Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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A B C DRB1 DPA1 DPB1 DQA1 DQB1

Population:  Country:  Source of dataset : 
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Displaying 1 to 100 (from 158) records   Pages: 1 2 of 2  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*24-B*39-DRB1*11-DQB1*03:01  Mexico Quintana Roo Rural 3.000050
 2  A*01-B*39-DRB1*11-DQB1*03:01  Mexico Chiapas, Tuxtla Gutierrez 1.886852
 3  A*02-B*39-DRB1*11-DQB1*03:01  Mexico Veracruz, Coatzacoalcos 1.785755
 4  A*01-B*39-DRB1*11-DQB1*03:01  Mexico Veracruz, Orizaba 1.666760
 5  A*31-B*39-DRB1*11-DQB1*03:01  Mexico Nayarit Rural 1.562564
 6  A*24-B*39-DRB1*11-DQB1*03:01  Mexico Mexico City West 1.470633
 7  A*68-B*39-DRB1*11-DQB1*03:01  Mexico Veracruz, Poza Rica 1.111145
 8  A*23-B*39-DRB1*11-DQB1*03:01  Mexico Quintana Roo Rural 1.000050
 9  A*02-B*39-DRB1*11-DQB1*03:01  Mexico Oaxaca, Oaxaca city 0.6623151
 10  A*02-B*39-DRB1*11-DQB1*03:01  Mexico Guanajuato, Leon 0.641078
 11  A*03-B*39-DRB1*11-DQB1*03:01  Mexico Guanajuato, Leon 0.641078
 12  A*02-B*39-DRB1*11-DQB1*03:01  Mexico Hidalgo Rural 0.617381
 13  A*02:01-B*39:01-DRB1*11:04-DQB1*03:01  Mexico Veracruz Xalapa 0.595284
 14  A*24-B*39-DRB1*11-DQB1*03:01  Mexico Aguascalientes state 0.526395
 15  A*25:01-B*39:01-C*12:03-DRB1*11:01-DQA1*05:01-DQB1*03:01-DPB1*04:01  USA San Diego 0.5210496
 16  A*24-B*39-DRB1*11-DQB1*03:01  Mexico Sonora, Hermosillo 0.505199
 17  A*68-B*39-DRB1*11-DQB1*03:01  Mexico Baja Californa, Mexicali 0.5000100
 18  A*24:02:01-B*39:01:01-C*07:02:01-DRB1*11:01:01-DQA1*05:05:01-DQB1*03:01-DPA1*01:03:01-DPB1*15:01:01  Russian Federation Vologda Region 0.4202119
 19  A*01:01-B*39:01-C*06:02-DRB1*11:01-DQA1*05:05-DQB1*03:01  Kosovo 0.4030124
 20  A*26:01-B*39:01-C*12:03-DRB1*11:04-DQA1*01:02-DQB1*03:01  Kosovo 0.4030124
 21  A*33-B*39-DRB1*11-DQB1*03:01  Guatemala, Guatemala City Mixed Ancestry 0.3900127
 22  A*02-B*39-DRB1*11-DQB1*03:01  Mexico Tabasco Rural 0.3521142
 23  A*68-B*39-DRB1*11-DQB1*03:01  Mexico Sonora, Ciudad Obregón 0.3497143
 24  A*24:02:01:01-B*39:01:01-C*12:03:01-DRB1*11:04:01-DQB1*03:01  Russia Bashkortostan, Tatars 0.2604192
 25  A*24:02-B*39:01-C*03:03-DRB1*11:01-DQB1*03:01  Malaysia Peninsular Chinese 0.2577194
 26  A*24-B*39-DRB1*11-DQB1*03:01  Mexico Nuevo Leon Rural 0.2273439
 27  A*23:01-B*39:05-C*07:02-DRB1*11:02-DQA1*05:01-DQB1*03:01-DPB1*01:01  Nicaragua Managua 0.2165339
 28  A*68:01-B*39:05-C*07:02-DRB1*11:04-DQA1*03:01-DQB1*03:01-DPB1*04:02  Nicaragua Managua 0.2165339
 29  A*02-B*39-DRB1*11-DQB1*03:01  Ecuador Coast Mixed Ancestry 0.2101238
 30  A*24-B*39-DRB1*11-DQB1*03:01  Mexico Oaxaca Rural 0.2053485
 31  A*30:01-B*39:01-C*07:02-DRB1*11:01-DQB1*03:01  England North West 0.2000298
 32  A*68-B*39-DRB1*11-DQB1*03:01  Mexico Zacatecas Rural 0.1859266
 33  A*68-B*39-DRB1*11-DQB1*03:01  Mexico Veracruz Rural 0.1848539
 34  A*24-B*39-DRB1*11:01-DQA1*05:05-DQB1*03:01  Brazil Paraná Caucasian 0.1560641
 35  A*24-B*39-DRB1*11-DQB1*03:01  Mexico Durango Rural 0.1529326
 36  A*68:01-B*39:01-DRB1*11:01-DQB1*03:01  Mexico Mexico City Tlalpan 0.1515330
