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 88 (from 88) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*24-B*49-DRB1*07-DQB1*02  Mexico Veracruz, Orizaba 2.500060
 2  A*23-B*49-DRB1*07-DQB1*02  Mexico Hidalgo, Pachuca 2.439041
 3  A*31-B*49-C*06-DRB1*07-DQB1*02  Sudan Khartoum 1.020098
 4  A*23-B*49-DRB1*07-DQB1*02  Mexico Guanajuato Rural 0.6135162
 5  A*68-B*49-DRB1*07-DQB1*02  Mexico Zacatecas, Zacatecas city 0.595284
 6  A*02-B*49-C*02-DRB1*07-DQB1*02  Sudan Khartoum 0.510098
 7  A*31-B*49-C*02-DRB1*07-DQB1*02  Sudan Khartoum 0.510098
 8  A*11:01-B*49:01-C*07:01-E*01:01:01-F*01:01:02-G*01:01-DRB1*07:01-DQA1*02:01-DQB1*02:02  Portugal Azores Terceira Island 0.4386130
 9  A*29:02-B*49:01-C*07:01-E*01:01:01-F*01:01:01-G*01:01-DRB1*07:01-DQA1*02:01-DQB1*02:02  Portugal Azores Terceira Island 0.4386130
 10  A*01-B*49-DRB1*07-DQB1*02  Ecuador Coast Mixed Ancestry 0.4202238
 11  A*02:01:01:01-B*49:01:01-C*07:01:01-DRB1*07:01:01:01-DQB1*02:02  Russia Bashkortostan, Bashkirs 0.4167120
 12  A*29:01:01:01-B*49:01:01-C*07:01:01-DRB1*07:01-DQB1*02:02  Russia Bashkortostan, Bashkirs 0.4167120
 13  A*03-B*49-DRB1*07:01-DQA1*02:01-DQB1*02:02  Brazil Paraná Caucasian 0.3900641
 14  A*32:01:01-B*49:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*02:01:01-DPB1*13:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 15  A*02-B*49-DRB1*07-DQB1*02  Mexico Jalisco, Zapopan 0.2976168
 16  A*26:01:01-B*49:01:01-C*07:01:01-DRB1*07:01:01-DQB1*02:02:01  Spain, Canary Islands, Gran canaria island 0.2300215
 17  A*01-B*49-DRB1*07-DQB1*02  Mexico Nuevo Leon, Monterrey city 0.2212226
 18  A*02:05-B*49:01-C*07:01-DRB1*07:01-DQB1*02:01  Germany DKMS - Italy minority 0.17301,159
 19  A*68-B*49-DRB1*07-DQB1*02  Mexico Jalisco Rural 0.1706585
 20  A*03:01-B*49:01-C*06:02-DRB1*07:01-DQB1*02:02-DPB1*17:01  Tanzania Maasai 0.1597336
 21  A*23-B*49-DRB1*07:01-DQA1*02:01-DQB1*02:02  Brazil Paraná Caucasian 0.1560641
 22  A*11:04-B*49:02-DRB1*07:01-DQB1*02:02  Mexico Mexico City Tlalpan 0.1515330
 23  A*01-B*49-DRB1*07-DQB1*02  Mexico Michoacan Rural 0.1433348
 24  A*01-B*49-DRB1*07-DQB1*02  Ecuador Mixed Ancestry 0.12791,173
 25  A*01-B*49-DRB1*07-DQB1*02  Mexico Puebla Rural 0.1199833
 26  A*11:01-B*49:01-C*07:01-DRB1*07:01-DQB1*02:01  USA Hispanic pop 2 0.09401,999
 27  A*23:01-B*49:01-C*07:01-DRB1*07:01-DQB1*02:01  Germany DKMS - Turkey minority 0.09104,856
 28  A*02-B*49-DRB1*07-DQB1*02  Mexico Jalisco Rural 0.0853585
 29  A*02-B*49-DRB1*07-DQB1*02  Mexico Jalisco, Guadalajara city 0.08381,189
 30  A*24-B*49-DRB1*07:01-DQA1*02:01-DQB1*02:02  Brazil Paraná Caucasian 0.0780641
 31  A*24-B*49-C*07-DRB1*07-DQB1*02-DPB1*17  Norway ethnic Norwegians 0.07004,510
 32  A*02:05-B*49:01-C*07:01-DRB1*07:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.06841,463
 33  A*02:01-B*49:01-C*07:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 34  A*23:01-B*49:01-C*07:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 35  A*01-B*49-DRB1*07-DQB1*02  Ecuador Andes Mixed Ancestry 0.0607824
 36  A*03:01-B*49:01-C*06:02-DRB1*07:01-DQB1*02:01  India Tamil Nadu 0.06022,492
 37  A*30-B*49-DRB1*07-DQB1*02  Mexico Tlaxcala Rural 0.0602830
 38  A*02-B*49-C*07-DRB1*07-DQB1*02-DPB1*17  Norway ethnic Norwegians 0.06004,510
 39  A*26:01-B*49:01-C*07:01-DRB1*07:01-DQB1*02:01  Germany DKMS - Italy minority 0.05701,159
 40  A*02:05-B*49:01-C*07:01-DRB1*07:01-DQB1*02:01-DPB1*17:01  Russia Karelia 0.05651,075
 41  A*02-B*49-C*07-DRB1*07-DQA1*02-DQB1*02  Spain, Castilla y Leon, Northwest, 0.05301,743
 42  A*01-B*49-DRB1*07-DQB1*02  Mexico Puebla, Puebla city 0.05011,994
 43  A*02-B*49-DRB1*07-DQB1*02  Mexico Puebla, Puebla city 0.05011,994
 44  A*02:02-B*49:01-C*07:01-DRB1*07:01-DQB1*02:01  USA African American pop 4 0.04402,411
 45  A*24:02-B*49:01-C*07:01-DRB1*07:01-DQB1*02:01  USA African American pop 4 0.04402,411
