Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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A B C DRB1 DPA1 DPB1 DQA1 DQB1

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Displaying 1 to 100 (from 121) records   Pages: 1 2 of 2  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*02-B*35-DRB1*09:01-DQB1*03:03  Bolivia La Paz Aymaras 5.491087
 2  A*02-B*35-DRB1*09-DQB1*03:03  Ecuador Amazonia Mixed Ancestry 2.564139
 3  A*68-B*35-DRB1*09:01-DQB1*03:03  Bolivia Quechua 2.100069
 4  A*24-B*35-DRB1*09:01-DQB1*03:03  Bolivia La Paz Aymaras 2.038087
 5  A*02-B*35-DRB1*09-DQB1*03:03  Ecuador Andes Mixed Ancestry 1.7597824
 6  A*02-B*35-DRB1*09-DQB1*03:03  Ecuador Mixed Ancestry 1.70501,173
 7  A*24-B*35-DRB1*09-DQB1*03:03  Ecuador Andes Mixed Ancestry 1.3350824
 8  A*24-B*35-DRB1*09-DQB1*03:03  Ecuador Amazonia Mixed Ancestry 1.282139
 9  A*02-B*35-DRB1*09:01-DQB1*03:03  Bolivia Quechua 1.100069
 10  A*24-B*35-DRB1*09-DQB1*03:03  Ecuador Mixed Ancestry 1.02301,173
 11  A*11-B*35-DRB1*09-DQB1*03:03  Mexico Veracruz, Cordoba 0.892956
 12  A*02:01-B*35:05-DRB1*09:01-DQB1*03:03  Peru Titikaka Lake Uros 0.5700105
 13  A*24-B*35-DRB1*09:01-DQB1*03:03  Bolivia Quechua 0.500069
 14  A*31:01:02-B*35:21-DRB1*09:01-DQB1*03:03  Peru Titikaka Lake Uros 0.4800105
 15  A*02-B*35-DRB1*09-DQB1*03:03  Mexico Chihuahua, Ciudad Juarez 0.4630106
 16  A*02:01-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  USA NMDP Alaska Native or Aleut 0.42081,376
 17  A*03:01:01:01-B*35:01:01-C*04:01:01-DRB1*09:01-DQB1*03:03:02  Russia Bashkortostan, Bashkirs 0.4167120
 18  A*02:09-B*35:03:01-C*04:01:01-DRB1*09:01:02-DQB1*03:03:02  India Karnataka Kannada Speaking 0.2870174
 19  A*32:01:01-B*35:01:01-C*04:01:01-DRB1*09:01:02-DQB1*03:03:02  Russia Bashkortostan, Tatars 0.2604192
 20  A*69:01-B*35:08:01-C*12:03:01:01-DRB1*09:01:02-DQB1*03:03:02  Russia Bashkortostan, Tatars 0.2604192
 21  A*11:01-B*35:01-C*03:03-DRB1*09:01-DQB1*03:03  Malaysia Peninsular Chinese 0.2577194
 22  A*26:01-B*35:01-C*16:02-DRB1*09:01-DQB1*03:03  Malaysia Peninsular Chinese 0.2577194
 23  A*02-B*35-DRB1*09-DQB1*03:03  Ecuador Coast Mixed Ancestry 0.2101238
 24  A*02:01-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03-DPB1*13:01  Panama 0.1900462
 25  A*24:02-B*35:01-C*03:03-DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*02:02-DPB1*05:01  Japan pop 17 0.16003,078
 26  A*02-B*35-DRB1*09-DQB1*03:03  Mexico Durango Rural 0.1529326
 27  A*24:02-B*35:01-C*03:03-DRB1*09:01-DQB1*03:03  USA Asian pop 2 0.13301,772
 28  A*02:06-B*35:01-C*03:03-DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*02:02-DPB1*05:01  Japan pop 17 0.13003,078
 29  A*24-B*35-DRB1*09-DQB1*03:03  Mexico Puebla, Puebla city 0.12531,994
 30  A*31-B*35-DRB1*09-DQB1*03:03  Ecuador Andes Mixed Ancestry 0.1214824
 31  A*24:02-B*35:30-C*03:04-DRB1*09:01-DQB1*03:03  Colombia Bogotá Cord Blood 0.11931,463
 32  A*02:01:01-B*35:01:01-C*03:03:01-DRB1*09:01:02-DQB1*03:03:02  China Zhejiang Han 0.11531,734
 33  A*02:01-B*35:30-C*03:04-DRB1*09:01-DQB1*03:03  Colombia Bogotá Cord Blood 0.10581,463
 34  A*02-B*35-DRB1*09-DQB1*03:03  Mexico Oaxaca Rural 0.1027485
 35  A*24:02:01-B*35:01:01-C*03:03:01-DRB1*09:01:02-DQB1*03:03:02  China Zhejiang Han 0.08961,734
