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 : 
Region:  Ethnic Origin:     Type of study :  Sort by: 
Sample Size:      Sample Year:     Loci Tested: 
Displaying 1 to 100 (from 3,461) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 35  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  DPA1*01:03-DPB1*02:01  Papua New Guinea Highland pop2 35.900028
 2  DPA1*01:03:01-DPB1*02:01:02  Tokelau 32.000050
 3  DPA1*01:03-DPB1*02:01  Russia Tuva pop 2 26.9000169
 4  DPA1*01:03:01-DPB1*02:01:02  Cook Islands 26.000050
 5  DPA1*01:03:01-DPB1*02:01:02  Tonga 24.000050
 6  DPA1*01:03-DPB1*02:01  Japan Fukuoka 19.200086
 7  DPA1*01:03:01-DPB1*02:01:02  Samoa pop2 19.000050
 8  DRB1*16:02:01-DPB1*02:01  Taiwan Orchid Island Yami 18.000050
 9  A*11-B*15-C*08-DRB1*12-DQB1*03-DPB1*02  Myanmar Kayin 16.771044
 10  DPA1*01:03-DPB1*02:01  India Bombay 16.100059
 11  DPA1*01:03-DPB1*02:01  Ecuador African 14.700058
 12  DPA1*01:03-DPB1*02:01  Gambia 12.7000146
 13  DPA1*01:03-DPB1*02:01  Uganda Baganda 11.700047
 14  DPA1*01:03-DPB1*02:01  Cameroon Saa 11.2000172
 15  DPA1*01:03-DPB1*02:01  France Ceph 10.5000124
 16  DRB1*15-DQB1*06:02-DPB1*02:01  Congo Kinshasa Bantu 10.000090
 17  DPA1*01:03-DPB1*02:02  Spain Navarre Basques 9.5000116
 18  A*24-B*15-C*04-DRB1*15-DQB1*05-DPB1*02  Myanmar Kayin 8.946044
 19  DRB1*12:02:01-DQB1*03:01:01/03:09-DPB1*02:01:02  China Yunnan Province Bai 8.2000128
 20  DRB1*11:01:01-DPB1*02:01  Taiwan Paiwan pop 2 7.600050
 21  DPA1*01:03-DPB1*02:01  Spain Navarre Basques 6.8000116
 22  DRB1*03:01-DQA1*05:01-DPA1*01:03-DPB1*02:02  Spain Gipuzkoa Basque 6.5000100
 23  DRB1*14:02-DQB1*03:01-DPB1*02:01:02  Mexico Chihuahua Tarahumara 5.700044
 24  DQB1*03:01-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 4.9170496
 25  A*11-B*15-C*04-DRB1*15-DQB1*05-DPB1*02  Myanmar Kayin 4.449044
 26  DRB1*04:06-DQA1*03:01-DQB1*03:02-DPB1*02:01  South Korea pop 11 4.4000149
 27  DRB1*11:01:01-DPB1*02:01:02  Taiwan Puyuma pop 2 4.300050
 28  DPA1*01:03-DPB1*02:01  Ecuador Cayapa 4.2000183
 29  DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*02:01  South Korea pop 11 4.0000149
 30  DRB1*09:01-DQA1*03:02-DQB1*03:03-DPB1*02:01  South Korea pop 11 3.9000149
 31  DQB1*03:03-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 3.7390496
 32  A*11-B*15-C*04-DRB1*04-DQB1*03-DPB1*02  Myanmar Kayin 3.514044
 33  DPA1*02:02:02-DPB1*02:01  Japan Fukuoka 3.500086
 34  A*24-B*15-C*08-DRB1*14-DQB1*05-DPB1*02  Myanmar Kayin 3.409044
 35  A*02:01:01/02:01:09-B*40:02-C*03:04-DRB1*14:02-DQB1*03:01-DPB1*02:01:02  Mexico Chihuahua Tarahumara 3.400044
 36  DRB1*04:06-DQA1*03:01-DQB1*03:02-DPB1*02:01  South Korea pop 1 3.4000324
 37  DRB1*04:06-DQB1*03:02-DPB1*02:01  South Korea pop 1 3.4000324
 38  DRB1*09:01:02-DQB1*03:03-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 3.1810496
 39  DRB1*09:01:02-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 3.0980496
 40  DRB1*04:06-DQA1*03:01-DQB1*03:02-DPB1*02:01  South Korea pop 2 3.0000207
 41  DRB1*15-DRB5*01-DQA1*01-DQB1*06-DPB1*02  USA San Francisco Caucasian 3.0000220
 42  DPA1*02:02:02-DPB1*02:02  Japan Fukuoka 2.900086
 43  DRB1*09:01-DQA1*03:02-DQB1*03:03-DPB1*02:01  South Korea pop 1 2.9000324
 44  DRB1*09:01-DQB1*03:03-DPB1*02:01  Mongolia Tarialan Khoton 2.900085
 45  DRB1*04:05-DPA1*01-DPB1*02:01  Mongolia Tarialan Khoton 2.800085
 46  DRB1*09:01-DQB1*03:03-DPB1*02:01  South Korea pop 1 2.8000324
 47  DRB1*09:01-DPA1*01-DPB1*02:01  Mongolia Tarialan Khoton 2.700085
 48  DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*02:01  South Korea pop 2 2.7000207
 49  A*02:07-B*46:01-C*01:02:01-DRB1*08:03:02-DQB1*06:01:01-DPB1*02:02  China Yunnan Province Nu 2.6000107
 50  A*11:01:01-B*15:25-C*04:03-DRB1*15:01:01-DQB1*05:02:01-DPB1*02:01:02  China Yunnan Province Nu 2.6000107
 51  A*11:03-B*52:01:01-C*07:02:01-DRB1*11:06-DQB1*03:01:01-DPB1*02:01:02  China Yunnan Province Nu 2.6000107
 52  DRB1*12:02:01-DQB1*03:01:01-DPB1*02:01:02  China Lijiang Naxi 2.6000100
 53  DRB1*15:01-DQB1*06:02-DPB1*02:01  South Korea pop 1 2.6000324
