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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Sample Size:      Sample Year:     Loci Tested: 
Displaying 1 to 100 (from 204) records   Pages: 1 2 3 of 3  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*01-B*51-DRB1*03:01-DQB1*02:01  Colombia San Basilio de Palenque 3.571042
 2  A*02-B*51-DRB1*03:01-DQB1*02  Mexico Queretaro Rural 2.325643
 3  A*26-B*51-DRB1*03:01-DQB1*02  Mexico Baja California Rural 2.000050
 4  A*02:01-B*51:01-C*16:02-DRB1*03:01-DQA1*05:01-DQB1*02:01  United Arab Emirates Abu Dhabi 1.920052
 5  A*02-B*51-DRB1*03:01-DQB1*02:01  Tunisia pop 3 1.8000104
 6  A*01-B*51-DRB1*03:01-DQB1*02  Mexico Veracruz, Orizaba 1.666760
 7  A*01:01-B*51:01-DRB1*03:01-DQB1*02:01  Tunisia Gabes 1.570095
 8  A*02:01-B*51:01-DRB1*03:01-DQB1*02:01  Tunisia Gabes 1.570095
 9  A*31:01-B*51:01-C*16:01-DRB1*03:01-DQA1*05:01-DQB1*02:01  Brazil Puyanawa 1.3333150
 10  A*02:05-B*51:01-C*16:01-DRB1*03:01-DQB1*02:01-DPB1*13:01  Tanzania Maasai 1.1182336
 11  A*02:01-B*51:01-C*15:04-DRB1*03:01-DQA1*05:01-DQB1*02:01  United Arab Emirates Abu Dhabi 0.960052
 12  A*02-B*51-DRB1*03:01-DQB1*02:01  Mexico Sinaloa Capomos Mayo Yoremes 0.833360
 13  A*02-B*51-DRB1*03:01-DQB1*02  Mexico Baja California, La Paz 0.666775
 14  A*24-B*51-DRB1*03:01-DQB1*02  Mexico Guanajuato, Leon 0.641078
 15  A*02:01:01-B*51:01:01-C*02:02:02-DRB1*03:01:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*02:01:19  Brazil Rio de Janeiro Parda 0.5882170
 16  A*30:02:01-B*51:01:01-C*05:01:01-DRB1*03:01:01-DQB1*02:01:01-DPA1*02:01:01-DPB1*14:01:01  Brazil Rio de Janeiro Parda 0.5882170
 17  A*02:01-B*51:08-DRB1*03:01-DQB1*02:01  Iran Tabriz Azeris 0.515597
 18  A*02-B*51-DRB1*03:01-DQB1*02  Mexico Baja Californa, Mexicali 0.5000100
 19  A*31:04-B*51:01-C*16:01-DRB1*03:01-DQA1*05:01-DQB1*02:01-DPB1*02:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 20  A*02:01-B*51:01-C*04:01-E*01:03:01-F*01:01:02-G*01:01-DRB1*03:01-DQA1*05:01-DQB1*02:01  Portugal Azores Terceira Island 0.4386130
 21  A*33:03:01-B*51:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01:01  Russia Bashkortostan, Bashkirs 0.4167120
 22  A*68-B*51-DRB1*03:01-DQB1*02  Mexico Michoacan, Morelia 0.3311150
 23  A*32-B*51-DRB1*03:01-DQB1*02  Mexico Mexico City Metropolitan Area Rural 0.3289150
 24  A*02:01:01-B*51:01:01-C*14:02:01-DRB1*03:01-DQA1*01:03:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*04:01:01  Russia Belgorod region 0.3268153
 25  A*24:02:01-B*51:01:01-C*04:01:01-DRB1*03:01:01-DQA1*05:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*04:01:01  Russia Belgorod region 0.3268153
 26  A*02-B*51-DRB1*03:01-DQB1*02  Mexico Mexico City Center 0.3247152
 27  A*02:05-B*51:01-C*16:01-DRB1*03:01-DQB1*02:01-DPB1*107:01  Tanzania Maasai 0.3195336
 28  A*02:05-B*51:01-C*16:01-DRB1*03:01-DQB1*02:01-DPB1*463:01  Tanzania Maasai 0.3195336
 29  A*02-B*51-DRB1*03:01-DQB1*02  Mexico Sinaloa Rural 0.2732183
 30  A*02-B*51-DRB1*03:01-DQB1*02  Mexico Sonora Rural 0.2538197
 31  A*02-B*51-DRB1*03:01-DQB1*02  Mexico Coahuila Rural 0.2294216
 32  A*02-B*51-DRB1*03:01-DQB1*02  Mexico Nuevo Leon Rural 0.2273439
 33  A*02-B*51-DRB1*03:01-DQB1*02  Mexico Chihuahua Rural 0.2092236
