 5,099 | See | | | |
41 |
B*46:01 | | France Grenoble, Nantes and Rennes | | 0 | | 6,094 | See | | | |
42 |
B*46:01 | | Germany DKMS - Austria minority | | 0.0003 | | 1,698 | See | | | |
43 |
B*46:01 | | Germany DKMS - China minority | | 0.1034 | | 1,282 | See | | | |
44 |
B*46:01 | | Germany DKMS - German donors | | 0.0002 | | 3,456,066 | See | | |
|
45 |
B*46:01 | | Germany DKMS - Portugal minority | | 0.0009 | | 1,176 | See | | | |
46 |
B*46:01 | | Germany DKMS - Romania minority | | 0.0008 | | 1,234 | See | | | |
47 |
B*46:01 | | Germany DKMS - Turkey minority | | 0.0024 | | 4,856 | See | | | |
48 |
B*46:01 | | Germany pop 6 | | 0.0002 | | 8,862 | See | | | |
49 |
B*46:01 | | Germany pop 8 | | 0.0004 | | 39,689 | See | | | |
50 |
B*46:01 | | Hong Kong Chinese | 30.4 | 0.1630 | | 569 | See | | | |
51 |
B*46:01 | | Hong Kong Chinese BMDR | | 0.1485 | | 7,595 | See | | |
|
52 |
B*46:01 | | Hong Kong Chinese cord blood registry | | 0.1403 | | 3,892 | See | | |
|
53 |
B*46:01 | | Iran Tabriz Azeris | | 0.0052 | | 97 | See | | |
|
54 |
B*46:01 | | Ireland Northern | 0.0 | 0 | | 1,000 | See | | | |
55 |
B*46:01 | | Israel Kavkazi Jews | | 0.0002 | | 2,840 | See | | |
|
56 |
B*46:01 | | Israel USA Jews | | 0.0000030 | | 6,058 | See | | |
|
57 |
B*46:01 | | Israel USSR Jews | | 0.0006 | | 45,681 | See | | |
|
58 |
B*46:01 | | Japan Central | | 0.0360 | | 371 | See | | | |
59 |
B*46:01 | | Japan Hokkaido Ainu | | 0.0100 | | 50 | See | | | |
60 |
B*46:01 | | Japan pop 16 | | 0.0477 | | 18,604 | See | | | |
61 |
B*46:01 | | Japan pop 3 | | 0.0500 | | 1,018 | See | | | |
62 |
B*46:01 | | Japan pop 5 | | 0.0610 | | 117 | See | | | |
63 |
B*46:01 | | Malaysia Champa | 10.3 | 0.0520 | | 29 | See | | |
|
64 |
B*46:01 | | Malaysia Jelebu Temuan | | 0.0420 | | 25 | See | | | |
65 |
B*46:01 | | Malaysia Kelantan | 21.4 | 0.1070 | | 28 | See | | |
|
66 |
B*46:01 | | Malaysia Peninsular Chinese | 21.7 | 0.1211 | | 194 | See | | |
|
67 |
B*46:01 | | Malaysia Peninsular Malay | 4.9 | 0.0252 | | 951 | See | | |
|
68 |
B*46:01 | | Malaysia Perak Grik Jehai | | 0.0200 | | 25 | See | | | |
69 |
B*46:01 | | Malaysia Sarawak Bau Bidayuh | | 0.0200 | | 25 | See | | | |
70 |
B*46:01 | | Mexico Mestizo | 0.0 | 0 | | 41 | See | | | |
71 |
B*46:01 | | Mexico Mexico City Tlalpan | 0.3 | 0.0015 | | 330 | See | | |
|
72 |
B*46:01 | | Morocco Nador Metalsa pop 2 | | 0 | | 73 | See | | | |
73 |
B*46:01 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
74 |
B*46:01 | | Netherlands Leiden | | 0 | | 1,305 | See | | | |
75 |
B*46:01 | | Oman | 0.0 | 0 | | 118 | See | | | |
76 |
B*46:01 | | Panama | | 0.0011 | | 462 | See | | |
|
77 |
B*46:01 | | Philippines Ivatan | 0.0 | 0 | | 50 | See | | | |
78 |
B*46:01 | | Poland DKMS | | 0.0005 | | 20,653 | See | | | |
79 |
B*46:01 | | Romania | 0.3 | 0.0010 | | 348 | See | | | |
80 |
B*46:01 | | Russia Bering Island Aleuts | | 0.0048 | | 104 | See | | |
|
81 |
B*46:01 | | Russia Tuva pop 2 | | 0.0140 | | 169 | See | | | |
82 |
B*46:01 | | Singapore Chinese | 23.5 | 0.1340 | | 149 | See | | | |
83 |
B*46:01 | | Singapore Chinese Han | | 0.1450 | | 94 | See | | | |
84 |
B*46:01 | | Singapore Javaneses | | 0.0200 | | 51 | See | | | |
85 |
B*46:01 | | Singapore Riau Malay | | 0.0150 | | 132 | See | | | |
86 |
B*46:01 | | Singapore SGVP Chinese CHS | | 0.0970 | | 96 | See | | |
|
87 |
B*46:01 | | Singapore SGVP Malay MAS | | 0.0120 | | 89 | See | | |
|
88 |
B*46:01 | | Singapore SGVP. Indian INS | | 0 | | 86 | See | | |
|
89 |
B*46:01 | | Singapore Thai | | 0.1720 | | 100 | See | | | |
90 |
B*46:01 | | South Africa Natal Zulu | 0.0 | 0 | | 100 | See | | | |
91 |
B*46:01 | | South Korea pop 10 | | 0.0474 | | 4,128 | See | | | |
92 |
B*46:01 | | South Korea pop 3 | | 0.0440 | | 485 | See | | | |
93 |
B*46:01 | | Switzerland Aargau-Solothurn | | 0.0040 | | 1,838 | See | | | |
94 |
B*46:01 | | Switzerland Basel | | 0 | | 1,888 | See | | | |
95 |
B*46:01 | | Switzerland Bern | | 0.0006 | | 3,545 | See | | | |
96 |
B*46:01 | | Switzerland Geneva pop 2 | | 0 | | 1,267 | See | | | |
97 |
B*46:01 | | Switzerland Graubunden | | 0.0010 | | 759 | See | | | |
98 |
B*46:01 | | Switzerland Lausanne | | 0.0006 | | 993 | See | | | |
99 |
B*46:01 | | Switzerland Lugano | | 0 | | 1,169 | See | | | |
100 |
B*46:01 | | Switzerland Luzern | | 0 | | 1,553 | 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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