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 199) records   Pages: 1 2 of 2  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  B*44:02-C*05:01-DRB1*04:01-DQB1*03:01  Ireland South 4.5000250
 2  A*02:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01  Ireland South 4.0000250
 3  A*02:01-B*44:02-C*05:01-DRB1*04:01:01-DQB1*03:01  England North West 3.9000298
 4  A*02:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01-DPB1*04:01  Ireland South 3.0000250
 5  A*02:01-B*44:02-C*05:01-DRB1*04:01-DRB4*01:01-DQB1*03:01  USA NMDP European Caucasian 1.85241,242,890
 6  A*02:01-B*44:02-C*05:01-DRB1*04:01-DRB4*01:01-DQB1*03:01  USA NMDP North American Amerindian 1.524735,791
 7  A*11:01:01-B*44:02:01-C*15:02:01-DRB1*04:01:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*04:02:01  Brazil Rio de Janeiro Black 1.470668
 8  A*02:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01  USA NMDP American Indian South or Central America 1.44695,926
 9  A*02-B*44-DRB1*04:02-DQB1*03:01  Tunisia pop 3 1.2000104
 10  A*33-B*44-DRB1*04-DQB1*03:01  Mexico Veracruz, Poza Rica 1.111145
 11  A*02:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01  USA NMDP Alaska Native or Aleut 1.07331,376
 12  A*02-B*44-DRB1*04-DQB1*03:01  Mexico Nayarit, Tepic 1.030997
 13  A*32-B*44-DRB1*04-DQB1*03:01  Mexico Veracruz, Orizaba 0.833360
 14  A*02-B*44-DRB1*04-DQB1*03:01  Mexico Colima, Colima city 0.819761
 15  A*02:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01-DPB1*04:01  Germany DKMS - German donors 0.79433,456,066
 16  A*02:01:01-B*44:02:01-C*05:01:01-DRB1*04:01:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.7782521
 17  A*02-B*44-DRB1*04-DQB1*03:01  Mexico Guerrero state 0.6944144
 18  A*02-B*44-DRB1*04-DQB1*03:01  Mexico Michoacan, Morelia 0.6623150
 19  A*02-B*44-DRB1*04-DQB1*03:01  Mexico Jalisco, Zapopan 0.5952168
 20  A*24:02-B*44:02-DRB1*04:01-DQB1*03:01  Mexico Veracruz Xalapa 0.595284
 21  A*02:01:01-B*44:02:01-C*05:01:01-DRB1*04:01:01-DQB1*03:01:01-DPA1*02:01:01-DPB1*04:01:01  Brazil Rio de Janeiro Parda 0.5882170
 22  A*34:02-B*44:02-DRB1*04:01-DQB1*03:01  Iran Tabriz Azeris 0.515597
 23  A*02:01-B*44:02-C*05:01-DRB1*04:01-DRB4*01:01-DQB1*03:01  USA NMDP Middle Eastern or North Coast of Africa 0.511270,890
 24  A*02:01:01-B*44:02:01-C*05:01:01-DRB1*04:01:01-DQB1*03:01:01  Poland BMR 0.475423,595
 25  A*02:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.44504,335
 26  A*02-B*44-DRB1*04-DQB1*03:01  Mexico Nuevo Leon, Monterrey city 0.4425226
 27  A*32-B*44-DRB1*04-DQA1*03-DQB1*03:01  Russia, South Ural, Chelyabinsk region, Nagaybaks 0.4400112
 28  A*02:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01  USA African American pop 4 0.43002,411
 29  A*25-B*44-DRB1*04-DQB1*03:01  Mexico Chihuahua Chihuahua City 0.4202119
 30  A*23-B*44-DRB1*04-DQB1*03:01  Mexico Chiapas Rural 0.4132121
 31  A*02:01-B*44:02-C*05:01-DRB1*04:01-DRB4*01:01-DQB1*03:01  USA NMDP African American pop 2 0.3795416,581
 32  A*02-B*44-DRB1*04-DQB1*03:01  Mexico Tabasco Rural 0.3521142
 33  A*02-B*44-DRB1*04-DQB1*03:01  Mexico Nuevo Leon Rural 0.3409439
 34  A*02:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01  USA NMDP Caribean Indian 0.338614,339
 35  A*02:01-B*44:02-C*05:01-DRB1*04:01-DRB4*01:01-DQB1*03:01  USA NMDP Mexican or Chicano 0.3361261,235
