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 231) records   Pages: 1 2 3 of 3  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*74-B*35-DRB1*10-DQB1*05  Mexico Tamaulipas, Ciudad Victoria 10.869623
 2  A*68-B*35-DRB1*10:01-DQB1*05:01  Colombia San Basilio de Palenque 3.571042
 3  A*02-B*35-DRB1*10-DQB1*05  Mexico Tamaulipas, Ciudad Victoria 2.173923
 4  A*23-B*35-DRB1*10-DQB1*05  Mexico Tamaulipas, Ciudad Victoria 2.173923
 5  A*11-B*35-DRB1*10-DQB1*05  Mexico Sonora, Ciudad Obregón 1.3986143
 6  A*24:07-B*35:01-DRB1*10:01-DQB1*05:03  Iran Yazd 0.892956
 7  A*30-B*35-DRB1*10-DQB1*05  Mexico Chihuahua Chihuahua City 0.8403119
 8  A*03-B*35-DRB1*10-DQB1*05  Mexico Chiapas Rural 0.8264121
 9  A*68-B*35-DRB1*10-DQB1*05  Mexico Colima, Colima city 0.819761
 10  A*30:01-B*35:01-C*03:02-DRB1*10:01-DQB1*05:01  Iran Gorgan 0.780064
 11  A*32:01:01-B*35:02:01-C*04:01:01-DRB1*10:01:01-DQB1*05:103-DPA1*01:03:01-DPB1*04:02:01  Brazil Rio de Janeiro Parda 0.5882170
 12  A*24-B*35-DRB1*10-DQB1*05  Mexico Sinaloa Rural 0.5464183
 13  A*24-B*35-DRB1*10-DQB1*05  Mexico Nayarit, Tepic 0.515597
 14  A*03:01-B*35:01-C*04:01-DRB1*10:01-DQB1*05:01  Italy pop 5 0.4400975
 15  A*02:01-B*35:27-C*07:01-E*01:03:01-F*01:01:01-G*01:06-DRB1*10:01-DQA1*01:05-DQB1*05:01  Portugal Azores Terceira Island 0.4386130
 16  A*23-B*35-DRB1*10-DQB1*05  Mexico Tabasco Rural 0.3521142
 17  A*68-B*35-DRB1*10-DQB1*05  Mexico Sonora, Ciudad Obregón 0.3497143
 18  A*03-B*35-DRB1*10:01-DQA1*01:01-DQB1*05:01  Brazil Paraná Caucasian 0.3120641
 19  A*25-B*35-DRB1*10-DQB1*05  Mexico Veracruz, Veracruz city 0.2907171
 20  A*29:01:01-B*35:01:01-C*15:05:01-DRB1*10:01:01-DQB1*05:01:01  India Karnataka Kannada Speaking 0.2870174
 21  A*32:01:01-B*35:01:01-C*04:01:01-DRB1*10:01:01-DQB1*05:01:01  India Karnataka Kannada Speaking 0.2870174
 22  A*11-B*35-DRB1*10-DQB1*05  Mexico Sinaloa Rural 0.2732183
 23  A*23:01:01-B*35:01:01-C*07:01:01-DRB1*10:01:01-DQB1*05:01  Costa Rica Central Valley Mestizo (G) 0.2262221
 24  A*01:01-B*35:01-C*04:01-DRB1*10:01-DQA1*01:01-DQB1*05:01-DPB1*02:01  Sri Lanka Colombo 0.2101714
 25  A*02-B*35-DRB1*10-DQB1*05  Mexico Oaxaca Rural 0.2053485
 26  A*01:01-B*35:01-C*04:01-DRB1*10:02-DQB1*05:01  Malaysia Peninsular Indian 0.1845271
 27  A*01:01-B*35:05-C*04:01-DRB1*10:01-DQB1*05:01  Malaysia Peninsular Indian 0.1845271
 28  A*02:11-B*35:03-C*04:01-DRB1*10:01-DQB1*05:01  Malaysia Peninsular Indian 0.1845271
 29  A*68-B*35-DRB1*10-DQB1*05  Mexico Tlaxcala Rural 0.1807830
 30  A*03-B*35-DRB1*10-DQB1*05  Mexico Durango Rural 0.1529326
 31  A*11:01-B*35:01-DRB1*10:01-DQB1*05:01  Mexico Mexico City Tlalpan 0.1515330
 32  A*02-B*35-DRB1*10-DQB1*05  Mexico Michoacan Rural 0.1433348
 33  A*11:01-B*35:03-C*04:01-DRB1*10:01-DQA1*01:01-DQB1*05:01-DPB1*04:01  Sri Lanka Colombo 0.1401714
 34  A*33:03-B*35:03-C*12:03-DRB1*10:01-DQA1*01:01-DQB1*05:01-DPB1*09:01  Sri Lanka Colombo 0.1401714