 36  A*31-B*35-DRB1*09-DQB1*03:03  Ecuador Mixed Ancestry 0.08531,173
 37  A*24:02-B*35:01-C*04:01-DRB1*09:01-DQA1*03:01-DQB1*03:03-DPB1*04:01  Sri Lanka Colombo 0.0700714
 38  A*02:01-B*35:01-C*03:03-DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*02:02-DPB1*05:01  Japan pop 17 0.07003,078
 39  A*26:01-B*35:01-C*03:03-DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*01:03-DPB1*02:01  Japan pop 17 0.07003,078
 40  A*26:01-B*35:01-C*03:03-DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*02:02-DPB1*05:01  Japan pop 17 0.07003,078
 41  A*02:01-B*35:68-C*04:01-DRB1*09:01-DQB1*03:03  Colombia Bogotá Cord Blood 0.06841,463
 42  A*03-B*35-DRB1*09-DQB1*03:03  Ecuador Andes Mixed Ancestry 0.0607824
 43  A*68-B*35-DRB1*09-DQB1*03:03  Ecuador Andes Mixed Ancestry 0.0607824
 44  A*11:01:01-B*35:01:01-C*03:03:01-DRB1*09:01:02-DQB1*03:03:02  China Zhejiang Han 0.05771,734
 45  A*11:01:01-B*35:01:01-C*07:02:01-DRB1*09:01:02-DQB1*03:03:02  China Zhejiang Han 0.05771,734
 46  A*11:01:01-B*35:03:01-C*04:01:01-DRB1*09:01:02-DQB1*03:03:02  China Zhejiang Han 0.05771,734
 47  A*03:01-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03-DPB1*04:02  Russia Karelia 0.05641,075
 48  A*24:02-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  Malaysia Peninsular Malay 0.0526951
 49  A*02:01-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  India North UCBB 0.05085,849
 50  A*11:02-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  USA Asian pop 2 0.04401,772
 51  A*24:07-B*35:05-C*04:01-DRB1*09:01-DQB1*03:03  USA Asian pop 2 0.04401,772
 52  A*03-B*35-DRB1*09-DQB1*03:03  Ecuador Mixed Ancestry 0.04261,173
 53  A*68-B*35-DRB1*09-DQB1*03:03  Ecuador Mixed Ancestry 0.04261,173
 54  A*02-B*35-DRB1*09-DQB1*03:03  Mexico Jalisco, Guadalajara city 0.04191,189
 55  A*02:01-B*35:30-C*08:03-DRB1*09:01-DQB1*03:03  Colombia Bogotá Cord Blood 0.03421,463
 56  A*02:17-B*35:01-C*03:05-DRB1*09:01-DQB1*03:03  Colombia Bogotá Cord Blood 0.03421,463
 57  A*02:17-B*35:01-C*04:04-DRB1*09:01-DQB1*03:03  Colombia Bogotá Cord Blood 0.03421,463
 58  A*24:02-B*35:30-C*08:03-DRB1*09:01-DQB1*03:03  Colombia Bogotá Cord Blood 0.03421,463
 59  A*68:01-B*35:30-C*03:04-DRB1*09:01-DQB1*03:03  Colombia Bogotá Cord Blood 0.03421,463
 60  A*24:03-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 61  A*02:01-B*35:01-C*03:03-DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 62  A*02:01-B*35:01-C*03:03-DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*02:02-DPB1*03:01  Japan pop 17 0.03003,078
 63  A*02:06-B*35:01-C*03:03-DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*01:03-DPB1*02:02  Japan pop 17 0.03003,078
 64  A*02:06-B*35:01-C*03:03-DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*02:02-DPB1*02:01  Japan pop 17 0.03003,078
 65  A*02:06-B*35:01-C*08:01-DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*01:03-DPB1*05:01  Japan pop 17 0.03003,078
 66  A*02:06-B*35:01-C*08:01-DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*02:01-DPB1*05:01  Japan pop 17 0.03003,078
 67  A*11:01-B*35:01-C*03:03-DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 68  A*11:01-B*35:01-C*08:01-DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*01:03-DPB1*04:02  Japan pop 17 0.03003,078
