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 3,437) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 35  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  DQA1*02:01-DQB1*02:02  Tunisia 25.7000100
 2  DRB1*07:01-DQB1*02:02  Tunisia 19.5000100
 3  DRB1*07:01-DQA1*02:01-DQB1*02:02  Morocco Settat Chaouya 16.700098
 4  DRB1*07:01-DQA1*02:01-DQB1*02:02  Spain Las Alpujarras 12.940085
 5  DRB1*07:01-DQA1*02:01-DQB1*02:02  USA European American 11.08001,899
 6  DRB1*07:01-DQA1*02:01-DQB1*02:02  Tunisia 10.2000100
 7  DRB1*07-DQA1*02:01-DQB1*02:02  Croatia Gorski Kotar Region 9.400063
 8  DRB1*07:01-DQA1*02:01-DQB1*02:02  USA San Francisco Caucasian 8.9000220
 9  DRB1*07-DQA1*02:01-DQB1*02:02  Czech Republic pop 3 8.3000180
 10  DQA1*02:01-DQB1*02:02  Belgium pop 2 7.8000715
 11  DRB1*07:01-DQB1*02:02  Mexico Mexico City Mestizo population 7.6923143
 12  DRB1*07:01-DQA1*02:01-DQB1*02:02  South Korea pop 5 6.6000467
 13  DRB1*07:01:01:01-DQB1*02:02  China Inner Mongolia Autonomous Region Northeast 6.5520496
 14  DRB1*07:01-DQB1*02:02  Taiwan pop 2 6.5000364
 15  DRB1*07:01-DQB1*02:02  Mexico Mexico City Mestizo pop 2 5.9800234
 16  DRB1*03:01-DQB1*02:02-DPB1*04:01  Mongolia Ulaanbaatar Khalkha 5.600041
 17  DRB1*07:01:01-DQB1*02:02  India Mumbai Maratha 5.420091
 18  A*33:03-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India East UCBB 5.40472,403
 19  A*29-B*44-DRB1*07:01-DRB4*01:01-DQA1*02:01-DQB1*02:02  Spain Murcia 5.1000173
 20  DRB1*07:01-DQA1*02:01-DQB1*02:02  South Korea pop 1 4.9000324
 21  DRB1*03:01-DQB1*02:02  Cretan Islanders 4.8317124
 22  DRB1*07:01-DQB1*02:02  Italy pop 5 4.4900975
 23  DRB1*07:01-DQA1*02:01-DQB1*02:02  Cameroon Yaounde 4.400092
 24  A*29-B*39-DRB1*07:01-DQB1*02:02  Tunisia Ghannouch 4.300082
 25  A*29:02-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Tunisia 4.0000100
 26  DRB1*03:01-DQA1*05:01-DQB1*02:02  Tunisia 4.0000100
 27  DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*02:01  South Korea pop 11 4.0000149
 28  A*29:02-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Colombia North Wiwa El Encanto 3.846252
 29  A*33:03-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India Northeast UCBB 3.7162296
 30  A*24-B*07-DRB1*07:01-DQB1*02:02  Tunisia Ghannouch 3.700082
 31  A*02:01:01:01-B*13:02:01-C*06:02:01:01-DRB1*07:01:01:01-DQB1*02:02  Russia Bashkortostan, Tatars 3.6238192
 32  A*29:02-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 3.42004,335
 33  A*02:01:01:01-B*13:02:01-C*06:02:01:01-DRB1*07:01:01:01-DQB1*02:02  Russia Bashkortostan, Bashkirs 3.3333120
 34  A*02:01:01-B*13:02:01-C*06:02:01:01-DRB1*07:01-DQB1*02:02  Russia Bashkortostan, Bashkirs 3.3333120
 35  B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Mexico Mexico City Mestizo population 3.1469143
 36  A*25-B*13-DRB1*07-DQA1*02-DQB1*02:02  Russia, South Ural, Chelyabinsk region, Nagaybaks 3.1200112
 37  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  China Zhejiang Han 3.11091,734
 38  A*01:01-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  Tunisia 3.0000100
 39  A*02:01-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Tunisia 3.0000100
 40  A*02:01-B*50:01-C*06:02-DRB1*07:01-DQB1*02:02  Tunisia 3.0000100
 41  B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Ireland South 3.0000250
 42  A*02:01:01-B*50:01-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02  Morocco Atlantic Coast Chaouya 2.900098
 43  A*02:01-B*50:01-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02  United Arab Emirates Abu Dhabi 2.880052
 44  A*29:02-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Mexico Mexico City Mestizo population 2.7972143
 45  A*33:03-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India West UCBB 2.79385,829
 46  A*02:01-B*50:01-DRB1*07:01-DQB1*02:02  Tunisia Gabes 2.630095
 47  A*33:03-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India Central UCBB 2.58154,204
 48  A*23:01-B*44:03-C*04:01-DRB1*07:01-DQA1*02:01-DQB1*02:02  Kosovo 2.4190124
 49  A*02-B*44-DRB1*07:01-DQB1*02:02  Tunisia Ghannouch 2.400082
 50  DRB1*07:01-DRB4*01:01-DQA1*02:01-DQB1*02:02-DPB1*04:01  USA San Francisco Caucasian 2.4000220
 51  DRB1*07:01-DRB4*01:01-DQA1*02:01-DQB1*02:02-DPB1*04:01  USA San Francisco Caucasian 2.4000220
 52  A*33:03-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India South UCBB 2.381211,446
 53  A*01:01:01-B*08:01:01-C*07:01:01-DRB1*03:01:01-DQB1*02:02:01-DPA1*02:01:01-DPB1*01:01:01  Brazil Barra Mansa Rio State Black 2.381073
 54  A*02:01:01-B*44:03:01-C*15:05:02-DRB1*07:01:01-DQB1*02:02:01-DPA1*02:01:01-DPB1*13:01:01  Brazil Barra Mansa Rio State Black 2.381073