 34  A*03:01-B*51:01-C*15:02-DRB1*03:01:01-DQB1*02:01  England North West 0.2000298
 35  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*03:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 36  A*33:01:01-B*51:01:01-C*15:02:01-DRB1*03:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*104:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 37  A*02-B*51-DRB1*03:01-DQB1*02  Mexico Zacatecas Rural 0.1859266
 38  A*68:01-B*51:01-C*08:01-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Indian 0.1845271
 39  A*01:01-B*51:01-DRB1*03:01-DQB1*02:01  Mexico Mexico City Tlalpan 0.1515330
 40  A*68:01-B*51:01-DRB1*03:01-DQB1*02:01  Mexico Mexico City Tlalpan 0.1515330
 41  A*11:01-B*51:01-C*14:02-DRB1*03:01-DQA1*05:01-DQB1*02:01-DPB1*04:01  Sri Lanka Colombo 0.1401714
 42  A*11:01-B*51:01-C*15:02-DRB1*03:01-DQB1*02:01  Italy pop 5 0.1400975
 43  A*24:02:01-B*51:01:01-C*03:04:01-DRB1*03:01:01-DQB1*02:01:01  India Kerala Malayalam speaking 0.1400356
 44  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*03:01:01-DQB1*02:01:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.121028,927
 45  A*02-B*51-DRB1*03:01-DQB1*02  Mexico Puebla Rural 0.1199833
 46  A*02:01-B*51:01-C*14:02-DRB1*03:01-DQB1*02:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.10304,335
 47  A*02:01-B*51:01-C*16:01-DRB1*03:01-DQB1*02:01  USA Hispanic pop 2 0.09401,999
 48  A*02-B*51-DRB1*03:01-DQB1*02  Mexico Veracruz Rural 0.0924539
 49  A*02:01-B*51:01-C*14:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.08804,856
 50  A*02-B*51-DRB1*03:01-DQB1*02  Mexico Jalisco Rural 0.0853585
 51  A*29-B*51-DRB1*03:01-DQB1*02  Mexico Jalisco Rural 0.0853585
 52  A*02-B*51-DRB1*03:01-DQB1*02  Mexico Jalisco, Guadalajara city 0.08381,189
 53  A*24-B*51-DRB1*03:01-DQB1*02  Mexico Jalisco, Guadalajara city 0.08381,189
 54  A*01:01-B*51:01-C*16:02-DRB1*03:01-DQA1*02:01-DQB1*02:01-DPB1*04:01  Sri Lanka Colombo 0.0700714
 55  A*01:01-B*51:19-C*14:02-DRB1*03:01-DQA1*05:01-DQB1*02:01-DPB1*16:01  Sri Lanka Colombo 0.0700714
 56  A*68-B*51-DRB1*03:01-DQB1*02  Ecuador Andes Mixed Ancestry 0.0607824
 57  A*26:01-B*51:01-C*15:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.05904,856
 58  A*24:02-B*51:01-C*14:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Malay 0.0526951
 59  A*02:01-B*51:01-C*04:01-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.05104,856
 60  A*68-B*51-DRB1*03:01-DQB1*02  Mexico Puebla, Puebla city 0.05011,994
 61  A*02:01-B*51:01-C*02:02-DRB1*03:01-DQB1*02:01  USA Hispanic pop 2 0.04701,999
 62  A*29:02-B*51:01-C*15:02-DRB1*03:01-DQB1*02:01  USA Hispanic pop 2 0.04701,999
 63  A*32:01-B*51:01-C*15:02-DRB1*03:01-DQB1*02:01  USA Hispanic pop 2 0.04701,999
 64  A*02:01-B*51:01-C*15:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Italy minority 0.04401,159
 65  A*11:01-B*51:01-C*15:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Italy minority 0.04301,159
 66  A*31:01-B*51:01-C*15:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Italy minority 0.04301,159
 67  A*32:01-B*51:07-C*14:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Italy minority 0.04301,159
 68  A*33:01-B*51:01-C*15:04-DRB1*03:01-DQB1*02:01  Germany DKMS - Italy minority 0.04301,159
