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 92 (from 92) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  DRB1*04:01-DQA1*03:01-DQB1*03:01  Mongolia Ulaanbaatar Khalkha 11.000041
 2  DRB1*04:01-DQA1*03:01-DQB1*03:01  Mongolia Tarialan Khoton 7.800085
 3  DRB1*04:01-DQA1*03:01-DQB1*03:01  Spain Las Alpujarras 5.290085
 4  DRB1*09:01-DQA1*03:01-DQB1*03:01  India Northeast Lachung 5.100058
 5  DRB1*04:01-DQA1*03:01/03:02-DQB1*03:01  England pop 6 4.0000177
 6  DRB1*08-DQA1*03:01-DQB1*03:01  India Northeast Mech 3.900063
 7  DRB1*04:07-DQA1*03:01-DQB1*03:01  Iran Yazd Zoroastrian 3.800065
 8  DRB1*04-DQA1*03:01-DQB1*03:01  Russia Mari 3.5000202
 9  DRB1*04:01-DRB4*01:01-DQA1*03:01-DQB1*03:01-DPB1*04:01  USA San Francisco Caucasian 3.2000220
 10  DRB1*04:01-DRB4*01:01-DQA1*03:01-DQB1*03:01-DPB1*04:01  USA San Francisco Caucasian 3.2000220
 11  DRB1*04:03-DQA1*03:01-DQB1*03:01  Iran Yazd Zoroastrian 3.100065
 12  DRB1*04:01-DQA1*03:01-DQB1*03:01  USA San Francisco Caucasian 3.0000220
 13  DRB1*04-DQA1*03:01-DQB1*03:01  Italy pop 2 2.800053
 14  DRB1*04-DQA1*03:01-DQB1*03:01  Russia Smolensk 2.6000156
 15  DRB1*04-DQA1*03:01-DQB1*03:01  Ukraine Khmelnytskyi 2.5000138
 16  DRB1*08-DQA1*03:01-DQB1*03:01  India Northeast Rajbanshi 2.500098
 17  DRB1*04:08-DQA1*03:01-DQB1*03:01  China Urumqi Kazak 2.400042
 18  DRB1*04:01-DQA1*03:01/03:02/03:03-DQB1*03:01/03:09  Russia Siberia Dudinka Nganasan 2.100024
 19  DRB1*04-DQA1*03:01-DQB1*03:01  Belarus Gomel Region 2.1000100
 20  DRB1*04:01-DQA1*03:01-DQB1*03:01  Russia Northwest Slavic 2.0000200
 21  DRB1*04-DQA1*03:01-DQB1*03:01  Ukraine Lvov 2.0000102
 22  DRB1*04-DQA1*03:01-DQB1*03:01  Belarus Brest Region 1.9000105
 23  DRB1*04:03/04:04/04:06/04:07/04:08-DQA1*03:01/03:02-DQB1*03:01  England pop 6 1.7000177
 24  DRB1*04-DQA1*03:01-DQB1*03:01  Russia Vologda 1.7000121
 25  DRB1*04-DQA1*03:01-DQB1*03:01  Russia Kostroma Region 1.6000126
 26  DRB1*04-DQA1*03:01-DQB1*03:01  Belarus Vitebsk Region 1.500070
 27  DRB1*09:01-DQA1*03:01-DQB1*03:01  India Northeast Mech 1.500063
 28  DRB1*04:01-DQA1*03:01-DQB1*03:01  Slovenia pop 2 1.4000140
 29  DRB1*04:07-DQA1*03:01-DQB1*03:01  Slovenia pop 2 1.4000140
 30  A*24:02-B*40:02-C*07:01-DRB1*04:04-DQA1*03:01-DQB1*03:01  Brazil Puyanawa 1.3333150
 31  DRB1*04:07-DQA1*03:01-DQB1*03:01  Mexico Highlands Mestizos 1.3000160
 32  A*68:01-B*40:04-C*03:02/03:04-DRB1*04:03-DQA1*03:01:01-DQB1*03:01-DPA1*02-DPB1*04:02  Venezuela Sierra de Perija Yucpa 1.200073
 33  DRB1*04-DQA1*03:01-DQB1*03:01  Russia Arkhangelsk 1.200081
 34  DRB1*04:01-DQA1*03:01-DQB1*03:01  Japan pop 2 1.1000916
 35  DRB1*04:04-DQA1*03:01-DQB1*03:01  Australia New South Wales Aborigine 1.1000177
 36  A*68:01-B*35:20-C*04:01-DRB1*04:07-DQA1*03:01-DQB1*03:01  Mexico Chichen Itza Maya (prehispanic) 1.063847
