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 75 (from 75) records   Pages: 1 of 1  

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*68-B*35-DRB1*09:01-DQB1*03:03  Bolivia Quechua 2.100069
 3  A*24-B*35-DRB1*09:01-DQB1*03:03  Bolivia La Paz Aymaras 2.038087
 4  A*02-B*35-DRB1*09:01-DQB1*03:03  Bolivia Quechua 1.100069
 5  A*02:01-B*35:05-DRB1*09:01-DQB1*03:03  Peru Titikaka Lake Uros 0.5700105
 6  A*24-B*35-DRB1*09:01-DQB1*03:03  Bolivia Quechua 0.500069
 7  A*31:01:02-B*35:21-DRB1*09:01-DQB1*03:03  Peru Titikaka Lake Uros 0.4800105
 8  A*02:01-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  USA NMDP Alaska Native or Aleut 0.42081,376
 9  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
 10  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
 11  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
 12  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
 13  A*11:01-B*35:01-C*03:03-DRB1*09:01-DQB1*03:03  Malaysia Peninsular Chinese 0.2577194
 14  A*26:01-B*35:01-C*16:02-DRB1*09:01-DQB1*03:03  Malaysia Peninsular Chinese 0.2577194
 15  A*02:01-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03-DPB1*13:01  Panama 0.1900462
 16  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
 17  A*24:02-B*35:01-C*03:03-DRB1*09:01-DQB1*03:03  USA Asian pop 2 0.13301,772
 18  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
 19  A*24:02-B*35:30-C*03:04-DRB1*09:01-DQB1*03:03  Colombia Bogotá Cord Blood 0.11931,463
 20  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
 21  A*02:01-B*35:30-C*03:04-DRB1*09:01-DQB1*03:03  Colombia Bogotá Cord Blood 0.10581,463
 22  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
 23  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
 24  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
 25  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
 26  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
 27  A*02:01-B*35:68-C*04:01-DRB1*09:01-DQB1*03:03  Colombia Bogotá Cord Blood 0.06841,463
 28  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
 29  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
 30  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
 31  A*03:01-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03-DPB1*04:02  Russia Karelia 0.05641,075
 32  A*24:02-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  Malaysia Peninsular Malay 0.0526951
 33  A*11:02-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  USA Asian pop 2 0.04401,772
 34  A*24:07-B*35:05-C*04:01-DRB1*09:01-DQB1*03:03  USA Asian pop 2 0.04401,772
 35  A*02:01-B*35:30-C*08:03-DRB1*09:01-DQB1*03:03  Colombia Bogotá Cord Blood 0.03421,463
 36  A*02:17-B*35:01-C*03:05-DRB1*09:01-DQB1*03:03  Colombia Bogotá Cord Blood 0.03421,463
 37  A*02:17-B*35:01-C*04:04-DRB1*09:01-DQB1*03:03  Colombia Bogotá Cord Blood 0.03421,463
 38  A*24:02-B*35:30-C*08:03-DRB1*09:01-DQB1*03:03  Colombia Bogotá Cord Blood 0.03421,463
 39  A*68:01-B*35:30-C*03:04-DRB1*09:01-DQB1*03:03  Colombia Bogotá Cord Blood 0.03421,463
 40  A*24:03-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 41  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
 42  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
 43  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
 44  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
 45  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
 46  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
 47  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
 48  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
 49  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
 50  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
 51  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
 52  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
 53  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
 54  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
 55  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
 56  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
 57  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
 58  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
 59  A*24:02-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  India UCBB_Central Indian HLA 0.02324,204
 60  A*01:01-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  India Tamil Nadu 0.02012,492
 61  A*11:01-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  Germany DKMS - Turkey minority 0.01504,856
 62  A*01:01-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  India UCBB_Central Indian HLA 0.01254,204
 63  A*24:02-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  USA Hispanic pop 2 0.01201,999
 64  A*31:01-B*35:01-C*04:01-DRB1*09:01-DQB1*03:03  USA Hispanic pop 2 0.01201,999
 65  A*03:01-B*35:03-C*04:01-DRB1*09:01-DQB1*03:03  India UCBB_Central Indian HLA 0.01194,204
 66  A*02:06-B*35:01-C*03:03-DRB1*09:01-DQB1*03:03  USA Asian pop 2 0.01101,772
 67  A*33:03-B*35:01-C*03:03-DRB1*09:01-DQB1*03:03  USA Asian pop 2 0.01101,772
 68  A*11:01:01-B*35:01:01-C*04:01:01-DRB1*09:01:02-DQB1*03:03:02  Poland BMR 0.005723,595
 69  A*03:01:01-B*35:01:01-C*04:01:01-DRB1*09:01:02-DQB1*03:03:02  Poland BMR 0.004423,595
 70  A*01:01:01-B*35:01:01-C*04:01:01-DRB1*09:01:02-DQB1*03:03:02  Poland BMR 0.003423,595
 71  A*02:01:01-B*35:01:01-C*04:01:01-DRB1*09:01:02-DQB1*03:03:02  Poland BMR 0.002223,595
 72  A*30:01:01-B*35:08:01-C*01:02:01-DRB1*09:01:02-DQB1*03:03:02  Poland BMR 0.002123,595
 73  A*32:01:01-B*35:02:01-C*16:02:01-DRB1*09:01:02-DQB1*03:03:02  Poland BMR 0.002123,595
 74  A*01:01:01-B*35:02:01-C*06:02:01-DRB1*09:01:02-DQB1*03:03:02  Poland BMR 0.002123,595
 75  A*25:01:01-B*35:03:01-C*12:03:01-DRB1*09:01:02-DQB1*03:03:02  Poland BMR 0.000972723,595

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).




   

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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