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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*58:01 | | Argentina Rosario Toba | 1.2 | 0.0060 | | 86 | See | | | |
2 |
B*58:01 | | Australia Cape York Peninsula Aborigine | | 0.0100 | | 103 | See | | | |
3 |
B*58:01 | | Australia New South Wales Caucasian | | 0.0490 | | 134 | See | | | |
4 |
B*58:01 | | Australia Yuendumu Aborigine | | 0 | | 191 | See | | | |
5 |
B*58:01 | | Austria | 1.5 | 0.0080 | | 200 | See | | | |
6 |
B*58:01 | | Azores Central Islands | | 0.0090 | | 59 | See | | | |
7 |
B*58:01 | | Azores Oriental Islands | | 0.0260 | | 43 | See | | | |
8 |
B*58:01 | | Azores Terceira Island | | 0.0120 | | 130 | See | | | |
9 |
B*58:01 | | Brazil Belo Horizonte Caucasian | 4.2 | 0.0210 | | 95 | See | | | |
10 |
B*58:01 | | Brazil Mixed | | 0.0220 | | 108 | See | | | |
11 |
B*58:01 | | Brazil Vale do Ribeira Quilombos | 0.0210 | 0 | | 144 | See | | | |
12 |
B*58:01 | | Bulgaria | | 0.0180 | | 55 | See | | | |
13 |
B*58:01 | | Burkina Faso Fulani | | 0.0610 | | 49 | See | | | |
14 |
B*58:01 | | Burkina Faso Mossi | | 0.0570 | | 53 | See | | | |
15 |
B*58:01 | | Burkina Faso Rimaibe | | 0.0430 | | 47 | See | | | |
16 |
B*58:01 | | Cameroon Baka Pygmy | | 0.1500 | | 10 | See | | | |
17 |
B*58:01 | | Cameroon Bakola Pygmy | 8.0 | 0.0408 | | 50 | See | | | |
18 |
B*58:01 | | Cameroon Bamileke | | 0.0520 | | 77 | See | | | |
19 |
B*58:01 | | Cameroon Beti | | 0.0370 | | 174 | See | | | |
20 |
B*58:01 | | Cameroon Sawa | | 0.1150 | | 13 | See | | | |
21 |
B*58:01 | | Cameroon Yaounde | | 0.0540 | | 92 | See | | | |
22 |
B*58:01 | | Cape Verde Northwestern Islands | | 0.0320 | | 62 | See | | | |
23 |
B*58:01 | | Cape Verde Southeastern Islands | | 0.0400 | | 62 | See | | | |
24 |
B*58:01 | | Central African Republic Mbenzele Pygmy | 5.5 | 0.0278 | | 36 | See | | | |
25 |
B*58:01 | | Chile Mapuche | | 0.0154 | | 66 | See | | |
|
26 |
B*58:01 | | Chile Santiago Mixed | 1.0 | 0.0050 | | 70 | See | | | |
27 |
B*58:01 | | China Beijing | | 0.0230 | | 67 | See | | | |
28 |
B*58:01 | | China Beijing Shijiazhuang Tianjian Han | | 0.0600 | | 618 | See | | | |
29 |
B*58:01 | | China Canton Han | | 0.0890 | | 264 | See | | | |
30 |
B*58:01 | | China Guangdong Province Meizhou Han | | 0.1700 | | 100 | See | | | |
31 |
B*58:01 | | China Guangxi Region Maonan | | 0.0420 | | 108 | See | | | |
32 |
B*58:01 | | China Guangzhou | | 0.0850 | | 102 | See | | | |
33 |
B*58:01 | | China Guangzhou Han | | 0.0470 | | 106 | See | | | |
34 |
B*58:01 | | China Guizhou Province Bouyei | | 0.0830 | | 109 | See | | | |
35 |
B*58:01 | | China Guizhou Province Miao pop 2 | | 0.0480 | | 85 | See | | | |
36 |
B*58:01 | | China Guizhou Province Shui | | 0.0150 | | 153 | See | | | |
37 |
B*58:01 | | China Han HIV negative | | 0.0630 | | 72 | See | | | |
38 |
B*58:01 | | China Henan HIV negative | | 0.0630 | | 16 | See | | | |
39 |
B*58:01 | | China Hubei Han | 12.3 | 0.0616 | | 3,732 | See | | |
|
40 |
B*58:01 | | China Inner Mongolia Region | | 0.0880 | | 102 | See | | | |
41 |
B*58:01 | | China Jiangsu Han | | 0.0710 | | 3,238 | See | | | |
42 |
B*58:01 | | China Jiangsu Province Han | | 0.0714 | | 334 | See | | | |
43 |
B*58:01 | | China North Han | | 0.0290 | | 105 | See | | | |
44 |
B*58:01 | | China Qinghai Province Hui | | 0.0230 | | 110 | See | | | |
45 |
B*58:01 | | China Shanxi HIV negative | | 0.0230 | | 22 | See | | | |
46 |
B*58:01 | | China Sichuan HIV negative | | 0.0880 | | 34 | See | | | |
47 |
B*58:01 | | China South Han | | 0.0890 | | 284 | See | | | |
48 |
B*58:01 | | China Southwest Dai | | 0.0770 | | 124 | See | | | |
49 |
B*58:01 | | China Tibet Region Tibetan | | 0.0160 | | 158 | See | | | |
50 |
B*58:01 | | China Yunnan Bulang | | 0.0040 | | 116 | See | | | |
51 |
B*58:01 | | China Yunnan Hani | | 0.0270 | | 150 | See | | | |
