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 49 (from 49) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*02-B*07-DRB1*15:01-DQA1*01:02-DQB1*06:02  Russia Tuva 2.0000190
 2  A*02-B*07-DRB1*15:01-DRB5*01:01-DQA1*01:02-DQB1*06:02  Spain Murcia 1.9000173
 3  A*02:01:01-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQA1*01:02:01-DQB1*06:02-DPA1*01:03:01-DPB1*03:01  Russian Federation Vologda Region 1.6807119
 4  A*03:01-B*07:02-C*07:02-E*01:03:02-F*01:03:01-G*01:01-DRB1*15:01-DQA1*01:02-DQB1*06:02  Portugal Azores Terceira Island 1.3158130
 5  A*03:01-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*04:01  USA San Diego 1.3020496
 6  A*02:01:01-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQA1*01:02:01-DQB1*06:02:01-DPA1*01:03:01-DPB1*04:01:01  Russian Federation Vologda Region 1.2605119
 7  A*24:02:01-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQA1*01:02:01-DQB1*06:02:01-DPA1*01:03:01-DPB1*04:01:01  Russian Federation Vologda Region 1.2605119
 8  A*03-B*07-DRB1*15:01-DQA1*01:02-DQB1*06:02  Brazil Paraná Caucasian 1.2260641
 9  A*24:02-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02  Kosovo 1.2100124
 10  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02  United Arab Emirates Abu Dhabi 0.960052
 11  A*02:01:01-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQA1*01:02:01-DQB1*06:02-DPA1*01:03:01-DPB1*04:01:01  Russian Federation Vologda Region 0.8403119
 12  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*04:02  USA San Diego 0.7810496
 13  A*03:01-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02  Brazil Puyanawa 0.6667150
 14  A*03:01:01-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQA1*01:02:01-DQB1*06:02-DPA1*01:03:01-DPB1*04:01  Russia Belgorod region 0.6536153
 15  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*03:01  South Africa Worcester 0.6000159
 16  A*11:01-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*04:01  USA San Diego 0.5210496
 17  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*03:01  Nicaragua Managua 0.4329339
 18  A*30:01-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*02:01  Nicaragua Managua 0.4329339
 19  A*01:01:01-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQA1*01:02:01-DQB1*06:02-DPA1*02:01:02-DPB1*01:01:01  Russian Federation Vologda Region 0.4202119
 20  A*24:02:01-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQA1*01:02:01-DQB1*06:02-DPA1*01:03:01-DPB1*04:01:01  Russian Federation Vologda Region 0.4202119
 21  A*25:01:01-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQA1*01:02:01-DQB1*06:02-DPA1*01:03:01-DPB1*23:01:01  Russian Federation Vologda Region 0.4202119
 22  A*26:01:01-B*07:02:01-C*03:03:01-DRB1*15:01:01-DQA1*01:02:01-DQB1*06:02:01-DPA1*01:03:01-DPB1*04:01:01  Russian Federation Vologda Region 0.4202119
 23  A*03:01-B*07:02-C*02:02-DRB1*15:01-DQA1*01:02-DQB1*06:02  Kosovo 0.4030124
 24  A*24:02-B*07:02-C*03:04-DRB1*15:01-DQA1*01:02-DQB1*06:02  Kosovo 0.4030124
 25  A*24-B*07-DRB1*15:01-DQA1*01:02-DQB1*06:02  Brazil Paraná Caucasian 0.3900641
 26  A*24:02-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*04:01  Sri Lanka Colombo 0.3501714
 27  A*11:01-B*07:02-C*07:01-DRB1*15:01-DQA1*01:02-DQB1*06:02  Brazil Puyanawa 0.3333150
 28  A*03:01:01-B*07:370-C*07:02:01-DRB1*15:01:01-DQA1*01:02:01-DQB1*06:02-DPA1*01:03:01-DPB1*04:01:01  Russia Belgorod region 0.3268153
 29  A*68:01:01-B*07:02:01-C*04:01:01-DRB1*15:01:01-DQA1*01:02:01-DQB1*06:02-DPA1*01:03:01-DPB1*02:01:02  Russia Belgorod region 0.3268153
 30  A*11-B*07-DRB1*15:01-DQA1*01:02-DQB1*06:02  Brazil Paraná Caucasian 0.3187641
 31  A*02:01-B*07:02-C*07:04-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*16:01  South Africa Worcester 0.3000159
 32  A*01:01-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*09:01  USA San Diego 0.2600496
 33  A*29:02-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*04:02  USA San Diego 0.2600496
 34  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPA1*02:01-DPB1*10:01  Mexico Chiapas Lacandon Mayans 0.2294218
 35  A*01:01-B*07:02-C*04:01-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*04:01  Nicaragua Managua 0.2165339
 36  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*04:01  Nicaragua Managua 0.2165339
 37  A*03:01-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*04:02  Nicaragua Managua 0.2165339
 38  A*24:02-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*03:01  Nicaragua Managua 0.2165339
 39  A*26:01-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*01:01  Nicaragua Managua 0.2165339
 40  A*02-B*07-DRB1*15:01-DQA1*01:02-DQB1*06:02  Brazil Paraná Caucasian 0.1714641
 41  A*03:01-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*04:01  Sri Lanka Colombo 0.1401714
 42  A*24:02-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*02:01  Sri Lanka Colombo 0.1401714
 43  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*06:01  Sri Lanka Colombo 0.0700714
 44  A*33:03-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*03:01  Sri Lanka Colombo 0.0700714
 45  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPA1*01:03-DPB1*03:01  Japan pop 17 0.03003,078
 46  A*11:01-B*07:02-C*03:04-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 47  A*24:02-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 48  A*24:02-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPA1*01:03-DPB1*04:02  Japan pop 17 0.03003,078
 49  A*26:01-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPA1*02:02-DPB1*03:01  Japan pop 17 0.03003,078

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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