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 : 
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Sample Size:      Sample Year:     Loci Tested: 
Displaying 1 to 59 (from 59) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*01:01:01:01-B*39:01:01-C*12:03:01:01-DRB1*13:01:01-DQB1*06:03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 2  A*01:01:01-B*39:01:01-C*12:03:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.011123,595
 3  A*01:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  India Central UCBB 0.02384,204
 4  A*01:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  India South UCBB 0.023311,446
 5  A*01:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  India West UCBB 0.03435,829
 6  A*02:01:01:01-B*39:01:01-C*12:03:01:01-DRB1*13:01:01-DQB1*06:03:01  Russia Nizhny Novgorod, Russians 0.15251,510
 7  A*02:01:01-B*39:01:01-C*12:03:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.065923,595
 8  A*02:01:01-B*39:01:24-C*12:03:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.002123,595
 9  A*02:01-B*39:01-C*12:03-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*02:01  USA San Diego 0.2600496
 10  A*02:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  Germany DKMS - Italy minority 0.16101,159
 11  A*02:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 12  A*02:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03-DPB1*02:01  Germany DKMS - German donors 0.01783,456,066
 13  A*02:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03-DPB1*04:01  Germany DKMS - German donors 0.01043,456,066
 14  A*03:01:01:01-B*39:01:01-C*12:03:01:01-DRB1*13:01:01-DQB1*06:03:01  Russia Nizhny Novgorod, Russians 0.06741,510
 15  A*03:01:01-B*39:01:01-C*12:03:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.070223,595
 16  A*03:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  India South UCBB 0.010111,446
 17  A*03:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  USA Asian pop 2 0.04401,772
 18  A*03:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03-DPB1*02:01  Germany DKMS - German donors 0.01273,456,066
 19  A*11:01:01:01-B*39:01:01-C*12:03:01:01-DRB1*13:01:01-DQB1*06:03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 20  A*11:01:01-B*39:01:01-C*12:03:01-DRB1*13:01:01-DQB1*06:03:01  India Kerala Malayalam speaking 0.4210356
 21  A*11:01:01-B*39:01:01-C*12:03:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.002223,595
 22  A*11:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  India Tamil Nadu 0.22082,492
 23  A*11:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  India Central UCBB 0.10704,204
 24  A*11:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  India South UCBB 0.051111,446
 25  A*11:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  India West UCBB 0.05155,829
 26  A*11:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  India North UCBB 0.09405,849
 27  A*24:02:01-B*39:01:01-C*12:03:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.015923,595
 28  A*24:02-B*39:01-C*12:03-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*10:01  Sri Lanka Colombo 0.0700714
 29  A*24:02-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  India West UCBB 0.01065,829
 30  A*24:02-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  India South UCBB 0.007911,446
 31  A*24:02-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 32  A*24:02-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03-DPB1*02:01  Russia Karelia 0.10801,075
 33  A*24:02-B*39:01-C*12:03-E*01:01:01-F*01:01:01-G*01:01-DRB1*13:01-DQA1*01:03-DQB1*06:03  Portugal Azores Terceira Island 0.8772130
 34  A*26:01:01-B*39:01:01-C*12:03:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.026923,595
 35  A*26:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  India North UCBB 0.00855,849
 36  A*26:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  India South UCBB 0.004411,446
 37  A*26:08-B*39:01:01-C*12:03:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.000706423,595
 38  A*29:02:01-B*39:01:01-C*12:03:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.002223,595
 39  A*29:02-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  Germany DKMS - Turkey minority 0.01004,856
 40  A*30:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  India West UCBB 0.00865,829
 41  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*13:01:01-DQB1*06:03:01  India Kerala Malayalam speaking 0.1400356
 42  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.020023,595
 43  A*31:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  India West UCBB 0.01515,829
 44  A*31:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03-DPB1*13:01  Russia Karelia 0.11291,075
 45  A*32:01:01-B*39:01:01-C*12:03:01:01-DRB1*13:01:01-DQB1*06:03  Russia Bashkortostan, Bashkirs 0.4167120
 46  A*32:01:01-B*39:01:01-C*12:03:01:01-DRB1*13:01:01-DQB1*06:03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 47  A*32:01:01-B*39:01:01-C*12:03:01:01-DRB1*13:01-DQB1*06:03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 48  A*32:01:01-B*39:01:01-C*12:03:01-DRB1*13:01:01-DQA1*01:03:01-DQB1*06:03:01-DPA1*01:03:01-DPB1*04:01  Russian Federation Vologda Region 0.4202119
 49  A*32:01:01-B*39:01:01-C*12:03:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.012123,595
 50  A*32:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  Germany DKMS - Turkey minority 0.01004,856
 51  A*32:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03-DPB1*04:01  Russia Karelia 0.05621,075
 52  A*33:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 53  A*33:03-B*39:01-C*12:03-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*04:01  Sri Lanka Colombo 0.0700714
 54  A*33:03-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  India North UCBB 0.00855,849
 55  A*68:01:02-B*39:01:01-C*12:03:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.003723,595
 56  A*68:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  India Central UCBB 0.01194,204
 57  A*68:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  India South UCBB 0.005311,446
 58  A*68:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  USA African American pop 4 0.04402,411
 59  A*68:01-B*39:01-C*12:03-DRB1*13:01-DQB1*06:03  USA NMDP Caribean Indian 0.181414,339

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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