Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Population:  Country:  Source of dataset : 
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Displaying 1 to 76 (from 76) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*34:01-B*56:01-C*01:02-DRB1*15:02-DQB1*06:01  USA NMDP Hawaiian or other Pacific Islander 0.450811,499
 2  A*26-B*56-DRB1*15-DQB1*06  Mexico Mexico City Center 0.3247152
 3  A*11:01-B*56:01-C*01:02-DRB1*15:01-DQB1*06:02:01  England North West 0.3000298
 4  A*02-B*56-DRB1*15-DQB1*06  Mexico Sonora Rural 0.2538197
 5  A*02:11-B*56:01-C*04:01-DRB1*15:02-DQB1*06:01  Malaysia Peninsular Indian 0.1845271
 6  A*11:01-B*56:01-C*01:02-DRB1*15:02-DQB1*06:01  India Northeast UCBB 0.1689296
 7  A*26:01-B*56:01-DRB1*15:01-DQB1*06:02  Mexico Mexico City Tlalpan 0.1515330
 8  A*03:01:01-B*56:01:01-C*01:02:01-DRB1*15:01:01-DQB1*06:02:01  India Kerala Malayalam speaking 0.1400356
 9  A*11:01-B*56:01-C*01:02-DRB1*15:01-DQB1*06:02-DPB1*04:01  Russia Karelia 0.13951,075
 10  A*03:01-B*56:01-C*01:02-DRB1*15:01-DQB1*06:02  India North UCBB 0.13655,849
 11  A*03:01-B*56:01-C*01:02-DRB1*15:01-DQB1*06:02  India Central UCBB 0.08334,204
 12  A*02:01-B*56:01-C*01:02-DRB1*15:01-DQA1*01:02-DQB1*06:01-DPB1*01:01  Sri Lanka Colombo 0.0700714
 13  A*02:01:01-B*56:01:01-C*01:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.065423,595
 14  A*03:01-B*56:01-C*01:02-DRB1*15:01-DQB1*06:02  India East UCBB 0.06242,403
 15  A*24-B*56-DRB1*15-DQB1*06  Ecuador Andes Mixed Ancestry 0.0607824
 16  A*03:01:01-B*56:01:01-C*01:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.055923,595
 17  A*24:02-B*56:01-C*01:02-DRB1*15:01-DQB1*06:02  USA Asian pop 2 0.04401,772
 18  A*24-B*56-DRB1*15-DQB1*06  Ecuador Mixed Ancestry 0.04261,173
 19  A*11:01:01-B*56:01:01-C*01:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.035223,595
 20  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 21  A*32:01:01-B*56:01:01-C*01:02:01-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 22  A*02-B*56-C*02-DRB1*15-DQA1*01-DQB1*06  Spain, Castilla y Leon, Northwest, 0.03281,743
 23  A*02:07:01-B*56:03-C*01:02:01-DRB1*15:01:01-DQB1*06:02:01  China Zhejiang Han 0.02881,734
 24  A*30:01:01-B*56:01:01-C*01:02:01-DRB1*15:02:01-DQB1*06:01:01  China Zhejiang Han 0.02881,734
 25  A*03:01-B*56:01-C*01:02-DRB1*15:01-DQB1*06:02  India West UCBB 0.02575,829
 26  A*11:01-B*56:01-C*04:01-DRB1*15:02-DQB1*06:01  India West UCBB 0.02255,829
 27  A*01:01-B*56:01-C*04:01-DRB1*15:01-DQB1*06:01  India West UCBB 0.02105,829
 28  A*02:11-B*56:01-C*01:02-DRB1*15:01-DQB1*06:01  India East UCBB 0.02082,403
 29  A*24:02-B*56:01-C*04:01-DRB1*15:01-DQB1*06:01  India East UCBB 0.02082,403
 30  A*26:01-B*56:01-C*01:02-DRB1*15:01-DQB1*06:02  India East UCBB 0.02082,403