 46  A*30:01-B*49:01-C*07:01-DRB1*07:01-DQB1*02:01  USA African American pop 4 0.04402,411
 47  A*24-B*49-DRB1*07-DQB1*02  Mexico Jalisco, Guadalajara city 0.04191,189
 48  A*30:04-B*49:01-C*07:01-DRB1*07:01-DQB1*02:01  Germany DKMS - Turkey minority 0.04104,856
 49  A*01:01-B*49:01-C*07:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 50  A*01:02-B*49:01-C*07:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 51  A*02:05-B*49:01-C*07:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 52  A*30:02-B*49:01-C*07:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 53  A*68:02-B*49:01-C*07:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 54  A*26-B*49-C*07-DRB1*07-DQA1*02-DQB1*02  Spain, Castilla y Leon, Northwest, 0.03311,743
 55  A*29-B*49-C*07-DRB1*07-DQA1*02-DQB1*02  Spain, Castilla y Leon, Northwest, 0.03311,743
 56  A*33:03:01-B*49:01:01-C*07:01:01-DRB1*07:01:01-DQB1*02:02  Russia Nizhny Novgorod, Russians 0.03311,510
 57  A*26-B*49-C*02-DRB1*07-DQA1*02-DQB1*02  Spain, Castilla y Leon, Northwest, 0.03281,743
 58  A*24:02:01-B*49:01:01-C*07:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.025923,595
 59  A*03-B*49-DRB1*07-DQB1*02  Mexico Puebla, Puebla city 0.02511,994
 60  A*03:01-B*49:01-C*07:01-DRB1*07:01-DQB1*02:01  Germany DKMS - Turkey minority 0.02304,856
 61  A*68:01-B*49:01-C*07:01-DRB1*07:01-DQB1*02:01  Germany DKMS - Turkey minority 0.02104,856
 62  A*11-B*49-C*07-DRB1*07-DQA1*02-DQB1*02  Spain, Castilla y Leon, Northwest, 0.02031,743
 63  A*01-B*49-C*07-DRB1*07-DQB1*02-DPB1*04  Norway ethnic Norwegians 0.02004,510
 64  A*02:01-B*49:01-C*07:01-DRB1*07:01-DQB1*02:01  Germany DKMS - Turkey minority 0.01404,856
 65  A*30:02-B*49:01-C*07:01-DRB1*07:01-DQB1*02:01-DPB1*02:01  Germany DKMS - German donors 0.01363,456,066
 66  A*26:01:01-B*49:01:01-C*07:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.012523,595
 67  A*24:07-B*49:01-C*07:01-DRB1*07:01-DQB1*02:02  India Central UCBB 0.01194,204
 68  A*11:01-B*49:01-C*07:01-DRB1*07:01-DQB1*02:02  India Central UCBB 0.01144,204
 69  A*03:02-B*49:01-C*07:01-DRB1*07:01-DQB1*02:01  USA African American pop 4 0.01102,411
 70  A*26:01-B*49:01-C*07:01-DRB1*07:01-DQB1*02:01  USA African American pop 4 0.01102,411
 71  A*02:05:01-B*49:01:01-C*07:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.010723,595
 72  A*02-B*49-C*07-DRB1*07-DQB1*02-DPB1*04  Norway ethnic Norwegians 0.01004,510
 73  A*24-B*49-C*07-DRB1*07-DQB1*02-DPB1*04  Norway ethnic Norwegians 0.01004,510
 74  A*32-B*49-C*07-DRB1*07-DQB1*02-DPB1*02  Norway ethnic Norwegians 0.01004,510
 75  A*01:01-B*49:01-C*07:01-DRB1*07:01-DQB1*02:02  India South UCBB 0.008711,446
 76  A*02:11-B*49:01-C*07:01-DRB1*07:01-DQB1*02:02  India West UCBB 0.00865,829
 77  A*33:03-B*49:01-C*07:01-DRB1*07:01-DQB1*02:02  India West UCBB 0.00865,829
 78  A*24:07-B*49:01-C*07:01-DRB1*07:01-DQB1*02:02  India North UCBB 0.00855,849
 79  A*23:01:01-B*49:01:01-C*07:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.007723,595
 80  A*02:01:01-B*49:01:01-C*07:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.006623,595
 81  A*11:01-B*49:01-C*07:01-DRB1*07:01-DQB1*02:02  India North UCBB 0.00665,849
 82  A*11:01:01-B*49:01:01-C*07:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.005623,595
 83  A*23:01-B*49:01-C*07:01-DRB1*07:01-DQB1*02:02  India South UCBB 0.004411,446
 84  A*32:01-B*49:01-C*07:01-DRB1*07:01-DQB1*02:02  India South UCBB 0.004411,446
 85  A*32:01:01-B*49:01:01-C*07:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.004223,595
 86  A*03:01:01-B*49:01:01-C*02:02:02-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.002123,595
 87  A*23:01:01-B*49:01:01-C*12:02:02-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.002123,595
 88  A*11:01:79-B*49:01:01-C*07:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.001623,595

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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