 35  A*11:01:01-B*35:03:01-C*04:01:01-DRB1*10:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 0.1400356
 36  A*32:01-B*35:01-C*12:03-DRB1*10:01-DQB1*05:01  Italy pop 5 0.1400975
 37  A*03:01-B*35:01-C*04:01-DRB1*10:01-DQB1*05:01  USA African American pop 4 0.13102,411
 38  A*02-B*35-DRB1*10-DQB1*05  Mexico Puebla, Puebla city 0.12531,994
 39  A*02-B*35-DRB1*10-DQB1*05  Mexico Coahuila, Torreon 0.1250396
 40  A*31:01-B*35:03-C*04:01-DRB1*10:01-DQB1*05:01  India Tamil Nadu 0.11922,492
 41  A*01-B*35-DRB1*10-DQB1*05  Mexico Nuevo Leon Rural 0.1136439
 42  A*11:01-B*35:03-C*04:01-DRB1*10:01-DQB1*05:01  India West UCBB 0.10085,829
 43  A*24:02-B*35:03-C*12:03-DRB1*10:01-DQB1*05:01  India Central UCBB 0.09784,204
 44  A*03:01-B*35:01-C*04:01-DRB1*10:01-DQB1*05:01  India South UCBB 0.095511,446
 45  A*03:01-B*35:01-C*04:01-DRB1*10:01-DQB1*05:01  India West UCBB 0.09005,829
 46  A*33:03-B*35:01-C*04:01-DRB1*10:01-DQB1*05:01  USA African American pop 4 0.08702,411
 47  A*02:01-B*35:01-C*04:01-DRB1*10:01-DQB1*05:01  Germany DKMS - Italy minority 0.08601,159
 48  A*11:01-B*35:03-C*04:01-DRB1*10:01-DQB1*05:01  India North UCBB 0.08275,849
 49  A*03:01-B*35:01-C*04:01-DRB1*10:01-DQB1*05:01  India Tamil Nadu 0.08092,492
 50  A*03:01-B*35:03-C*04:01-DRB1*10:01-DQB1*05:01  India East UCBB 0.08082,403
 51  A*03:01-B*35:01-C*04:01-DRB1*10:01-DQB1*05:01  Germany DKMS - Turkey minority 0.07904,856
 52  A*02-B*35-DRB1*10:01-DQA1*01:01-DQB1*05:02  Brazil Paraná Caucasian 0.0780641
 53  A*68-B*35-DRB1*10:01-DQA1*01:01-DQB1*05:01  Brazil Paraná Caucasian 0.0780641
 54  A*01:01-B*35:01-C*04:01-DRB1*10:01-DQB1*05:01  India East UCBB 0.07542,403
 55  A*11:01-B*35:01-C*04:01-DRB1*10:01-DQA1*01:01-DQB1*05:01-DPB1*09:01  Sri Lanka Colombo 0.0700714
 56  A*24:02-B*35:03-C*07:01-DRB1*10:01-DQA1*01:01-DQB1*05:01-DPB1*09:01  Sri Lanka Colombo 0.0700714
 57  A*24:02-B*35:03-C*12:03-DRB1*10:01-DQA1*01:01-DQB1*05:01-DPB1*14:01  Sri Lanka Colombo 0.0700714
 58  A*31:01-B*35:03-C*12:03-DRB1*10:01-DQA1*01:01-DQB1*05:01-DPB1*09:01  Sri Lanka Colombo 0.0700714
 59  A*33:03-B*35:01-C*04:01-DRB1*10:01-DQA1*01:01-DQB1*05:01-DPB1*03:01  Sri Lanka Colombo 0.0700714
 60  A*02:01-B*35:03-C*04:01-DRB1*10:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.06841,463
 61  A*11:01-B*35:01-C*04:01-DRB1*10:01-DQB1*05:01  India South UCBB 0.068311,446
 62  A*03-B*35-DRB1*10-DQB1*05  Mexico Mexico City North 0.0664751
 63  A*24:02-B*35:03-C*04:01-DRB1*10:01-DQB1*05:01  India North UCBB 0.06565,849
 64  A*24:02-B*35:03-C*04:01-DRB1*10:01-DQB1*05:01  India Tamil Nadu 0.06562,492
 65  A*01:01-B*35:03-C*04:01-DRB1*10:01-DQB1*05:01  India Tamil Nadu 0.06432,492
 66  A*11:01-B*35:03-C*04:01-DRB1*10:01-DQB1*05:01  India Central UCBB 0.06414,204
 67  A*03-B*35-DRB1*10-DQB1*05  Mexico Tlaxcala Rural 0.0602830
 68  A*01:01-B*35:01-C*04:01-DRB1*10:01-DQB1*05:01  India South UCBB 0.059811,446
 69  A*24:02-B*35:02-C*04:01-DRB1*10:01-DQB1*05:01-DPB1*04:01  Russia Karelia 0.05651,075