 37  DRB1*04:02-DQA1*03:01-DQB1*03:01  Spain Las Alpujarras 0.590085
 38  A*02:01-B*44:02-C*05:01-DRB1*01:01-DQA1*03:01-DQB1*03:01-DPB1*04:01  USA San Diego 0.5210496
 39  A*11:01-B*35:01-C*04:01-DRB1*04:07-DQA1*03:01-DQB1*03:01-DPB1*03:01  USA San Diego 0.5210496
 40  A*68:02-B*45:01-C*07:02-DRB1*09:01-DQA1*03:01-DQB1*03:01-DPB1*129:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 41  A*24:02-B*50:01-C*04:01-E*01:01:01-F*01:03:01-G*01:04-DRB1*11:04-DQA1*03:01-DQB1*03:01  Portugal Azores Terceira Island 0.4386130
 42  A*02:01:01-B*18:01:01-C*07:01:01-DRB1*04:04:01-DQA1*03:01:01-DQB1*03:01-DPA1*01:03:01-DPB1*04:02  Russian Federation Vologda Region 0.4202119
 43  A*24:02:01-B*35:01:01-C*04:01:01-DRB1*04:01:01-DQA1*03:01:01-DQB1*03:01-DPA1*01:03:01-DPB1*04:01:01  Russian Federation Vologda Region 0.4202119
 44  A*02:01-B*51:01-C*14:02-DRB1*04:07-DQA1*03:01-DQB1*03:01  Kosovo 0.4030124
 45  A*11:01-B*52:01-C*14:02-DRB1*04:07-DQA1*03:01-DQB1*03:01  Kosovo 0.4030124
 46  A*23:01-B*49:01-C*07:01-DRB1*04:03-DQA1*03:01-DQB1*03:01  Kosovo 0.4030124
 47  A*69:01-B*35:03-C*12:03-DRB1*04:07-DQA1*03:01-DQB1*03:01  Kosovo 0.4030124
 48  A*02:01-B*07:02-C*07:02-DRB1*04:04-DQA1*03:01-DQB1*03:01  Brazil Puyanawa 0.3333150
 49  A*01:01:01-B*44:03:01-C*15:02:01-DRB1*11:04:01-DQA1*03:01:01-DQB1*03:01-DPA1*01:03:01-DPB1*04:01  Russia Belgorod region 0.3268153
 50  A*02:01:01-B*35:01:01-C*15:13-DRB1*13:03:01-DQA1*03:01:01-DQB1*03:01-DPA1*01:03:01-DPB1*04:02  Russia Belgorod region 0.3268153
 51  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
 52  A*02:05-B*41:01-C*17:01-DRB1*11:01-DQA1*03:01-DQB1*03:01-DPB1*01:01  South Africa Worcester 0.3000159
 53  A*24:02-B*15:10-C*12:02-DRB1*11:01-DQA1*03:01-DQB1*03:01-DPB1*02:01  South Africa Worcester 0.3000159
 54  A*30:04-B*15:10-C*04:01-DRB1*12:01-DQA1*03:01-DQB1*03:01-DPB1*04:01  South Africa Worcester 0.3000159
 55  A*02:01-B*37:01-C*06:02-DRB1*04:01-DQA1*03:01-DQB1*03:01-DPB1*17:01  USA San Diego 0.2600496
 56  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
 57  A*02:01-B*51:01-C*02:02-DRB1*09:01-DQA1*03:01-DQB1*03:01-DPB1*04:01  USA San Diego 0.2600496
 58  A*02:03-B*54:01-C*03:17-DRB1*04:05-DQA1*03:01-DQB1*03:01-DPB1*02:01  USA San Diego 0.2600496
 59  A*02:05-B*51:01-C*01:02-DRB1*13:01-DQA1*03:01-DQB1*03:01-DPB1*04:01  USA San Diego 0.2600496
 60  A*24:02-B*40:01-C*04:01-DRB1*12:01-DQA1*03:01-DQB1*03:01-DPB1*05:01  USA San Diego 0.2600496
 61  A*24:02-B*51:01-C*07:02-DRB1*04:07-DQA1*03:01-DQB1*03:01-DPB1*05:01  USA San Diego 0.2600496
 62  A*24:02-B*57:01-C*08:01-DRB1*12:01-DQA1*03:01-DQB1*03:01-DPB1*05:01  USA San Diego 0.2600496
 63  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
 64  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