 37  A*32-B*39-DRB1*11-DQB1*03:01  Mexico Michoacan Rural 0.1433348
 38  A*02:01-B*39:01-C*06:02-DRB1*11:04-DQB1*03:01  Italy pop 5 0.1400975
 39  A*02:01-B*39:06-C*12:03-DRB1*11:01-DQB1*03:01  Italy pop 5 0.1400975
 40  A*26:01-B*39:01-C*12:03-DRB1*11:04-DQB1*03:01  Italy pop 5 0.1400975
 41  A*30:02-B*39:01-C*07:01-DRB1*11:01-DQB1*03:01  Italy pop 5 0.1400975
 42  A*31:01:02-B*39:01:01-C*04:01:01-DRB1*11:01:01-DQB1*03:01:01  India Kerala Malayalam speaking 0.1400356
 43  A*02:01-B*39:01-C*07:02-DRB1*11:04-DQB1*03:01  Germany DKMS - Italy minority 0.12901,159
 44  A*24:02-B*39:01-C*12:03-DRB1*11:01-DQB1*03:01  Germany DKMS - Italy minority 0.12901,159
 45  A*24:02-B*39:01-C*12:03-DRB1*11:04-DQB1*03:01-DPB1*03:01  Russia Karelia 0.11291,075
 46  A*02-B*39-DRB1*11-DQB1*03:01  Mexico Oaxaca Rural 0.1027485
 47  A*02-B*39-DRB1*11-DQB1*03:01  Mexico Veracruz Rural 0.0924539
 48  A*66:01-B*39:10-C*12:03-DRB1*11:02-DQB1*03:01  USA African American pop 4 0.08702,411
 49  A*11:02:01-B*39:01:01-C*07:02:01-DRB1*11:01:01-DQB1*03:01:01  China Zhejiang Han 0.08651,734
 50  A*01:01-B*39:01-C*06:02-DRB1*11:03-DQB1*03:01  Germany DKMS - Italy minority 0.08601,159
 51  A*02:01-B*39:01-C*12:03-DRB1*11:04-DQB1*03:01  Germany DKMS - Italy minority 0.08601,159
 52  A*02-B*39-DRB1*11-DQB1*03:01  Ecuador Mixed Ancestry 0.08531,173
 53  A*02-B*39-DRB1*11:04-DQA1*05:01-DQB1*03:01  Brazil Paraná Caucasian 0.0780641
 54  A*02-B*39-DRB1*11-DQB1*03:01  Mexico Puebla, Puebla city 0.07521,994
 55  A*24-B*39-DRB1*11-DQB1*03:01  Mexico Puebla, Puebla city 0.07521,994
 56  A*11:01:01-B*39:01:01-C*07:02:01-DRB1*11:01:01-DQB1*03:01:01  China Zhejiang Han 0.07211,734
 57  A*02:01-B*39:01-C*12:03-DRB1*11:03-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 58  A*26:01:01-B*39:01:01-C*12:03:01:01-DRB1*11:01:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.06621,510
 59  A*02-B*39-DRB1*11-DQB1*03:01  Ecuador Andes Mixed Ancestry 0.0607824
 60  A*68-B*39-DRB1*11-DQB1*03:01  Ecuador Andes Mixed Ancestry 0.0607824
 61  A*02-B*39-DRB1*11-DQB1*03:01  Mexico Tlaxcala Rural 0.0602830
 62  A*26-B*39-DRB1*11-DQB1*03:01  Mexico Tlaxcala Rural 0.0602830
 63  A*24-B*39-DRB1*11-DQB1*03:01  Mexico Puebla Rural 0.0600833
 64  A*02:01:01:01-B*39:01:01-C*12:03:01:01-DRB1*11:01:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.05941,510
 65  A*02:01:01-B*39:01:01-C*07:02:01-DRB1*11:01:01-DQB1*03:01:01  China Zhejiang Han 0.05771,734
 66  A*24:02-B*39:06-C*07:02-DRB1*11:01-DQB1*03:01-DPB1*23:01  Russia Karelia 0.05651,075
 67  A*02:01-B*39:01-C*12:03-DRB1*11:01-DQB1*03:01  Germany DKMS - Italy minority 0.05501,159
 68  A*11:01:01-B*39:08-C*07:04:01-DRB1*11:01-DQB1*03:01  Costa Rica Central Valley Mestizo (G) 0.0511221
 69  A*68-B*39-DRB1*11-DQB1*03:01  Mexico Puebla, Puebla city 0.05011,994
 70  A*01:01-B*39:06-C*07:02-DRB1*11:01-DQB1*03:01  USA Hispanic pop 2 0.04701,999
 71  A*02:01-B*39:01-C*12:03-DRB1*11:01-DQB1*03:01  USA Hispanic pop 2 0.04701,999
 72  A*02:06-B*39:01-C*07:02-DRB1*11:01-DQB1*03:01  USA Asian pop 2 0.04401,772
 73  A*11:01-B*39:01-C*04:03-DRB1*11:01-DQB1*03:01  USA Asian pop 2 0.04401,772
