Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Population:  Country:  Source of dataset : 
Region:  Ethnic Origin:     Type of study :  Sort by: 
Sample Size:      Sample Year:     Loci Tested: 
Displaying 1 to 64 (from 64) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*02:01:01-B*51:01:01-C*15:02:01  England Blood Donors of Mixed Ethnicity 1.2818519
 2  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*04:02-DQB1*03:02:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 1.055528,927
 3  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  Spain, Canary Islands, Gran canaria island 0.9300215
 4  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*11:01  Costa Rica Guanacaste Mestizo (G) 0.9091110
 5  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*04:03:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 6  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*11:01:01-DQB1*03:01:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 7  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*16:01:01-DQB1*05:02:01-DPA1*02:02:02-DPB1*05:01:01  Brazil Rio de Janeiro Parda 0.5882170
 8  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  India Kerala Malayalam speaking 0.4210356
 9  A*02:01:01:01-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  Russia Bashkortostan, Bashkirs 0.4167120
 10  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*15:01:01-DQB1*03:02:01-DPB1*03:01:01  South African Black 0.3520142
 11  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*04:11:01  Nicaragua Mestizo (G) 0.3226155
 12  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*04:07:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 13  A*02:01:01:01-B*51:01:01-C*15:02:01-DRB1*13:02:01-DQB1*06:04:01  Russia Bashkortostan, Tatars 0.2604192
 14  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*01:02:01-DQB1*05:01:01  Spain, Canary Islands, Gran canaria island 0.2300215
 15  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*03:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 16  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*04:03:01-DQB1*03:02:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.194528,927
 17  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*04:02-DQB1*03:02:01-DPB1*02:01:02  Saudi Arabia pop 6 (G) 0.187528,927
 18  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*01:01:01-DQB1*05:01:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.168028,927
 19  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*07:01:01-DQB1*02:01:01-DPB1*17:01:01  Saudi Arabia pop 6 (G) 0.148628,927
 20  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*03:01:01-DQB1*02:01:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.121028,927
 21  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.115823,595
 22  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*12:02:01-DQB1*03:01:01  China Zhejiang Han 0.11541,734
 23  A*02:01:01:01-B*51:01:01-C*15:02:01:01-DRB1*04:04:01-DQB1*03:02  Russia Nizhny Novgorod, Russians 0.09931,510
 24  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.088923,595
 25  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*08:03:02-DQB1*06:01:01  China Zhejiang Han 0.05771,734
 26  A*02:01:01:01-B*51:01:01-C*15:02:01:01-DRB1*13:01:01-DQB1*06:03:01  Russia Nizhny Novgorod, Russians 0.03611,510
 27  A*02:01:01:01-B*51:01:01-C*15:02:01:01-DRB1*04:03:01-DQB1*03:02  Russia Nizhny Novgorod, Russians 0.03311,510
 28  A*02:01:01:01-B*51:01:01-C*15:02:01:01-DRB1*07:01:01-DQB1*03:03:02  Russia Nizhny Novgorod, Russians 0.03311,510
 29  A*02:01:01:01-B*51:01:01-C*15:02:01:01-DRB1*07:01:01-DQB1*05:01  Russia Nizhny Novgorod, Russians 0.03311,510
 30  A*02:01:01:01-B*51:01:01-C*15:02:01:01-DRB1*11:04:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 31  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.032223,595
 32  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.031823,595
 33  A*02:01:01:01-B*51:01:01-C*15:02:01:01-DRB1*16:01:01-DQB1*05:02  Russia Nizhny Novgorod, Russians 0.03011,510
 34  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*11:01:01-DQB1*03:01:01  China Zhejiang Han 0.02881,734
 35  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*16:01:01-DQB1*05:02:01  Poland BMR 0.019823,595
 36  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*04:03:01-DPB1*03:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.01895,266
 37  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.017223,595
 38  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*12:01:01-DQB1*03:01:01  Poland BMR 0.016723,595
 39  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.014923,595
 40  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.014423,595
 41  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*11:03:01-DQB1*03:01:01  Poland BMR 0.013723,595
 42  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*09:01:02-DQB1*03:03:02  Poland BMR 0.011223,595
 43  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*14:05:01-DQB1*05:03:01  China Zhejiang Han 0.00861,734
 44  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*11:01:01-DPB1*14:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00855,266
 45  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*01:01:01-DQB1*03:01:01  Poland BMR 0.006623,595
 46  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*01:01:01-DQB1*06:02:01  Poland BMR 0.005923,595
 47  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*04:10:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00475,266
 48  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*04:07:01-DQB1*05:02:01  Poland BMR 0.004223,595
 49  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*14:54:01-DQB1*05:03:01  Poland BMR 0.003923,595
 50  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*04:01:01-DQB1*03:01:01  Poland BMR 0.003323,595
 51  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*07:01:01-DQB1*03:01:01  Poland BMR 0.002223,595
 52  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*11:01:01-DQB1*04:02:01  Poland BMR 0.002223,595
 53  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*01:01:01-DQB1*03:03:02  Poland BMR 0.002123,595
 54  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*03:01:01-DQB1*03:03:02  Poland BMR 0.002123,595
 55  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*10:01:01-DQB1*03:02:01  Poland BMR 0.002123,595
 56  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*11:03:01-DQB1*02:01:01  Poland BMR 0.002123,595
 57  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*11:03:01-DQB1*05:02:01  Poland BMR 0.002123,595
 58  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*15:01:01-DQB1*03:03:02  Poland BMR 0.002123,595
 59  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*11:01:01-DQB1*06:04:01  Poland BMR 0.002123,595
 60  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*04:02:01-DQB1*03:02:01  Poland BMR 0.002123,595
 61  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*04:08-DQB1*03:01:01  Poland BMR 0.002123,595
 62  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*11:01:01-DQB1*05:03:01  Poland BMR 0.002023,595
 63  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*15:01:01-DQB1*05:02:01  Poland BMR 0.001223,595
 64  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*11:04:01-DQB1*03:01:01  Poland BMR 0.000130223,595

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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