 36  A*02:01:01:01-B*44:02:01:01-C*05:01:01:02-DRB1*04:01:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.33271,510
 37  A*02:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01  USA NMDP Hawaiian or other Pacific Islander 0.328011,499
 38  A*02:01:01-B*44:02:01-C*05:01:01-DRB1*04:01:01-DQA1*03:03:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*04:01:01  Russia Belgorod region 0.3268153
 39  A*02-B*44-DRB1*04-DQB1*03:01  Mexico Guanajuato Rural 0.3067162
 40  A*01:01-B*44:02-C*05:01-DRB1*04:07:01-DQB1*03:01  England North West 0.3000298
 41  A*02:01-B*44:02-C*05:01-DRB1*04:01-DQA1*03:01-DQB1*03:01-DPB1*04:01  South Africa Worcester 0.3000159
 42  A*02:01-B*44:02-C*05:01-DRB1*04:01-DRB4*01:01-DQB1*03:01  USA NMDP Caribean Hispanic 0.2972115,374
 43  A*24:02:01-B*44:03:02-C*03:04:01-DRB1*04:03:01-DQB1*03:01:01  India Karnataka Kannada Speaking 0.2870174
 44  A*02-B*44-DRB1*04-DQB1*03:01  Mexico Michoacan Rural 0.2865348
 45  A*02:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01-DPB1*04:01  Russia Karelia 0.27851,075
 46  A*02:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01  USA Hispanic pop 2 0.26601,999
 47  A*01:01:01:01-B*44:02:01:01-C*08:02:01-DRB1*04:01:01-DQB1*03:01  Russia Bashkortostan, Tatars 0.2604192
 48  A*02:01-B*44:02-C*05:01-DRB1*04:01-DQA1*03:01-DQB1*03:01-DPB1*04:01  USA San Diego 0.2600496
 49  A*32:01-B*44:02-C*05:01-DRB1*04:01-DQA1*03:01-DQB1*03:01-DPB1*03:01  USA San Diego 0.2600496
 50  A*74:03-B*44:03-C*04:01-DRB1*04:01-DQA1*03:01-DQB1*03:01-DPB1*02:01  USA San Diego 0.2600496
 51  A*02:01-B*44:02-C*05:01-DRB1*04:01-DRB4*01:01-DQB1*03:01  USA NMDP Caribean Black 0.251233,328
 52  A*02:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01  USA NMDP Black South or Central American 0.24884,889
 53  A*02:01-B*44:02-C*05:01-DRB1*04:01-DRB4*01:01-DQB1*03:01  USA NMDP African 0.233628,557
 54  A*29:02-B*44:03-C*16:01-DRB1*04:11-DQA1*05:05-DQB1*03:01-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218
 55  A*02:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01  Germany DKMS - Italy minority 0.21601,159
 56  A*02:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01  Germany DKMS - Turkey minority 0.21304,856
 57  A*02:01-B*44:02-C*05:01-DRB1*04:01-DRB4*01:01-DQB1*03:01  USA NMDP Hispanic South or Central American 0.2086146,714
 58  A*01:01-B*44:02-C*05:01-DRB1*04:01:01-DQB1*03:01  England North West 0.2000298
 59  A*02:01-B*44:02-C*07:04-DRB1*04:07:01-DQB1*03:01  England North West 0.2000298
 60  A*03:01-B*44:02-C*07:02-DRB1*04:01:01-DQB1*03:01  England North West 0.2000298
 61  A*25:01-B*44:02-C*05:01-DRB1*04:01:01-DQB1*03:01  England North West 0.2000298
 62  A*30:02-B*44:02-C*05:01-DRB1*04:01:01-DQB1*03:01  England North West 0.2000298
 63  A*02:01:01-B*44:02:01-C*05:01:01-DRB1*04:01:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*17:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 64  A*24:02:01-B*44:02:01-C*05:01:01-DRB1*04:03:01-DQB1*03:01:01-DPA1*02:01:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 65  A*24:02-B*44:02-C*03:02-DRB1*04:02-DQB1*03:01-DPB1*04:01  Panama 0.1900462
 66  A*24:02-B*44:02-C*15:02-DRB1*04:03-DQB1*03:01  Malaysia Peninsular Indian 0.1845271
 67  A*24:02-B*44:03-C*08:01-DRB1*04:01-DQB1*03:01  Malaysia Peninsular Indian 0.1845271