 69  A*68-B*51-DRB1*03:01-DQB1*02  Ecuador Mixed Ancestry 0.04261,173
 70  A*68:01-B*51:01-C*15:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.04104,856
 71  A*31:01-B*51:01-C*14:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.04035,849
 72  A*02:11-B*51:01-C*16:02-DRB1*03:01-DQB1*02:01  India Tamil Nadu 0.03992,492
 73  A*68:01-B*51:01-C*14:02-DRB1*03:01-DQB1*02:01  India Tamil Nadu 0.03942,492
 74  A*02:01-B*51:01-C*16:01-DRB1*03:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.03421,463
 75  A*11:01-B*51:01-C*15:02-DRB1*03:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.03421,463
 76  A*68:01-B*51:01-C*16:02-DRB1*03:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.03421,463
 77  A*03:01-B*51:01-C*14:02-DRB1*03:01-DQB1*02:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 78  A*11:01-B*51:01-C*14:02-DRB1*03:01-DQB1*02:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 79  A*24:02-B*51:01-C*14:02-DRB1*03:01-DQB1*02:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 80  A*24:02-B*51:01-C*15:02-DRB1*03:01-DQB1*02:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 81  A*29:02-B*51:01-C*15:02-DRB1*03:01-DQB1*02:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 82  A*31:01-B*51:01-C*14:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.03405,829
 83  A*68:01-B*51:01-C*15:02-DRB1*03:01-DQB1*02:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 84  A*01:01-B*51:01-C*14:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.03355,829
 85  A*24:02:01:01-B*51:01:01-C*04:01:01-DRB1*03:01:01-DQB1*02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 86  A*02:01-B*51:08-C*16:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.03304,856
 87  A*02:01-B*51:01-C*14:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.03275,849
 88  A*24:02-B*51:01-C*14:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.03204,204
 89  A*03:02-B*51:01-C*15:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.03104,204
 90  A*02:06-B*51:01-C*16:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.03065,849
 91  A*24:02-B*51:01-C*03:04-DRB1*03:01-DQA1*05:01-DQB1*02:01-DPA1*01:03-DPB1*04:01  Japan pop 17 0.03003,078
 92  A*02:06:01-B*51:01:01-C*14:02:01-DRB1*03:01:01-DQB1*02:01:01  China Zhejiang Han 0.02881,734
 93  A*26:01:01-B*51:01:01-C*16:02:01-DRB1*03:01:01-DQB1*02:01:01  China Zhejiang Han 0.02881,734
 94  A*31:01-B*51:01-C*14:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.02784,204
 95  A*01:01-B*51:01-C*14:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.02765,849
 96  A*02:01-B*51:01-C*07:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.02704,856
 97  A*24:02-B*51:01-C*16:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.02565,849
 98  A*03:01-B*51:01-C*14:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.025011,446
 99  A*68:01-B*51:01-C*14:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.02345,849
 100  A*32:01:01-B*51:01:01-C*02:02:02-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.023423,595

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 204) records   Pages: 1 2 3 of 3  


   

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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