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 62 (from 62) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*31:01:02-B*51:02:01-C*08:01-DRB1*08:02:01-DQB1*04:02-DPB1*04:02  Mexico Chihuahua Tarahumara 4.600044
 2  A*68:01-B*51:02:01-C*08:01-DRB1*08:02:01-DQB1*04:02-DPB1*04:02  Mexico Chihuahua Tarahumara 3.400044
 3  A*02-B*51-DRB1*08:02-DQB1*04:02  Bolivia Quechua 2.170069
 4  A*02-B*51-DRB1*08:02-DQB1*04:02  Bolivia La Paz Aymaras 1.310087
 5  B*51:01-C*15:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.8600234
 6  A*24-B*51-DRB1*08:02-DQB1*04:02  Bolivia La Paz Aymaras 0.858087
 7  A*03:01-B*51:01-DRB1*08:02-DQB1*04:02  Chile Mapuche 0.770066
 8  A*02:01:01-B*51:01:01-C*04:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 9  A*02:01:01-B*51:01:01-C*08:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 10  A*26:01-B*51:02-C*15:02-DRB1*08:02-DQB1*04:02  India Northeast UCBB 0.6757296
 11  A*02:01-B*51:01-DRB1*08:02-DQB1*04:02  Mexico Veracruz Xalapa 0.595284
 12  A*03:01-B*51:01-DRB1*08:02-DQB1*04:02  Mexico Veracruz Xalapa 0.595284
 13  A*24:02-B*51:01-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 14  A*02:01-B*51:01-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uros 0.5000105
 15  B*51:01-C*15:09-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.4300234
 16  A*02:01-B*51:01-C*15:09-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.4274234
 17  A*11:01-B*51:01-C*15:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 18  B*51:01-C*15:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 19  A*31:01-B*51:01-C*14:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Japan pop 17 0.29003,078
 20  A*30:02-B*51:01-C*15:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPB1*01:01  USA San Diego 0.2600496
 21  A*31:01-B*51:01-C*14:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.23003,078
 22  A*33:01-B*51:02-C*15:02-DRB1*08:02-DQB1*04:02-DPB1*04:01  Panama 0.1900462
 23  A*03:34-B*51:01-C*16:02-DRB1*08:02-DQB1*04:02  Malaysia Peninsular Indian 0.1845271
 24  A*02:01-B*51:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 0.1515330
 25  A*02:06-B*51:01-C*08:01-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.14001,999
 26  A*02:01-B*51:10-C*15:02-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.13671,463
 27  A*31:01-B*51:01-C*14:02-DRB1*08:02-DQB1*04:02  USA Asian pop 2 0.13501,772
 28  A*31:01-B*51:02-C*08:01-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.09401,999
 29  A*31-B*51-DRB1*08:02-DQA1*04:01-DQB1*04:02  Brazil Paraná Caucasian 0.0780641
 30  A*02:13-B*51:01-C*15:02-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.07721,463
 31  A*24:02-B*51:01-C*14:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Japan pop 17 0.07003,078
 32  A*11:02:01-B*51:02:01-C*12:02:02-DRB1*08:02:01-DQB1*04:02:01  China Zhejiang Han 0.05771,734
 33  A*24:02:01-B*51:02:01-C*15:02:01-DRB1*08:02:01-DQB1*04:02:01  China Zhejiang Han 0.05771,734
 34  A*31:01:02-B*51:02:01-C*15:02:01-DRB1*08:02:01-DQB1*04:02:01  China Zhejiang Han 0.05771,734
 35  A*01:01-B*51:07-C*14:02-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.04701,999
 36  A*02:06-B*51:01-C*15:02-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.04701,999
 37  A*02:13-B*51:01-C*15:02-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.04701,999
 38  A*68:01-B*51:01-C*14:02-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.04701,999
 39  A*24:02-B*51:37-C*14:02-DRB1*08:02-DQB1*04:02  USA Asian pop 2 0.04401,772
 40  A*02:01-B*51:02-C*15:02-DRB1*08:02-DQB1*04:02  USA Asian pop 2 0.04301,772
 41  A*01:01-B*51:01-C*07:02-DRB1*08:02-DQB1*04:02  India Tamil Nadu 0.04012,492
 42  A*02:01-B*51:01-C*03:04-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.03421,463
 43  A*03:01-B*51:01-C*14:02-DRB1*08:02-DQB1*04:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 44  A*01:01-B*51:01-C*14:02-DRB1*08:02-DQB1*04:02  India Tamil Nadu 0.03372,492
 45  A*02:06-B*51:01-C*14:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Japan pop 17 0.03003,078
 46  A*02:06-B*51:02-C*03:03-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Japan pop 17 0.03003,078
 47  A*24:02-B*51:02-C*03:04-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 48  A*26:03-B*51:01-C*14:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 49  A*31:01-B*51:01-C*14:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 50  A*31:01-B*51:01-C*14:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*02:01-DPB1*09:01  Japan pop 17 0.03003,078
 51  A*31:01-B*51:02-C*15:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*02:01-DPB1*14:01  Japan pop 17 0.03003,078
 52  A*33:03-B*51:01-C*14:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Japan pop 17 0.03003,078
 53  A*33:03-B*51:01-C*14:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*02:01-DPB1*14:01  Japan pop 17 0.03003,078
 54  A*11:01:01-B*51:01:01-C*04:82-DRB1*08:02:01-DQB1*04:02:01  China Zhejiang Han 0.02881,734
 55  A*29:01-B*51:01-C*14:02-DRB1*08:02-DQB1*04:02  India Tamil Nadu 0.02012,492
 56  A*02:01-B*51:01-C*14:02-DRB1*08:02-DQB1*04:02  India South UCBB 0.017511,446
 57  A*02:01-B*51:01-C*15:09-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.01201,999
 58  A*32:01-B*51:01-C*15:09-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.01201,999
 59  A*11:01-B*51:01-C*14:02-DRB1*08:02-DQB1*04:02  India Tamil Nadu 0.00652,492
 60  A*02:06-B*51:01-C*16:02-DRB1*08:02-DQB1*04:02  India South UCBB 0.004411,446
 61  A*26:01-B*51:01-C*14:02-DRB1*08:02-DQB1*04:02  India South UCBB 0.004411,446
 62  A*32:01-B*51:01-C*03:153-DRB1*08:02-DQB1*04:02  India South UCBB 0.004411,446

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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