 69  A*24:02-B*35:01-C*08:01-DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*02:01-DPB1*05:01  Japan pop 17 0.03003,078
 70  A*24:02-B*35:01-C*08:01-DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 71  A*24:20-B*35:01-C*03:03-DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 72  A*26:01-B*35:01-C*03:03-DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*02:02-DPB1*02:02  Japan pop 17 0.03003,078
 73  A*26:01-B*35:01-C*04:01-DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*01:03-DPB1*04:02  Japan pop 17 0.03003,078
 74  A*26:03-B*35:01-C*03:03-DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 75  A*31:01-B*35:01-C*03:03-DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 76  A*31:01-B*35:01-C*03:03-DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*02:01-DPB1*09:01  Japan pop 17 0.03003,078
 77  A*02:01:01-B*35:01:01-C*08:01:01-DRB1*09:01:02-DQB1*03:03:02  China Zhejiang Han 0.02881,734
 78  A*02:01:01-B*35:01:23-C*04:01:01-DRB1*09:01:02-DQB1*03:03:02  China Zhejiang Han 0.02881,734
 79  A*33:03-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  India East UCBB 0.02622,403
 80  A*31-B*35-DRB1*09-DQB1*03:03  Mexico Puebla, Puebla city 0.02511,994
 81  A*32-B*35-DRB1*09-DQB1*03:03  Mexico Puebla, Puebla city 0.02511,994
 82  A*68-B*35-DRB1*09-DQB1*03:03  Mexico Puebla, Puebla city 0.02511,994
 83  A*24:02-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  India Central UCBB 0.02324,204
 84  A*02:06-B*35:01-C*16:02-DRB1*09:01-DQB1*03:03  India East UCBB 0.02082,403
 85  A*11:01-B*35:03-C*04:01-DRB1*09:01-DQB1*03:03  India East UCBB 0.02082,403
 86  A*01:01-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  India Tamil Nadu 0.02012,492
 87  A*02:11-B*35:03-C*04:01-DRB1*09:01-DQB1*03:03  India East UCBB 0.01542,403
 88  A*11:01-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  Germany DKMS - Turkey minority 0.01504,856
 89  A*01:01-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  India South UCBB 0.013111,446
 90  A*02:11-B*35:03-C*04:01-DRB1*09:01-DQB1*03:03  India South UCBB 0.012911,446
 91  A*01:01-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  India Central UCBB 0.01254,204
 92  A*24:02-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  USA Hispanic pop 2 0.01201,999
 93  A*31:01-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  USA Hispanic pop 2 0.01201,999
 94  A*03:01-B*35:03-C*04:01-DRB1*09:01-DQB1*03:03  India Central UCBB 0.01194,204
 95  A*02:06-B*35:01-C*03:03-DRB1*09:01-DQB1*03:03  USA Asian pop 2 0.01101,772
 96  A*33:03-B*35:01-C*03:03-DRB1*09:01-DQB1*03:03  USA Asian pop 2 0.01101,772
 97  A*11:01-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  India North UCBB 0.00905,849
 98  A*01:01-B*35:03-C*04:01-DRB1*09:01-DQB1*03:03  India South UCBB 0.008711,446
 99  A*11:01-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  India West UCBB 0.00865,829
 100  A*11:01-B*35:03-C*04:01-DRB1*09:01-DQB1*03:03  India West UCBB 0.00865,829

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 121) 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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