 70  A*11:01-B*35:03-C*04:01-DRB1*10:01-DQB1*05:01  India South UCBB 0.056411,446
 71  A*24:10-B*35:01-C*04:01-DRB1*10:01-DQB1*05:02  Malaysia Peninsular Malay 0.0526951
 72  A*01:01-B*35:03-C*12:03-DRB1*10:01-DQB1*05:01  India East UCBB 0.05062,403
 73  A*30-B*35-DRB1*10-DQB1*05  Mexico Puebla, Puebla city 0.05011,994
 74  A*02:01-B*35:03-C*04:01-DRB1*10:01-DQB1*05:01  India Tamil Nadu 0.04812,492
 75  A*23:01-B*35:01-C*04:01-DRB1*10:01-DQB1*05:01  USA Hispanic pop 2 0.04701,999
 76  A*68:01-B*35:03-C*04:01-DRB1*10:01-DQB1*05:01  India West UCBB 0.04695,829
 77  A*24:02-B*35:03-C*04:01-DRB1*10:01-DQB1*05:01  USA African American pop 4 0.04402,411
 78  A*24:02-B*35:03-C*12:03-DRB1*10:01-DQB1*05:01  USA Asian pop 2 0.04401,772
 79  A*01:01-B*35:03-C*04:01-DRB1*10:01-DQB1*05:01  India South UCBB 0.043211,446
 80  A*11:01-B*35:08-C*04:01-DRB1*10:01-DQB1*05:01  Germany DKMS - Italy minority 0.04301,159
 81  A*32:01-B*35:08-C*04:01-DRB1*10:01-DQB1*05:01  Germany DKMS - Italy minority 0.04301,159
 82  A*02:11-B*35:01-C*04:01-DRB1*10:01-DQB1*05:01  India Tamil Nadu 0.04232,492
 83  A*02:01-B*35:03-C*12:03-DRB1*10:01-DQB1*05:01  India East UCBB 0.04162,403
 84  A*03:01-B*35:03-C*12:03-DRB1*10:01-DQB1*05:01  India East UCBB 0.04162,403
 85  A*03:02-B*35:03-C*04:01-DRB1*10:01-DQB1*05:01  India East UCBB 0.04162,403
 86  A*32:01-B*35:01-C*04:01-DRB1*10:01-DQB1*05:01  India East UCBB 0.04162,403
 87  A*24:02-B*35:03-C*12:03-DRB1*10:01-DQB1*05:01  India Tamil Nadu 0.04162,492
 88  A*68:01-B*35:01-C*04:01-DRB1*10:01-DQB1*05:01  India South UCBB 0.041111,446
 89  A*03:01-B*35:01-C*04:01-DRB1*10:01-DQB1*05:01  India North UCBB 0.04105,849
 90  A*24:02-B*35:03-C*04:01-DRB1*10:01-DQB1*05:01  India West UCBB 0.03965,829
 91  A*68:01-B*35:03-C*12:03-DRB1*10:01-DQB1*05:01  India South UCBB 0.039311,446
 92  A*31:01-B*35:03-C*04:01-DRB1*10:01-DQB1*05:01  India South UCBB 0.036311,446
 93  A*01:01-B*35:01-C*15:05-DRB1*10:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.03421,463
 94  A*24:02-B*35:01-C*04:01-DRB1*10:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.03421,463
 95  A*24:02-B*35:43-C*01:02-DRB1*10:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.03421,463
 96  A*30:02-B*35:01-C*04:01-DRB1*10:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.03421,463
 97  A*31:01-B*35:30-C*03:04-DRB1*10:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.03421,463
 98  A*24:02-B*35:08-C*04:01-DRB1*10:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 99  A*03:01-B*35:03-C*04:01-DRB1*10:01-DQB1*05:01  India North UCBB 0.03355,849
 100  A*11:01:01:01-B*35:01:01-C*04:01:01-DRB1*10:01:01-DQB1*05:01  Russia Nizhny Novgorod, Russians 0.03311,510

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 231) records   Pages: 1 2 3 of 3  


   

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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