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 104) records   Pages: 1 2 of 2  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*02-B*57-DRB1*11-DQB1*03:01  Mexico Veracruz, Poza Rica 2.222245
 2  A*02:01-B*57:03-DRB1*11:03-DQB1*03:01  Chile Mapuche 1.540066
 3  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*11:01:01-DQB1*03:01:01  India Karnataka Kannada Speaking 0.8620174
 4  A*02-B*57-DRB1*11-DQB1*03:01  Mexico Sinaloa Rural 0.5464183
 5  A*01-B*57-DRB1*11-DQB1*03:01  Mexico Veracruz, Xalapa 0.5348187
 6  A*34:02-B*57:03-C*07:01-DRB1*11:02-DQA1*05:01-DQB1*03:01-DPB1*04:02  Kenya, Nyanza Province, Luo tribe 0.5000100
 7  A*02:01-B*57:01-C*06:02-DRB1*11:01-DQA1*05:05-DQB1*03:01  Kosovo 0.4030124
 8  A*68-B*57-DRB1*11-DQB1*03:01  Mexico Mexico City Metropolitan Area Rural 0.3289150
 9  A*24:02-B*57:02-C*07:01-DRB1*11:14-DQA1*05:05-DQB1*03:01-DPB1*11:01  South Africa Worcester 0.3000159
 10  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*11:01:01-DQB1*03:01:01  India Kerala Malayalam speaking 0.2810356
 11  A*24:02:13-B*57:01:01-C*06:02:01-DRB1*11:01:01-DQB1*03:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 12  A*68-B*57-DRB1*11-DQB1*03:01  Mexico Yucatan, Merida 0.2564192
 13  A*02:01:01-B*57:01:01-C*07:01:01-DRB1*11:01:01-DQB1*03:01:01  Spain, Canary Islands, Gran canaria island 0.2300215
 14  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*11:01:01-DQB1*03:01:01-DPA1*02:01:04-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 15  A*33:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  Malaysia Peninsular Indian 0.1845271
 16  A*26-B*57-DRB1*11:01-DQA1*05:05-DQB1*03:01  Brazil Paraná Caucasian 0.1560641
 17  A*01:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  Italy pop 5 0.1400975
 18  A*01:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  Germany DKMS - Italy minority 0.12901,159
 19  A*01:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  India West UCBB 0.10665,829
 20  A*01:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  India North UCBB 0.10145,849
 21  A*01:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  India South UCBB 0.099411,446
 22  A*03-B*57-DRB1*11-DQB1*03:01  Mexico Veracruz Rural 0.0924539
 23  A*01:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  India Central UCBB 0.09054,204
 24  A*01-B*57-DRB1*11:01-DQA1*05:05-DQB1*03:01  Brazil Paraná Caucasian 0.0780641
 25  A*11-B*57-DRB1*11:01-DQA1*05:05-DQB1*03:01  Brazil Paraná Caucasian 0.0780641
 26  A*02-B*57-DRB1*11-DQB1*03:01  Mexico Puebla, Puebla city 0.07521,994
 27  A*24:02-B*57:01-C*04:01-DRB1*11:01-DQA1*02:01-DQB1*03:01-DPB1*26:01  Sri Lanka Colombo 0.0700714
 28  A*01:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 29  A*03:01:01:01-B*57:01:01-C*06:02:01:01-DRB1*11:01:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.06621,510
 30  A*30:02-B*57:03-C*18:01-DRB1*11:02-DQB1*03:01  USA African American pop 4 0.06502,411
 31  A*23-B*57-DRB1*11-DQB1*03:01  Mexico Tlaxcala Rural 0.0602830
 32  A*31-B*57-DRB1*11-DQB1*03:01  Mexico Tlaxcala Rural 0.0602830
 33  A*02:01-B*57:01-C*06:02-DRB1*11:03-DQB1*03:01-DPB1*03:01  Russia Karelia 0.05641,075
 34  A*01:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  India Tamil Nadu 0.05142,492
 35  A*33:03-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  India East UCBB 0.05032,403
 36  A*68:01-B*57:03-C*07:01-DRB1*11:01-DQB1*03:01  USA Hispanic pop 2 0.04701,999
 37  A*01:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  USA Asian pop 2 0.04401,772
 38  A*02:02-B*57:03-C*07:01-DRB1*11:03-DQB1*03:01  USA African American pop 4 0.04402,411
 39  A*24:02-B*57:01-C*06:02-DRB1*11:04-DQB1*03:01  Germany DKMS - Italy minority 0.04401,159
 40  A*02:01-B*57:03-C*07:01-DRB1*11:03-DQB1*03:01  Germany DKMS - Italy minority 0.04301,159
 41  A*01:01-B*57:01-C*06:02-DRB1*11:04-DQB1*03:01  Germany DKMS - Turkey minority 0.04204,856
 42  A*30-B*57-DRB1*11-DQB1*03:01  Mexico Jalisco, Guadalajara city 0.04191,189
 43  A*11:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  India Tamil Nadu 0.03982,492
 44  A*29:01-B*57:03-C*07:01-DRB1*11:01-DQB1*03:01  Germany DKMS - Turkey minority 0.03904,856
 45  A*01:01-B*57:03-C*07:01-DRB1*11:02-DQB1*03:01  Colombia Bogotá Cord Blood 0.03421,463
 46  A*02:01-B*57:03-C*07:01-DRB1*11:03-DQB1*03:01  Colombia Bogotá Cord Blood 0.03421,463
 47  A*30:02-B*57:02-C*18:01-DRB1*11:04-DQB1*03:01  Colombia Bogotá Cord Blood 0.03421,463
 48  A*02:01-B*57:01-C*06:02-DRB1*11:03-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 49  A*02:01-B*57:03-C*07:01-DRB1*11:01-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 50  A*03:01-B*57:03-C*07:01-DRB1*11:03-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 51  A*02:01:01-B*57:01:01-C*06:02:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.028323,595