 55  A*03:01:01-B*07:06:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*02:01:04-DPB1*11:01:01  Brazil Barra Mansa Rio State Black 2.381073
 56  DRB1*07:01-DQA1*02:01-DQB1*02:02-DPA1*02:01-DPB1*17:01  China Zhejiang Han pop 2 2.3340833
 57  DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*13:01  South Korea pop 2 2.2000207
 58  A*33:03-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India North UCBB 2.18365,849
 59  A*29-B*44-DRB1*07:01-DQA1*02:01-DQB1*02:02  Brazil Paraná Caucasian 2.1611641
 60  DRB1*07:01-DQB1*02:02-DPB1*13:01  South Korea pop 1 2.1000324
 61  DRB1*07:01:01:01-DQB1*02:02-DPB1*19:01  China Inner Mongolia Autonomous Region Northeast 2.0700496
 62  DQB1*02:02-DPB1*19:01  China Inner Mongolia Autonomous Region Northeast 2.0270496
 63  B*14:01-C*08:02-DRB1*07:01-DQB1*02:02  Ireland South 2.0000250
 64  DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*13:01  South Korea pop 1 2.0000324
 65  DRB1*07:01-DQB1*02:02  Sweden Southern Sami 2.0000130
 66  A*02:11-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India North UCBB 1.89865,849
 67  A*29:02:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01  Spain, Canary Islands, Gran canaria island 1.8600215
 68  A*02:11-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India Northeast UCBB 1.8581296
 69  A*29:02-B*44:03-C*16:01-DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*11:01  USA San Diego 1.8230496
 70  A*02-B*50-DRB1*07:01-DQB1*02:02  Tunisia Ghannouch 1.800082
 71  DRB1*07:01-DRB4*01:01-DQA1*02:01-DQB1*02:02-DPB1*17:01  USA San Francisco Caucasian 1.8000220
 72  DRB1*07:01-DRB4*01:01-DQA1*02:01-DQB1*02:02-DPB1*17:01  USA San Francisco Caucasian 1.8000220
 73  A*30-B*50-DRB1*07-DQA1*02-DQB1*02:02  Russia, South Ural, Chelyabinsk region, Nagaybaks 1.7900112
 74  A*02:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 1.775923,595
 75  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
 76  A*33:03:01-B*44:03:02-C*07:01:01-DRB1*07:01:01-DQB1*02:02:01  India Karnataka Kannada Speaking 1.7240174
 77  DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*17:01  South Korea pop 2 1.7000207
 78  DRB1*07:01-DQB1*02:02-DPB1*04:01  Ireland South 1.7000250
 79  A*02:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DQA1*02:01:01-DQB1*02:02-DPA1*01:03:01-DPB1*04:01:01  Russia Belgorod region 1.6340153
 80  A*33:03:01-B*44:03:02-C*07:01:01-DRB1*07:01:01-DQB1*02:02:01  India Kerala Malayalam speaking 1.6150356
 81  A*26:01-B*13:02-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02  Kosovo 1.6130124
 82  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:02  Italy pop 5 1.6000975
 83  DRB1*07:01-DQB1*02:02-DPB1*11:01  Ireland South 1.6000250
 84  DRB1*13:03-DQA1*02:01-DQB1*02:02  Cameroon Yaounde 1.600092
 85  A*02:01:01:01-B*13:02:01-C*06:02:01:01-DRB1*07:01:01-DQB1*02:02  Russia Nizhny Novgorod, Russians 1.57491,510
 86  A*01:01-B*50:01-DRB1*07:01-DQB1*02:02  Tunisia Gabes 1.570095
 87  A*03:01-B*50:01-DRB1*07:01-DQB1*02:02  Tunisia Gabes 1.570095
 88  A*23:01-B*50:01-DRB1*07:01-DQB1*02:02  Tunisia Gabes 1.570095
 89  A*68:02-B*44:02-DRB1*07:01-DQB1*02:02  Tunisia Gabes 1.570095
 90  A*69:01-B*44:02-DRB1*07:01-DQB1*02:02  Tunisia Gabes 1.570095
 91  A*02-B*44-DRB1*07:01-DRB4*01:01-DQA1*02:01-DQB1*02:02  Spain Murcia 1.5000173
 92  DQB1*02:02-DPB1*04:01:01  China Inner Mongolia Autonomous Region Northeast 1.4930496
 93  A*26:01-B*45:01-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02  Mexico Tixcacaltuyub Maya 1.492567
 94  DRB1*07:01:01:01-DQB1*02:02-DPB1*04:01:01  China Inner Mongolia Autonomous Region Northeast 1.4890496
 95  DRB1*09:01-DQB1*02:02-DPB1*02:01  Gambia pop 3 1.4737939
 96  A*01:01:01-B*08:01:01-C*04:01:01-DRB1*03:01:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*03:01:01  Brazil Rio de Janeiro Black 1.470668
 97  A*02:01:01-B*44:03:01-C*16:02:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Black 1.470668
 98  A*23:01:01-B*42:01:01-C*02:10:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*02:02:02-DPB1*01:01:01  Brazil Rio de Janeiro Black 1.470668
 99  A*23:01:01-B*53:01:01-C*04:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*01:01:01  Brazil Rio de Janeiro Black 1.470668
 100  A*24:02:01-B*35:01:01-C*04:01:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*03:01:01  Brazil Rio de Janeiro Black 1.470668

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 3,437) 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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