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 87 (from 87) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*29:02-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Tunisia 4.0000100
 2  A*29:02-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Colombia North Wiwa El Encanto 3.846252
 3  A*29:02-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 3.42004,335
 4  B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Mexico Mexico City Mestizo population 3.1469143
 5  A*02:01-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Tunisia 3.0000100
 6  B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Ireland South 3.0000250
 7  A*29:02-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Mexico Mexico City Mestizo population 2.7972143
 8  A*03:01:01-B*07:06:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*02:01:04-DPB1*11:01:01  Brazil Barra Mansa Rio State Black 2.381073
 9  A*29:02:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01  Spain, Canary Islands, Gran canaria island 1.8600215
 10  A*29:02-B*44:03-C*16:01-DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*11:01  USA San Diego 1.8230496
 11  A*29:02-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Italy pop 5 1.3300975
 12  A*29:02-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Ireland South 1.3000250
 13  A*29:02-B*44:03-C*16:01-DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*04:01  Nicaragua Managua 1.2987339
 14  B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Mexico Mexico City Mestizo pop 2 1.2800234
 15  A*29:02:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*02:01:04-DPB1*13:01:01  Brazil Rio de Janeiro Parda 1.1765170
 16  A*29:02:01:01-B*44:03:01-C*16:01:01-DRB1*07:01:01:01-DQB1*02:02  Russia Bashkortostan, Tatars 1.0417192
 17  A*29:02:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.9727521
 18  A*29:02-B*40:11-C*16:01-DRB1*07:01-DQB1*02:02  Colombia North Wiwa El Encanto 0.961552
 19  A*29:02-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02-DPB1*02:01  Panama 0.9500462
 20  A*29:02:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*02:01:01-DPB1*11:01:01  Brazil Rio de Janeiro Caucasian 0.7782521
 21  A*29:01:01-B*44:08-C*16:01:01-DRB1*07:01:01-DQB1*02:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 22  A*29:02:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.667623,595
 23  A*29:02:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.6270405
 24  A*29:02:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Parda 0.5882170
 25  A*29:02-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02-DPB1*01:01  Panama 0.5700462
 26  A*01:01-B*51:01-C*16:01-DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*01:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 27  A*30:02-B*45:01-C*16:01-DRB1*07:01-DQA1*04:01-DQB1*02:02-DPB1*01:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 28  A*36:01-B*53:01-C*16:01-DRB1*07:01-DQA1*01:02-DQB1*02:02-DPB1*03:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 29  A*02:01-B*18:01-C*16:01-E*01:03:02-F*01:01:01-G*01:01-DRB1*07:01-DQA1*01:01-DQB1*02:02  Portugal Azores Terceira Island 0.4386130
 30  A*68:02-B*44:03-C*16:01-E*01:03:02-F*01:01:01-G*01:01-DRB1*07:01-DQA1*01:03-DQB1*02:02  Portugal Azores Terceira Island 0.4386130
 31  A*02:01-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Mexico Mexico City Mestizo pop 2 0.4274234
 32  A*29:02-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Mexico Mexico City Mestizo pop 2 0.4274234
 33  A*02:01-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02-DPB1*11:01  Panama 0.3800462
 34  A*02:01-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Mexico Mexico City Mestizo population 0.3497143
 35  B*51:01-C*16:01-DRB1*07:01-DQB1*02:02  Mexico Mexico City Mestizo population 0.3497143
 36  A*29:02:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.3423521
 37  A*29:02:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*02:02:02-DPB1*01:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 38  A*29:02:01:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02  Russia Nizhny Novgorod, Russians 0.29801,510
 39  A*03:01-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Italy pop 5 0.2900975
 40  A*03:01-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.27404,335
 41  A*02:01-B*44:03-C*16:01-DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*04:01  USA San Diego 0.2600496
 42  A*02:01:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.2414521
 43  A*02:01-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.23904,335
 44  A*03:01:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01  Spain, Canary Islands, Gran canaria island 0.2300215
 45  A*23:01:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01  Spain, Canary Islands, Gran canaria island 0.2300215
 46  A*24:02:01-B*45:03-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01  Spain, Canary Islands, Gran canaria island 0.2300215
 47  A*31:01:02-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01  Spain, Canary Islands, Gran canaria island 0.2300215
 48  A*03:01-B*44:03-C*16:01-DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*04:02  Nicaragua Managua 0.2165339
 49  A*29:02-B*44:03-C*16:01-DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*11:01  Nicaragua Managua 0.2165339
 50  A*03:01:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*02:01:04-DPB1*13:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 51  A*23:01:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*02:01:02-DPB1*01:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 52  A*26:01:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 53  A*30:02:01-B*45:01:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*03:01:01-DPB1*105:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 54  A*68:02:01-B*45:01:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*02:01:04-DPB1*13:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 55  A*01:01-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02-DPB1*04:01  Panama 0.1900462
 56  A*02:11-B*40:01-C*16:01-DRB1*07:01-DQB1*02:02  Malaysia Peninsular Indian 0.1845271
 57  A*01:01-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.17104,335
 58  A*24:02-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Italy pop 5 0.1400975
 59  A*11:01-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.13704,335
 60  A*30:02-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.13704,335
 61  A*24:02-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.10304,335
 62  A*30:02-B*51:01-C*16:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.10304,335
 63  A*31:01-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.10304,335
 64  A*03:01:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.082523,595
 65  A*29:02-B*15:03-C*16:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 66  A*32:01-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 67  A*02:01:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.056223,595
 68  A*02:01-B*45:01-C*16:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 69  A*23:01-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 70  A*24:02-B*45:01-C*16:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 71  A*26:08-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 72  A*33:03-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 73  A*68:02-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 74  A*68:02-B*51:01-C*16:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 75  A*01:01:01:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02  Russia Nizhny Novgorod, Russians 0.03311,510
 76  A*01:01:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.028023,595
 77  A*24:02:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.023423,595
 78  A*03:01-B*45:01-C*16:01-DRB1*07:01-DQB1*02:02  India East UCBB 0.02082,403
 79  A*02:01-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  India West UCBB 0.00865,829
 80  A*11:01:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.007223,595
 81  A*31:01:02-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.006623,595
 82  A*29:02-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  India South UCBB 0.004411,446
 83  A*32:01:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.004223,595
 84  A*68:01:02-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.003623,595
 85  A*25:01:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.003323,595
 86  A*03:01:01-B*44:03:01-C*16:01:15-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.002123,595
 87  A*26:08-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.001423,595

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).




   

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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