 68  A*03:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01  USA NMDP Alaska Native or Aleut 0.17671,376
 69  A*03:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01  Germany DKMS - Italy minority 0.17301,159
 70  A*32-B*44-DRB1*04:01-DQA1*03:02-DQB1*03:01  Brazil Paraná Caucasian 0.1560641
 71  A*01:01-B*44:02-DRB1*04:01-DQB1*03:01  Mexico Mexico City Tlalpan 0.1515330
 72  A*02:01-B*44:02-DRB1*04:01-DQB1*03:01  Mexico Mexico City Tlalpan 0.1515330
 73  A*11:01-B*44:02-DRB1*04:02-DQB1*03:01  Mexico Mexico City Tlalpan 0.1515330
 74  A*03:02-B*44:02-C*04:01-DRB1*04:05-DQB1*03:01  Italy pop 5 0.1400975
 75  A*02-B*44-DRB1*04-DQB1*03:01  Mexico Jalisco, Guadalajara city 0.12561,189
 76  A*68:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01  USA Hispanic pop 2 0.10301,999
 77  A*24:02:01:01-B*44:02:01:01-C*05:01:01:02-DRB1*04:01:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.09771,510
 78  A*02:01-B*44:02-C*05:01-DRB1*04:01-DRB4*01:01-DQB1*03:01  USA NMDP Japanese 0.086324,582
 79  A*02-B*44-DRB1*04-DQB1*03:01  Mexico Jalisco Rural 0.0853585
 80  A*02:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01-DPB1*20:01  Russia Karelia 0.08231,075
 81  A*24:02-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01  Germany DKMS - Turkey minority 0.08204,856
 82  A*02:01-B*44:02-C*05:01-DRB1*04:01-DRB4*01:01-DQB1*03:01  USA NMDP Filipino 0.077350,614
 83  A*68:01-B*44:03-C*07:01-DRB1*04:08-DQA1*03:01-DQB1*03:01-DPB1*09:01  Sri Lanka Colombo 0.0700714
 84  A*01:01:01-B*44:03:02-C*04:01:01-DRB1*04:07-DQB1*03:01  Costa Rica Central Valley Mestizo (G) 0.0689221
 85  A*01:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 86  A*03:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 87  A*02:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01-DPB1*04:02  Germany DKMS - German donors 0.06663,456,066
 88  A*02:01:01:01-B*44:02:01:01-C*05:01:01:02-DRB1*04:07:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.06611,510
 89  A*01-B*44-DRB1*04-DQB1*03:01  Ecuador Andes Mixed Ancestry 0.0607824
 90  A*11-B*44-DRB1*04-DQB1*03:01  Ecuador Andes Mixed Ancestry 0.0607824
 91  A*01:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01-DPB1*05:01  Russia Karelia 0.05741,075
 92  A*32:01-B*44:03-C*04:01-DRB1*04:07-DQB1*03:01-DPB1*03:01  Russia Karelia 0.05651,075
 93  A*03:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01-DPB1*02:01  Russia Karelia 0.05641,075
 94  A*02:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01-DPB1*02:01  Russia Karelia 0.05641,075
 95  A*32:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01-DPB1*04:01  Russia Karelia 0.05571,075
 96  A*02:65-B*44:03-C*07:01-DRB1*04:04-DQB1*03:01  Malaysia Peninsular Malay 0.0526951
 97  A*02:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01-DPB1*02:01  Germany DKMS - German donors 0.05153,456,066
 98  A*24:02-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01  USA Hispanic pop 2 0.05101,999
 99  A*30:02-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01  USA African American pop 4 0.05002,411
 100  A*03:01-B*44:02-C*05:01-DRB1*04:01-DQB1*03:01  USA Hispanic pop 2 0.04701,999

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 199) 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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