 65  A*02:01-B*39:05-C*01:02-DRB1*04:07-DQA1*03:01-DQB1*03:01-DPB1*04:01  Nicaragua Managua 0.2165339
 66  A*02:01-B*39:05-C*02:02-DRB1*14:06-DQA1*03:01-DQB1*03:01-DPB1*01:01  Nicaragua Managua 0.2165339
 67  A*03:01-B*07:02-C*01:02-DRB1*04:07-DQA1*03:01-DQB1*03:01-DPB1*15:01  Nicaragua Managua 0.2165339
 68  A*23:01-B*51:01-C*15:02-DRB1*04:04-DQA1*03:01-DQB1*03:01-DPB1*04:01  Nicaragua Managua 0.2165339
 69  A*68:01-B*39:05-C*07:02-DRB1*11:04-DQA1*03:01-DQB1*03:01-DPB1*04:02  Nicaragua Managua 0.2165339
 70  A*68:03-B*35:01-C*07:02-DRB1*04:07-DQA1*03:01-DQB1*03:01-DPB1*03:01  Nicaragua Managua 0.2165339
 71  A*68:05-B*15:30-C*01:02-DRB1*04:04-DQA1*03:01-DQB1*03:01-DPB1*04:02  Nicaragua Managua 0.2165339
 72  DRB1*04:01-DQA1*03:01-DQB1*03:01  USA European American 0.11001,899
 73  A*01-B*37-DRB1*04:02-DQA1*03:01-DQB1*03:01  Brazil Paraná Caucasian 0.0780641
 74  A*02-B*51-DRB1*11:02-DQA1*03:01-DQB1*03:01  Brazil Paraná Caucasian 0.0780641
 75  A*02-B*58-DRB1*04:01-DQA1*03:01-DQB1*03:01  Brazil Paraná Caucasian 0.0780641
 76  A*03-B*27-DRB1*04:01-DQA1*03:01-DQB1*03:01  Brazil Paraná Caucasian 0.0780641
 77  A*03-B*51-DRB1*04:01-DQA1*03:01-DQB1*03:01  Brazil Paraná Caucasian 0.0780641
 78  A*11-B*44-DRB1*15:03-DQA1*03:01-DQB1*03:01  Brazil Paraná Caucasian 0.0780641
 79  A*23-B*35-DRB1*04:02-DQA1*03:01-DQB1*03:01  Brazil Paraná Caucasian 0.0780641
 80  A*24-B*35-DRB1*04:01-DQA1*03:01-DQB1*03:01  Brazil Paraná Caucasian 0.0780641
 81  A*29-B*53-DRB1*04:05-DQA1*03:01-DQB1*03:01  Brazil Paraná Caucasian 0.0780641
 82  A*02:01-B*52:01-C*12:02-DRB1*04:01-DQA1*03:01-DQB1*03:01-DPB1*05:01  Sri Lanka Colombo 0.0700714
 83  A*02:01-B*56:01-C*01:02-DRB1*04:01-DQA1*03:01-DQB1*03:01-DPB1*01:01  Sri Lanka Colombo 0.0700714
 84  A*02:11-B*35:01-C*04:01-DRB1*04:08-DQA1*03:01-DQB1*03:01-DPB1*04:02  Sri Lanka Colombo 0.0700714
 85  A*02:11-B*51:06-C*14:02-DRB1*04:08-DQA1*03:01-DQB1*03:01-DPB1*04:01  Sri Lanka Colombo 0.0700714
 86  A*03:01-B*52:01-C*12:02-DRB1*04:01-DQA1*03:01-DQB1*03:01-DPB1*04:01  Sri Lanka Colombo 0.0700714
 87  A*11:01-B*40:06-C*14:02-DRB1*04:01-DQA1*03:01-DQB1*03:01-DPB1*04:02  Sri Lanka Colombo 0.0700714
 88  A*11:01-B*51:06-C*14:02-DRB1*14:04-DQA1*03:01-DQB1*03:01-DPB1*15:01  Sri Lanka Colombo 0.0700714
 89  A*33:03-B*58:01-C*03:02-DRB1*04:01-DQA1*03:01-DQB1*03:01-DPB1*09:01  Sri Lanka Colombo 0.0700714
 90  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
 91  A*11:01-B*55:02-C*01:02-DRB1*09:01-DQA1*03:01-DQB1*03:01-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 92  A*31:01-B*56:01-C*04:01-DRB1*09:01-DQA1*03:01-DQB1*03:01-DPA1*02:01-DPB1*13:01  Japan pop 17 0.03003,078

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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