 54  DQB1*03:02-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 2.5840496
 55  DRB1*15:01:01:01-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 2.5040496
 56  DRB1*09:01:02-DQA1*03:02-DQB1*03:03:02-DPB1*02:01  South Korea pop 2 2.5000207
 57  DRB1*09:01-DQA1*03:01-DQB1*03:03-DPB1*02:01  China Canton Han 2.5000264
 58  DRB1*04:05-DQB1*04:01-DPB1*02:01  Mongolia Tarialan Khoton 2.400085
 59  DRB1*09:01-DPA1*01-DPB1*02:01  Mongolia Ulaanbaatar Khalkha 2.400041
 60  DRB1*11-DRB3*02-DQA1*05-DQB1*03-DPB1*02  USA San Francisco Caucasian 2.4000220
 61  DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*02:01  South Korea pop 1 2.4000324
 62  A*23:01:01-B*41:01:01-C*06:02:01-DRB1*12:01:01-DQB1*06:02:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Barra Mansa Rio State Black 2.381073
 63  A*23:01:01-B*44:03:01-C*04:01:01-DRB1*04:05:01-DQB1*06:04:01-DPA1*02:01:01-DPB1*02:01:02  Brazil Barra Mansa Rio State Black 2.381073
 64  DRB1*11:01-DQB1*03:01-DPB1*02:01  Greece pop3 2.3000246
 65  DRB1*13:01-DQB1*06:03-DPB1*02:01  Greece pop3 2.3000246
 66  DRB1*13:02-DQB1*06:05-DPB1*02:01  South Korea pop 1 2.3000324
 67  DRB1*16:01-DQB1*05:02-DPB1*02:01  Greece pop3 2.3000246
 68  A*11-B*38-C*07-DRB1*15-DQB1*05-DPB1*02  Myanmar Kayin 2.273044
 69  DQB1*02:01-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 2.2100496
 70  DRB1*04:03-DQA1*03:01-DQB1*03:02-DPB1*02:01  China Canton Han 2.2000264
 71  DRB1*11:01:01-DPB1*02:01:02  Taiwan Saisiat pop 2 2.200050
 72  DRB1*13:02-DQA1*01:02-DQB1*06:05-DPB1*02:01  South Korea pop 1 2.2000324
 73  DRB1*16:02:01-DPB1*02:01:02  Taiwan Saisiat pop 2 2.200050
 74  DRB1*09:01-DQA1*03:01-DQB1*03:03-DPB1*02:02  China Canton Han 2.1000264
 75  DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  South Korea pop 11 2.1000149
 76  DRB1*15:01-DRB5*01:01-DQA1*01:02-DQB1*06:02-DPB1*02:01  USA San Francisco Caucasian 2.1000220
 77  DRB1*15:01-DRB5*01:01-DQA1*01:02-DQB1*06:02-DPB1*02:01  USA San Francisco Caucasian 2.1000220
 78  DQB1*05:01-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 2.0360496
 79  DRB1*11:01:01-DPB1*02:01  Taiwan Rukai pop 2 2.000050
 80  DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*02:01  South Korea pop 11 2.0000149
 81  DRB1*12:01:01-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 1.9400496
 82  DQB1*06:02-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 1.9260496
 83  DRB1*11:01:01-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 1.9210496
 84  DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*01:03-DPB1*02:01  China Zhejiang Han pop 2 1.9200833
 85  DRB1*12:01-DQB1*03:01-DPB1*02:01  South Korea pop 1 1.9000324
 86  DRB1*04:05:01-DQB1*03:01:01-DPB1*02:01:02  China Lijiang Naxi 1.8000100
 87  DRB1*12:02:01-DQB1*05:02-DPB1*02:01:02  China Lijiang Naxi 1.8000100
 88  DRB1*15:04-DQB1*05:02-DPB1*02:02  China Lijiang Naxi 1.8000100
 89  A*23:01:01-B*44:03:01-C*04:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Parda 1.7647170
 90  DRB1*03:01:01:01-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 1.7460496
 91  DRB1*11:01:01-DQB1*03:01-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 1.7130496
 92  DRB1*12:01:01-DQB1*03:01-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 1.7020496
 93  DPA1*02:02:02-DPB1*02:01  India Bombay 1.700059
 94  DRB1*01:01-DQA1*01:01-DQB1*05:01-DPB1*02:01  South Korea pop 2 1.7000207
 95  DRB1*08:03-DQA1*01:03-DQB1*06:01-DPB1*02:01  South Korea pop 2 1.7000207
 96  DRB1*13:02-DQA1*01:02-DQB1*06:04-DPB1*02:01  South Korea pop 11 1.7000149
 97  DRB1*15:01:01:01-DQB1*06:02-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 1.6880496
 98  DRB1*07:01-DQB1*02:01-DPB1*02:01  Greece pop3 1.6000246
 99  DRB1*11:01-DQA1*05:01-DQB1*03:01-DPB1*02:01  China Canton Han 1.6000264
 100  DRB1*15:01-DQB1*06:02-DPB1*02:01  Ireland South 1.6000250

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 3,461) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 35  


   

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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