 52  A*01:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  India East UCBB 0.02632,403
 53  A*03:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  India North UCBB 0.02565,849
 54  A*01-B*57-DRB1*11-DQB1*03:01  Mexico Puebla, Puebla city 0.02511,994
 55  A*68:01-B*57:01-C*06:02-DRB1*11:04-DQB1*03:01  Germany DKMS - Turkey minority 0.02404,856
 56  A*68:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  India Central UCBB 0.02384,204
 57  A*01:01-B*57:01-C*06:02-DRB1*11:04-DQB1*03:01  India East UCBB 0.02242,403
 58  A*02:06-B*57:01-C*06:02-DRB1*11:04-DQB1*03:01  India East UCBB 0.02082,403
 59  A*01:01-B*57:01-C*06:02-DRB1*11:06-DQB1*03:01  India Tamil Nadu 0.02012,492
 60  A*02:01:01-B*57:01:01-C*06:02:01-DRB1*11:04:01-DQB1*03:01:01  Poland BMR 0.017923,595
 61  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*11:04:01-DQB1*03:01:01  Poland BMR 0.017723,595
 62  A*01:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01-DPB1*04:01  Germany DKMS - German donors 0.01593,456,066
 63  A*02:01-B*57:01-C*06:02-DRB1*11:04-DQB1*03:01  Germany DKMS - Turkey minority 0.01404,856
 64  A*11:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  India South UCBB 0.013711,446
 65  A*26:01-B*57:01-C*06:02-DRB1*11:04-DQB1*03:01  India Central UCBB 0.01284,204
 66  A*24:02-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  India Central UCBB 0.01274,204
 67  A*02:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  India Central UCBB 0.01214,204
 68  A*11:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  India Central UCBB 0.01194,204
 69  A*31:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  India Central UCBB 0.01194,204
 70  A*32:01-B*57:01-C*12:02-DRB1*11:01-DQB1*03:01  India Central UCBB 0.01194,204
 71  A*68:01-B*57:01-C*06:02-DRB1*11:11-DQB1*03:01  India Central UCBB 0.01194,204
 72  A*33:03-B*57:01-C*06:02-DRB1*11:04-DQB1*03:01  India Central UCBB 0.01104,204
 73  A*11:01-B*57:01-C*06:02-DRB1*11:04-DQB1*03:01  India North UCBB 0.01075,849
 74  A*68:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  India West UCBB 0.01015,829
 75  A*01:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01-DPB1*02:01  Germany DKMS - German donors 0.01013,456,066
 76  A*01:01-B*57:01-C*06:02-DRB1*11:03-DQB1*03:01  Germany DKMS - Turkey minority 0.01004,856
 77  A*24:02-B*57:01-C*06:02-DRB1*11:04-DQB1*03:01  Germany DKMS - Turkey minority 0.01004,856
 78  A*11:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  India West UCBB 0.00915,829
 79  A*01:01-B*57:01-C*06:02-DRB1*11:04-DQB1*03:01  India West UCBB 0.00865,829
 80  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*11:03:01-DQB1*03:01:01  Poland BMR 0.006023,595
 81  A*68:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  India South UCBB 0.005811,446
 82  A*32:01:01-B*57:01:01-C*06:02:01-DRB1*11:04:01-DQB1*03:01:01  Poland BMR 0.005523,595
 83  A*01:01-B*57:01-C*06:02-DRB1*11:04-DQB1*03:01  India South UCBB 0.004811,446
 84  A*24:02-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  India South UCBB 0.004711,446
 85  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.004623,595
 86  A*02:03-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  India South UCBB 0.004411,446
 87  A*02:11-B*57:01-C*06:02-DRB1*11:06-DQB1*03:01  India South UCBB 0.004411,446
 88  A*32:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  India South UCBB 0.004411,446
 89  A*03:02:01-B*57:01:01-C*06:02:01-DRB1*11:04:01-DQB1*03:01:01  Poland BMR 0.004223,595
 90  A*68:01:01-B*57:01:01-C*06:02:01-DRB1*11:03:01-DQB1*03:01:01  Poland BMR 0.004223,595
 91  A*02:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  India South UCBB 0.004011,446
 92  A*24:02:01-B*57:01:01-C*06:02:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.003923,595
 93  A*11:01-B*57:01-C*06:02-DRB1*11:04-DQB1*03:01  India South UCBB 0.003911,446
 94  A*26:01-B*57:01-C*06:02-DRB1*11:01-DQB1*03:01  India South UCBB 0.003511,446
 95  A*02:05:01-B*57:03:01-C*07:01:02-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.002123,595
 96  A*03:02:01-B*57:01:01-C*06:02:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.002123,595
 97  A*23:48-B*57:01:01-C*06:02:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.002123,595
 98  A*30:04:01-B*57:03:01-C*07:01:02-DRB1*11:04:01-DQB1*03:01:01  Poland BMR 0.002123,595
 99  A*02:01:01-B*57:01:01-C*06:02:01-DRB1*11:12:01-DQB1*03:01:01  Poland BMR 0.002123,595
 100  A*02:01:01-B*57:03:01-C*07:01:02-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.002123,595

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 104) 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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