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 98 (from 98) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  Ireland South 1.6000250
 2  A*24:02:01-B*39:01:01-C*05:01:01-DRB1*01:01:01-DQB1*05:01:01-DPA1*02:06-DPB1*05:01:01  Brazil Rio de Janeiro Black 1.470668
 3  A*02:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  Ireland South 1.2000250
 4  A*02:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01-DPB1*04:02  Ireland South 1.2000250
 5  A*02:01-B*44:02-C*05:01-DRB1*01:01:01-DQB1*05:01:01  England North West 1.0000298
 6  A*02:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.63751,463
 7  A*02:01:01:01-B*58:01:01-C*05:01:01:02-DRB1*01:01:01-DQB1*05:01  Russia Bashkortostan, Tatars 0.5208192
 8  A*32:01:01-B*44:02:01:01-C*05:01:01:02-DRB1*01:01:01-DQB1*05:01  Russia Bashkortostan, Tatars 0.5208192
 9  A*02:01-B*44:02-C*05:01-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPB1*04:01  Nicaragua Managua 0.4329339
 10  A*01:01:01-B*44:02:01-C*05:01:01-DRB1*01:01:01-DQA1*01:01:01-DQB1*05:01-DPA1*01:03:01-DPB1*04:01  Russia Belgorod region 0.3268153
 11  A*02:01-B*44:02:01-C*05:01:01-DRB1*01:01:01-DQA1*01:01:01-DQB1*05:01-DPA1*02:02:02-DPB1*04:01:01  Russia Belgorod region 0.3268153
 12  A*02:01:01-B*35:02:01-C*05:01:01-DRB1*01:01:01-DQB1*05:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 13  A*29:02:01-B*18:01:01-C*05:01:01-DRB1*01:01:01-DQB1*05:01:01-DPA1*02:01:01-DPB1*14:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 14  A*02:01-B*44:02-C*05:01-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPB1*05:01  South Africa Worcester 0.3000159
 15  A*29:01-B*44:02-C*05:01-DRB1*01:01-DQA1*05:05-DQB1*05:01-DPB1*18:01  South Africa Worcester 0.3000159
 16  A*02:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  USA NMDP American Indian South or Central America 0.29215,926
 17  A*02:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  Italy pop 5 0.2900975
 18  A*02:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  Germany DKMS - Italy minority 0.28801,159
 19  A*24:02:01:01-B*44:02:01:01-C*05:01:01-DRB1*01:01:01-DQB1*05:01  Russia Bashkortostan, Tatars 0.2604192
 20  A*32:01-B*44:02-C*05:01-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPB1*13:01  USA San Diego 0.2600496
 21  A*02:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.23904,335
 22  A*68:01-B*44:02-C*05:01-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPB1*04:01  Nicaragua Managua 0.2165339
 23  A*24:02:01-B*44:02:01-C*05:01:01-DRB1*01:01:01-DQB1*05:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 24  A*02:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  USA NMDP Black South or Central American 0.18394,889
 25  A*02:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  USA African American pop 4 0.17402,411
 26  A*02:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01-DPB1*04:01  Russia Karelia 0.15361,075
 27  A*02:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01-DPB1*04:01  Germany DKMS - German donors 0.14473,456,066
 28  A*01:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  Italy pop 5 0.1400975
 29  A*25:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01-DPB1*04:01  Germany DKMS - German donors 0.13203,456,066
 30  A*26:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  Germany DKMS - Turkey minority 0.12604,856
 31  A*02:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  Germany DKMS - Turkey minority 0.10204,856
 32  A*02:01:01-B*44:02:01-C*05:01:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.101423,595
 33  A*32:01:01-B*44:02:01:01-C*05:01:01:02-DRB1*01:01:01-DQB1*05:01  Russia Nizhny Novgorod, Russians 0.09931,510
 34  A*02:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01-DPB1*02:01  Russia Karelia 0.09741,075
 35  A*02:11-B*44:02-C*05:01-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPB1*04:01  Sri Lanka Colombo 0.0700714
 36  A*03:01-B*51:08-C*05:01-DRB1*01:01-DQB1*05:01  India West UCBB 0.06865,829
 37  A*03:01:01-B*44:02:01-C*05:01:01-DRB1*01:01:01-DQB1*05:01:01  China Zhejiang Han 0.05771,734
 38  A*02:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01-DPB1*04:02  Germany DKMS - German donors 0.05733,456,066
 39  A*02:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  USA Hispanic pop 2 0.04801,999
 40  A*29:02-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  USA Hispanic pop 2 0.04701,999
 41  A*32:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  Germany DKMS - Turkey minority 0.04704,856
 42  A*24:02-B*27:02-C*05:01-DRB1*01:01-DQB1*05:01  Germany DKMS - Italy minority 0.04301,159
 43  A*24:02-B*51:01-C*05:01-DRB1*01:01-DQB1*05:01  Germany DKMS - Italy minority 0.04301,159
 44  A*03:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  Germany DKMS - Turkey minority 0.04004,856
 45  A*02:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01-DPB1*03:01  Germany DKMS - German donors 0.03703,456,066
 46  A*02:01:01:01-B*44:02:01:01-C*05:01:01-DRB1*01:01:01-DQB1*05:01  Russia Nizhny Novgorod, Russians 0.03681,510
