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 48 (from 48) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*01:01-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  Tunisia 3.0000100
 2  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  India Andhra Pradesh Telugu Speaking 1.1181186
 3  A*24:02:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*02:01:01-DPB1*17:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 4  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  India Kerala Malayalam speaking 0.2810356
 5  A*24:02-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  Malaysia Peninsular Chinese 0.2577194
 6  A*02:03-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  Malaysia Peninsular Indian 0.1845271
 7  A*33:03-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India Northeast UCBB 0.1689296
 8  A*01:01-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India East UCBB 0.15822,403
 9  A*01:01-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India Central UCBB 0.13164,204
 10  A*01:01-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India West UCBB 0.10815,829
 11  A*01:01-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India South UCBB 0.077911,446
 12  A*11:01-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India East UCBB 0.07402,403
 13  A*24:02-B*57:01-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*17:01  Sri Lanka Colombo 0.0700714
 14  A*01:01-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 15  A*24:02-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  Malaysia Peninsular Malay 0.0526951
 16  A*01:01-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India North UCBB 0.04665,849
 17  A*02:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.036923,595
 18  A*02:01-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 19  A*24:02-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 20  A*25:01-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 21  A*26:01-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 22  A*01:01:01:01-B*57:01:01-C*06:02:01:01-DRB1*07:01:01-DQB1*02:02  Russia Nizhny Novgorod, Russians 0.03311,510
 23  A*02:01:01:01-B*57:01:01-C*06:02:01:01-DRB1*07:01:01-DQB1*02:02  Russia Nizhny Novgorod, Russians 0.03311,510
 24  A*24:02-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India West UCBB 0.02895,829
 25  A*33:03-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India West UCBB 0.02645,829
 26  A*24:02-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India South UCBB 0.024711,446
 27  A*24:07-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India Central UCBB 0.02384,204
 28  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.022323,595
 29  A*32:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.019923,595
 30  A*11:01-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India South UCBB 0.019111,446
 31  A*33:03-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India South UCBB 0.019111,446
 32  A*31:01-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India Central UCBB 0.01344,204
 33  A*30:01-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India West UCBB 0.00875,829
 34  A*01:12-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India West UCBB 0.00865,829
 35  A*02:05-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India North UCBB 0.00855,849
 36  A*02:131-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India North UCBB 0.00855,849
 37  A*31:01-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India North UCBB 0.00855,849
 38  A*26:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.008523,595
 39  A*03:01-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India South UCBB 0.007111,446
 40  A*02:01-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India South UCBB 0.005911,446
 41  A*68:01-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India South UCBB 0.005611,446
 42  A*03:02-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India South UCBB 0.005011,446
 43  A*02:03-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India South UCBB 0.004511,446
 44  A*02:06-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India South UCBB 0.004411,446
 45  A*24:11N-B*57:01-C*06:02-DRB1*07:01-DQB1*02:02  India South UCBB 0.004411,446
 46  A*33:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.004223,595
 47  A*68:01:02-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.003023,595
 48  A*25:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.002223,595

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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