 74  A*11:01-B*39:01-C*07:02-DRB1*11:01-DQB1*03:01  USA Asian pop 2 0.04401,772
 75  A*24:02-B*39:01-C*07:02-DRB1*11:01-DQB1*03:01  USA Asian pop 2 0.04401,772
 76  A*66:01-B*39:10-C*12:03-DRB1*11:01-DQB1*03:01  USA African American pop 4 0.04402,411
 77  A*68:01-B*39:01-C*07:02-DRB1*11:02-DQB1*03:01  USA African American pop 4 0.04402,411
 78  A*24:02-B*39:01-C*07:02-DRB1*11:03-DQB1*03:01  Germany DKMS - Italy minority 0.04301,159
 79  A*25:01-B*39:01-C*12:03-DRB1*11:01-DQB1*03:01  Germany DKMS - Italy minority 0.04301,159
 80  A*32:01-B*39:24-C*07:01-DRB1*11:04-DQB1*03:01  Germany DKMS - Italy minority 0.04301,159
 81  A*68:01-B*39:01-C*12:03-DRB1*11:01-DQB1*03:01  Germany DKMS - Italy minority 0.04301,159
 82  A*68-B*39-DRB1*11-DQB1*03:01  Ecuador Mixed Ancestry 0.04261,173
 83  A*24-B*39-DRB1*11-DQB1*03:01  Mexico Jalisco, Guadalajara city 0.04191,189
 84  A*26-B*39-DRB1*11-DQB1*03:01  Mexico Jalisco, Guadalajara city 0.04191,189
 85  A*68-B*39-DRB1*11-DQB1*03:01  Mexico Jalisco, Guadalajara city 0.04191,189
 86  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.036023,595
 87  A*02:22-B*39:08-C*07:02-DRB1*11:01-DQB1*03:01  Colombia Bogotá Cord Blood 0.03421,463
 88  A*24:95-B*39:01-C*12:03-DRB1*11:04-DQB1*03:01  Colombia Bogotá Cord Blood 0.03421,463
 89  A*02:01-B*39:01-C*12:03-DRB1*11:01-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 90  A*24:02-B*39:06-C*07:02-DRB1*11:01-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 91  A*25:01-B*39:01-C*12:03-DRB1*11:01-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 92  A*26:08-B*39:01-C*12:03-DRB1*11:01-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 93  A*02:01:01-B*39:01:01-C*12:03:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.033323,595
 94  A*02:01:01:01-B*39:01:01-C*12:03:01:01-DRB1*11:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 95  A*24:02:01-B*39:01:01-C*12:03:01-DRB1*11:01:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 96  A*32:01:01-B*39:01:01-C*12:03:01:01-DRB1*11:04:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 97  A*01:01-B*39:01-C*07:02-DRB1*11:04-DQB1*03:01  Germany DKMS - Turkey minority 0.03104,856
 98  A*11:01-B*39:01-C*07:02-DRB1*11:01-DQA1*05:05-DQB1*03:01-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 99  A*24:02:01-B*39:01:01-C*12:03:01:01-DRB1*11:01:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.02721,510
 100  A*02:01-B*39:01-C*12:03-DRB1*11:01-DQB1*03:01  Germany DKMS - Turkey minority 0.02704,856

Notes:

* Haplotype Frequencies: Total number of copies of the haplotype in the population sample (Haplotypes / 2n) shown in percentages (%).
   Important: This field has been expanded to two decimals to better represent frequencies of large datasets (e.g. where sample size > 1000 individuals)
¹ Distribution - Shows the geographic distribution in overlaid maps of the complete haplotype (left icon) or the input alleles if low level resolution was entered (right icon).


Displaying 1 to 100 (from 158) records   Pages: 1 2 of 2  


   

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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