52 |
B*58:01 | | China Yunnan Province Han | | 0.0740 | | 101 | See | | | |
53 |
B*58:01 | | China Yunnan Province Jinuo | | 0.0050 | | 109 | See | | | |
54 |
B*58:01 | | China Yunnan Province Lisu | | 0.0070 | | 111 | See | | | |
55 |
B*58:01 | | China Yunnan Province Nu | | 0.0190 | | 107 | See | | | |
56 |
B*58:01 | | China Yunnan Province Wa | | 0.0170 | | 119 | See | | | |
57 |
B*58:01 | | Colombia Bogotá Cord Blood | 3.3 | 0.0167 | | 1,463 | See | | | |
58 |
B*58:01 | | Croatia | | 0.0130 | | 150 | See | | | |
59 |
B*58:01 | | Croatia pop 4 | | 0.0105 | | 4,000 | See | | | |
60 |
B*58:01 | | Cuba Caucasian | 5.7 | 0.0290 | | 70 | See | | | |
61 |
B*58:01 | | Cuba Mixed Race | 9.5 | 0.0480 | | 42 | See | | | |
62 |
B*58:01 | | Czech Republic | | 0.0140 | | 106 | See | | | |
63 |
B*58:01 | | Czech Republic NMDR | | 0.0069 | | 5,099 | See | | | |
64 |
B*58:01 | | England North West | 1.0 | 0.0050 | | 298 | See | | | |
65 |
B*58:01 | | France Corsica Island | | 0.0450 | | 100 | See | | | |
66 |
B*58:01 | | France French Bone Marrow Donor Registry | | 0.0102 | | 42,623 | See | | | |
67 |
B*58:01 | | France Southeast | 3.1 | 0.0160 | | 130 | See | | | |
68 |
B*58:01 | | Gaza | 9.5 | 0.0476 | | 42 | See | | |
|
69 |
B*58:01 | | Georgia Tibilisi | | 0.0140 | | 109 | See | | | |
70 |
B*58:01 | | Germany DKMS - Austria minority | | 0.0118 | | 1,698 | See | | | |
71 |
B*58:01 | | Germany DKMS - Bosnia and Herzegovina minority | | 0.0097 | | 1,028 | See | | | |
72 |
B*58:01 | | Germany DKMS - China minority | | 0.0593 | | 1,282 | See | | | |
73 |
B*58:01 | | Germany DKMS - Croatia minority | | 0.0117 | | 2,057 | See | | | |
74 |
B*58:01 | | Germany DKMS - France minority | | 0.0125 | | 1,406 | See | | | |
75 |
B*58:01 | | Germany DKMS - German donors | | 0.0079 | | 3,456,066 | See | | |
|
76 |
B*58:01 | | Germany DKMS - Greece minority | | 0.0145 | | 1,894 | See | | | |
77 |
B*58:01 | | Germany DKMS - Italy minority | | 0.0198 | | 1,159 | See | | | |
78 |
B*58:01 | | Germany DKMS - Netherlands minority | | 0.0073 | | 1,374 | See | | | |
79 |
B*58:01 | | Germany DKMS - Portugal minority | | 0.0162 | | 1,176 | See | | | |
80 |
B*58:01 | | Germany DKMS - Romania minority | | 0.0097 | | 1,234 | See | | | |
81 |
B*58:01 | | Germany DKMS - Spain minority | | 0.0131 | | 1,107 | See | | | |
82 |
B*58:01 | | Germany DKMS - Turkey minority | | 0.0180 | | 4,856 | See | | | |
83 |
B*58:01 | | Germany DKMS - United Kingdom minority | | 0.0048 | | 1,043 | See | | | |
84 |
B*58:01 | | Germany pop 6 | | 0.0081 | | 8,862 | See | | | |
85 |
B*58:01 | | Germany pop 8 | | 0.0090 | | 39,689 | See | | | |
86 |
B*58:01 | | Ghana Ga-Adangbe | 7.6 | 0.0420 | | 131 | See | | | |
87 |
B*58:01 | | Greece pop 8 | 4.8 | 0.0241 | | 83 | See | | | |
88 |
B*58:01 | | Guatemala Mayan | | 0.0070 | | 132 | See | | | |
89 |
B*58:01 | | Guinea Bissau | | 0.0780 | | 65 | See | | | |
90 |
B*58:01 | | Hong Kong Chinese | 14.2 | 0.0730 | | 569 | See | | | |
91 |
B*58:01 | | Hong Kong Chinese BMDR | | 0.0887 | | 7,595 | See | | |
|
92 |
B*58:01 | | Hong Kong Chinese cord blood registry | | 0.0840 | | 3,892 | See | | |
|
93 |
B*58:01 | | India Andhra Pradesh Golla | | 0.0720 | | 111 | See | | | |
94 |
B*58:01 | | India Delhi pop 2 | 15.4 | 0.0880 | | 90 | See | | | |
95 |
B*58:01 | | India Khandesh Region Pawra | | 0.1500 | | 50 | See | | | |
96 |
B*58:01 | | India Mumbai Maratha | | 0.0740 | | 91 | See | | | |
97 |
B*58:01 | | India New Delhi | | 0.0680 | | 71 | See | | | |
98 |
B*58:01 | | India North pop 2 | | 0.0580 | | 72 | See | | | |
99 |
B*58:01 | | India Tamil Nadu | | 0.0366 | | 2,492 | See | | |
|
100 |
B*58:01 | | India West Bhil | | 0.0900 | | 50 | 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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