Allele Frequencies in World Populations

HLA » Haplotype Frequency Search

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Line Haplotype Population Frequency (%) Sample Size Location
1B*48:01-DRB1*08:02USA Alaska Yupik3.9025260_48_N_161_26_W
2A*24:02-B*48:01-DRB1*08:02-DQB1*04:02USA Alaska Yupik3.8025260_48_N_161_26_W
3A*24:02:01-B*48:01-C*08:01-DRB1*08:02:01-DQB1*04:02-DPB1*04:01Mexico Chihuahua Tarahumara3.404427_30_N_107_45_W
4A*02:06-B*48:01-DRB1*08:02Mexico Mixtec3.109723_57_N_103_29_W
5A*24:02-B*48:01-DRB1*08:02Mexico Oaxaca Zapotec3.009017_5_N_96_45_W
6A*02:06-B*48:01-DRB1*08:02Mexico Oaxaca Jamiltepec Mixtec2.609616_25_N_97_58_W
7A*02:01-B*48:01-DRB1*08:02-DQB1*04:02Peru Titikaka Lake Uros1.7910515_50_S_70_1_W
8B*48:01-C*08:01-DRB1*08:02-DQB1*04:02Mexico Mexico City Mestizo pop 21.7123419_26_N_99_8_W
9B*48:01-C*08:01-DRB1*08:02-DQB1*04:02Mexico Mexico City Mestizo population0.7014319_25_N_99_7_W
10A*02:01:01-B*48:01:01-C*08:01:01-DRB1*08:02:01-DQB1*04:02Mexico Hidalgo Mezquital Valley/ Otomi0.697220_28_N_99_13_W
11A*03:01:01-B*48:01:01-C*08:01:01-DRB1*08:02:01-DQB1*04:02Mexico Hidalgo Mezquital Valley/ Otomi0.697220_28_N_99_13_W
12A*68:01:01-B*48:01:01-C*07:01:01-DRB1*08:02:01-DQB1*04:02Mexico Hidalgo Mezquital Valley/ Otomi0.697220_28_N_99_13_W
13A*68:01:01-B*48:01:01-C*08:01:01-DRB1*08:02:01-DQB1*04:02Mexico Hidalgo Mezquital Valley/ Otomi0.697220_28_N_99_13_W
14A*68:03:01-B*48:01:01-C*04:01:01-DRB1*08:02:01-DQB1*04:02Mexico Hidalgo Mezquital Valley/ Otomi0.697220_28_N_99_13_W
15A*02:01-B*48:01-C*08:01-DRB1*08:02-DQB1*04:02Mexico Mexico City Mestizo pop 20.6423419_26_N_99_8_W
16A*02:06-B*48:01-C*08:01-DRB1*08:02-DQB1*04:02Mexico Mexico City Mestizo pop 20.6423419_26_N_99_8_W
17A*68:01-B*48:01-DRB1*08:02-DQB1*04:02Mexico Veracruz Xalapa0.608419_32_N_96_55_W
18B*48:01-C*08:03-DRB1*08:02-DQB1*04:02Mexico Mexico City Mestizo pop 20.4323419_26_N_99_8_W
19A*02:01-B*48:01-C*08:03-DRB1*08:02-DQB1*04:02Mexico Mexico City Mestizo pop 20.4323419_26_N_99_8_W
20A*02:01-B*48:01-C*08:01-DRB1*08:02-DQB1*04:02Mexico Mexico City Mestizo population0.3514319_25_N_99_7_W
21A*31:01-B*48:01-C*08:01-DRB1*08:02-DQB1*04:02Mexico Mexico City Mestizo population0.3514319_25_N_99_7_W
22B*48:01-C*08:03-DRB1*08:02-DQB1*04:02Mexico Mexico City Mestizo population0.3514319_25_N_99_7_W
23A*02:01-B*48:01-DRB1*08:02-DQB1*04:02Mexico Mexico City Tlalpan0.1533019_25_N_99_8_W
24A*24:02-B*48:01-DRB1*08:02-DQB1*04:02Mexico Mexico City Tlalpan0.1533019_25_N_99_8_W
25A*68:01-B*48:01-DRB1*08:02-DQB1*04:02Mexico Mexico City Tlalpan0.1533019_25_N_99_8_W
26A*68:03-B*48:01-DRB1*08:02-DQB1*04:02Mexico Mexico City Tlalpan0.1533019_25_N_99_8_W
27A*24:02-B*48:01-C*08:01-DRB1*08:02-DQB1*04:02Colombia Bogotá Cord Blood0.151,4634_39_N_73_52_W
28A*68:01-B*48:01-C*08:01-DRB1*08:02-DQB1*04:02USA Hispanic pop 20.141,99944_58_N_93_15_W
