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*01:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  India Andhra Pradesh Telugu Speaking 3.1035186
 2  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  India Kerala Malayalam speaking 2.0680356
 3  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  India Karnataka Kannada Speaking 2.0110174
 4  A*01:01-B*57:01:01-C*06:02-DRB1*07:01:01-DQB1*03:03:02  England North West 1.8000298
 5  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Spain, Canary Islands, Gran canaria island 1.1600215
 6  A*11:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  India Andhra Pradesh Telugu Speaking 1.0944186
 7  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQA1*02:01:01-DQB1*03:03:02-DPA1*01:03:01-DPB1*04:01:01  Russian Federation Vologda Region 0.8403119
 8  A*02:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.795623,595
 9  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.731523,595
 10  A*01:01:01:01-B*57:01:01-C*06:02:01:01-DRB1*07:01:01-DQB1*03:03:02  Russia Nizhny Novgorod, Russians 0.70431,510
 11  A*24:02:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  India Andhra Pradesh Telugu Speaking 0.5980186
 12  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.5837521
 13  A*24:02:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  India Karnataka Kannada Speaking 0.5750174
 14  A*02:01:01:01-B*57:01:01-C*06:02:01:01-DRB1*07:01:01-DQB1*03:03:02  Russia Nizhny Novgorod, Russians 0.54331,510
 15  A*02:01:01:01-B*57:01:01-C*06:02:01:01-DRB1*07:01:01:01-DQB1*03:03:02:01  Russia Bashkortostan, Tatars 0.5208192
 16  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Vietnam Kinh 0.4950101
 17  A*11:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  India Kerala Malayalam speaking 0.4550356
 18  A*24:02:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQA1*02:01:01-DQB1*03:03:02-DPA1*01:03:01-DPB1*04:01:01  Russia Belgorod region 0.3268153
 19  A*03:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02-DPA1*02:01:01-DPB1*09:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 20  A*26:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  India Karnataka Kannada Speaking 0.2870174
 21  A*02:11:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  India Kerala Malayalam speaking 0.2810356
 22  A*24:11N-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  India Andhra Pradesh Telugu Speaking 0.2688186
 23  A*03:01-B*57:01:01-C*06:02-DRB1*07:01:01-DQB1*03:03:02  England North West 0.2000298
 24  A*11:01-B*57:01:01-C*06:02-DRB1*07:01:01-DQB1*03:03:02  England North West 0.2000298
 25  A*24:02-B*57:01:01-C*06:02-DRB1*07:01:01-DQB1*03:03:02  England North West 0.2000298
 26  A*24:02:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 27  A*25:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.171623,595
 28  A*32:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  India Kerala Malayalam speaking 0.1450356
 29  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  China Zhejiang Han 0.14421,734
 30  A*24:02:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  China Zhejiang Han 0.14421,734
 31  A*02:05:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  India Kerala Malayalam speaking 0.1400356
 32  A*24:02:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  India Kerala Malayalam speaking 0.1400356
 33  A*31:01:02:01-B*57:01:01-C*06:02:01:01-DRB1*07:01:01-DQB1*03:03:02  Russia Nizhny Novgorod, Russians 0.12921,510
 34  A*24:02:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.116623,595
 35  A*03:01:01:01-B*57:01:01-C*06:02:01:01-DRB1*07:01:01-DQB1*03:03:02  Russia Nizhny Novgorod, Russians 0.10581,510
 36  A*24:02:01:01-B*57:01:01-C*06:02:01:01-DRB1*07:01:01-DQB1*03:03:02  Russia Nizhny Novgorod, Russians 0.09931,510
 37  A*11:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.098923,595
 38  A*33:03:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  China Zhejiang Han 0.08651,734
 39  A*11:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  China Zhejiang Han 0.07851,734
 40  A*32:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.073723,595
 41  A*26:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.072323,595
 42  A*02:01:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Russia Nizhny Novgorod, Russians 0.06621,510
 43  A*26:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Russia Nizhny Novgorod, Russians 0.06621,510
 44  A*11:02:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  China Zhejiang Han 0.05771,734
 45  A*03:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.057023,595
 46  A*11:01:01:01-B*57:01:01-C*06:02:01:01-DRB1*07:01:01-DQB1*03:03:02  Russia Nizhny Novgorod, Russians 0.03831,510
 47  A*03:01:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Russia Nizhny Novgorod, Russians 0.03311,510
 48  A*32:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Russia Nizhny Novgorod, Russians 0.03311,510
 49  A*68:01:02:01-B*57:01:01-C*06:02:01:01-DRB1*07:01:01-DQB1*03:03:02  Russia Nizhny Novgorod, Russians 0.03311,510
 50  A*69:01-B*57:01:01-C*06:02:01:01-DRB1*07:01:01-DQB1*03:03:02  Russia Nizhny Novgorod, Russians 0.03311,510
 51  A*02:07:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  China Zhejiang Han 0.03151,734
 52  A*31:01:02-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.015823,595
 53  A*68:01:02-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.010223,595
 54  A*02:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  China Zhejiang Han 0.00541,734
 55  A*68:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.005223,595
 56  A*23:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.002723,595
 57  A*33:03:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.002423,595
 58  A*29:02:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.002323,595
 59  A*30:04:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.002223,595
 60  A*02:01:02-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.002123,595
 61  A*68:02:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.002023,595
 62  A*26:08-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.001323,595

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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