 47  A*24:02-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.03431,463
 48  A*02:01-B*18:01-C*05:01-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 49  A*03:01-B*14:01-C*05:01-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 50  A*03:01-B*18:01-C*05:01-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 51  A*03:01-B*39:01-C*05:01-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 52  A*24:02-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 53  A*26:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 54  A*29:02-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 55  A*30:02-B*18:01-C*05:01-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 56  A*32:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 57  A*68:02-B*18:01-C*05:01-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 58  A*68:03-B*51:01-C*05:01-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 59  A*02:01:01:01-B*13:02:01-C*05:01:01-DRB1*01:01:01-DQB1*05:01  Russia Nizhny Novgorod, Russians 0.03311,510
 60  A*02:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01-DPB1*02:01  Germany DKMS - German donors 0.02633,456,066
 61  A*03:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  India West UCBB 0.02575,829
 62  A*24:02:01-B*44:02:01-C*05:01:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.025523,595
 63  A*25:01:01-B*44:02:01-C*05:01:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.024423,595
 64  A*03:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01-DPB1*04:01  Germany DKMS - German donors 0.02223,456,066
 65  A*24:02-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01-DPB1*04:01  Germany DKMS - German donors 0.01893,456,066
 66  A*01:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01-DPB1*04:01  Germany DKMS - German donors 0.01783,456,066
 67  A*03:01:01-B*44:02:01-C*05:01:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.016423,595
 68  A*02:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  India West UCBB 0.01335,829
 69  A*32:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01-DPB1*04:01  Germany DKMS - German donors 0.01293,456,066
 70  A*01:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  India Central UCBB 0.01194,204
 71  A*26:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  India Central UCBB 0.01194,204
 72  A*26:01-B*51:08-C*05:01-DRB1*01:01-DQB1*05:01  India Central UCBB 0.01194,204
 73  A*32:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01-DPB1*03:01  Germany DKMS - German donors 0.01143,456,066
 74  A*02:01-B*39:01-C*05:01-DRB1*01:01-DQB1*05:01  Germany DKMS - Turkey minority 0.01004,856
 75  A*23:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  Germany DKMS - Turkey minority 0.01004,856
 76  A*33:03-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  Germany DKMS - Turkey minority 0.01004,856
 77  A*69:01-B*39:01-C*05:01-DRB1*01:01-DQB1*05:01  Germany DKMS - Turkey minority 0.01004,856
 78  A*02:01-B*51:08-C*05:01-DRB1*01:01-DQB1*05:01  India South UCBB 0.008711,446
 79  A*03:01-B*51:08-C*05:01-DRB1*01:01-DQB1*05:01  India South UCBB 0.008711,446
 80  A*02:20-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  India West UCBB 0.00865,829
 81  A*26:01-B*51:08-C*05:01-DRB1*01:01-DQB1*05:01  India West UCBB 0.00865,829
 82  A*26:01-B*51:08-C*05:01-DRB1*01:01-DQB1*05:01  India North UCBB 0.00855,849
 83  A*68:01-B*44:02-C*05:01-DRB1*01:01-DQB1*05:01  India North UCBB 0.00855,849
 84  A*26:01:01-B*44:02:01-C*05:01:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.006323,595
 85  A*02:01-B*51:01-C*05:01-DRB1*01:01-DQB1*05:01  India South UCBB 0.004411,446
 86  A*24:02-B*51:08-C*05:01-DRB1*01:01-DQB1*05:01  India South UCBB 0.004411,446
 87  A*30:01-B*51:08-C*05:01-DRB1*01:01-DQB1*05:01  India South UCBB 0.004411,446
 88  A*33:03-B*51:08-C*05:01-DRB1*01:01-DQB1*05:01  India South UCBB 0.004411,446
 89  A*31:01:02-B*27:05:02-C*05:01:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.004223,595
 90  A*31:01:02-B*44:02:01-C*05:01:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.003623,595
 91  A*68:01:02-B*44:02:01-C*05:01:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.002523,595
 92  A*02:01:01-B*27:05:02-C*05:01:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.002223,595
 93  A*33:03:01-B*44:02:01-C*05:01:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.002123,595
 94  A*03:02:01-B*44:02:01-C*05:01:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.002123,595
 95  A*68:01:02-B*27:05:02-C*05:01:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.002123,595
 96  A*02:01:01-B*18:01:01-C*05:01:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.002123,595
 97  A*29:02:01-B*44:02:01-C*05:01:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.002023,595
 98  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.001723,595

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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