29A*24:02-B*48:01-C*12:03-DRB1*08:02Italy pop 50.1097545_28_N_9_11_E
30A*02:01-B*48:01-C*08:01-DRB1*08:02-DQB1*04:02USA Hispanic pop 20.091,99944_58_N_93_15_W
31A*02:01-B*48:01-C*08:01-DRB1*08:02-DQB1*04:02Colombia Bogotá Cord Blood0.091,4634_39_N_73_52_W
32A*68:02-B*48:01-C*08:01-DRB1*08:02-DQB1*04:02Colombia Bogotá Cord Blood0.071,4634_39_N_73_52_W
33A*30:02-B*48:01-C*08:01-DRB1*08:02-DQB1*04:02USA Hispanic pop 20.051,99944_58_N_93_15_W
34A*24:02-B*48:01-C*01:02-DRB1*08:02-DQB1*04:02Colombia Bogotá Cord Blood0.031,4634_39_N_73_52_W
35A*31:01-B*48:01-C*08:01-DRB1*08:02-DQB1*03:02Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria,0.034,33541_22_N_2_11_E
36A*02:01-B*48:01-C*03:03-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02Japan pop 170.033,07837_36_N_138_2_E
37A*02:01-B*48:01-C*08:03-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*02:01Japan pop 170.033,07837_36_N_138_2_E
38A*31:01-B*48:01-C*04:01-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02Japan pop 170.033,07837_36_N_138_2_E
39A*02:01:01-B*48:01:01-C*08:03:01-DRB1*08:02:01-DQB1*04:02:01China Zhejiang Han0.031,73427_2_N_118_1_E
40A*02:01-B*48:01-C*01:02-DRB1*08:02-DQB1*04:02USA Hispanic pop 20.021,99944_58_N_93_15_W
41A*02:06-B*48:01-C*01:02-DRB1*08:02-DQB1*04:02USA Hispanic pop 20.021,99944_58_N_93_15_W
42A*02:01-B*48:01-DRB1*08:02Israel Argentina Jews0.024,30732_8_N_34_52_E
43A*03:01-B*48:01-DRB1*08:02Israel Argentina Jews0.014,30732_8_N_34_52_E
44A*02:11-B*48:01-C*08:01-DRB1*08:02-DQB1*04:02India Central UCBB0.014,20427_1_N_81_19_E
45A*31:08-B*48:01-DRB1*08:02Israel Argentina Jews0.014,30732_8_N_34_52_E
46A*03:01-B*48:01-C*04:01-DRB1*08:02-DQB1*04:02USA Asian pop 20.011,77244_58_N_93_15_W
47A*26:02-B*48:01-C*04:01-DRB1*08:02-DQB1*04:02USA Asian pop 20.011,77244_58_N_93_15_W
48A*24:02-B*48:01-C*08:01-DRB1*08:02Japan pop 160.0118,60435_41_N_139_46_E
49A*31:01-B*48:01-C*03:03-DRB1*08:02Japan pop 160.0118,60435_41_N_139_46_E
50A*31:01-B*48:01-C*04:01-DRB1*08:02Japan pop 160.0118,60435_41_N_139_46_E
51A*02:11-B*48:01-C*08:01-DRB1*08:02-DQB1*04:02India West UCBB0.015,82919_11_N_73_3_E
52A*02:01-B*48:01-C*03:03-DRB1*08:02Japan pop 160.0118,60435_41_N_139_46_E
53A*02:06-B*48:01-C*08:01-DRB1*08:02Japan pop 160.0118,60435_41_N_139_46_E
54A*11:01-B*48:01-C*04:01-DRB1*08:02Japan pop 160.0118,60435_41_N_139_46_E
55A*24:02-B*48:01-C*03:03-DRB1*08:02Japan pop 160.0118,60435_41_N_139_46_E
56A*24:02-B*48:01-C*08:03-DRB1*08:02Poland DKMS0.0020,65352_8_N_19_23_E



   

Allele frequency net database (AFND) 2020 update: gold-standard data classification, open access genotype data and new query tools
Gonzalez-Galarza FF, McCabe A, Santos EJ, Jones J, Takeshita LY, Ortega-Rivera ND, Del Cid-Pavon GM, Ramsbottom K, Ghattaoraya GS, Alfirevic A, Middleton D and Jones AR Nucleic Acid Research 2020, 48:D783-8.
Liverpool, U.K.

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