 31  A*11:01-B*56:01-C*04:10-DRB1*15:01-DQB1*06:02  India West UCBB 0.01725,829
 32  A*11:01-B*56:01-C*01:02-DRB1*15:01-DQB1*06:02-DPB1*04:01  Germany DKMS - German donors 0.01613,456,066
 33  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.015123,595
 34  A*03:01-B*56:01-C*01:02-DRB1*15:01-DQB1*06:02-DPB1*04:01  Germany DKMS - German donors 0.01403,456,066
 35  A*02:01-B*56:01-C*01:02-DRB1*15:01-DQB1*06:02-DPB1*04:01  Germany DKMS - German donors 0.01333,456,066
 36  A*11:01-B*56:01-C*04:01-DRB1*15:01-DQB1*06:01  India Central UCBB 0.01194,204
 37  A*11:01-B*56:01-C*04:10-DRB1*15:01-DQB1*06:02  India Central UCBB 0.01194,204
 38  A*02:03-B*56:01-C*12:02-DRB1*15:01-DQB1*06:02  USA Asian pop 2 0.01101,772
 39  A*02:11-B*56:01-C*04:01-DRB1*15:02-DQB1*06:01  USA Asian pop 2 0.01101,772
 40  A*26:01-B*56:01-C*04:01-DRB1*15:02-DQB1*06:01  USA Asian pop 2 0.01101,772
 41  A*26:01-B*56:01-C*12:02-DRB1*15:01-DQB1*06:02  USA Asian pop 2 0.01101,772
 42  A*11:01-B*56:01-C*04:10-DRB1*15:02-DQB1*06:01  India South UCBB 0.010111,446
 43  A*02:01-B*56:01-C*01:02-DRB1*15:02-DQB1*06:01  India South UCBB 0.008811,446
 44  A*24:02:01-B*56:01:01-C*01:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.008823,595
 45  A*11:01-B*56:01-C*04:10-DRB1*15:02-DQB1*06:01  India West UCBB 0.00875,829
 46  A*02:01-B*56:01-C*03:02-DRB1*15:01-DQB1*06:02  India West UCBB 0.00865,829
 47  A*02:01-B*56:01-C*03:03-DRB1*15:02-DQB1*06:01  India West UCBB 0.00865,829
 48  A*02:06-B*56:01-C*04:01-DRB1*15:01-DQB1*06:01  India West UCBB 0.00865,829
 49  A*32:01-B*56:01-C*06:02-DRB1*15:02-DQB1*06:01  India West UCBB 0.00865,829
 50  A*68:01-B*56:01-C*04:01-DRB1*15:01-DQB1*06:01  India West UCBB 0.00865,829
 51  A*02:01-B*56:01-C*01:02-DRB1*15:01-DQB1*06:02  India North UCBB 0.00855,849
 52  A*02:20-B*56:01-C*01:02-DRB1*15:01-DQB1*06:02  India North UCBB 0.00855,849
 53  A*24:07-B*56:01-C*04:10-DRB1*15:02-DQB1*06:01  India North UCBB 0.00855,849
 54  A*31:01-B*56:01-C*15:02-DRB1*15:02-DQB1*06:01  India North UCBB 0.00855,849
 55  A*33:03-B*56:01-C*04:10-DRB1*15:02-DQB1*06:01  India North UCBB 0.00855,849
 56  A*31:01:02-B*56:01:01-C*01:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.008323,595
 57  A*25:01:01-B*56:01:01-C*01:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.006123,595
 58  A*02:11-B*56:01-C*15:02-DRB1*15:01-DQB1*06:01  India South UCBB 0.004811,446
 59  A*11:01-B*56:01-C*01:02-DRB1*15:01-DQB1*06:01  India South UCBB 0.004511,446
 60  A*01:01-B*56:01-C*04:01-DRB1*15:02-DQB1*06:01  India South UCBB 0.004411,446
 61  A*32:01-B*56:01-C*01:02-DRB1*15:02-DQB1*06:01  India South UCBB 0.004411,446
 62  A*68:01-B*56:01-C*15:02-DRB1*15:01-DQB1*06:01  India South UCBB 0.003911,446
 63  A*24:02-B*56:01-C*01:02-DRB1*15:01-DQB1*06:01  India Tamil Nadu 0.00362,492
 64  A*24:02-B*56:01-C*01:02-DRB1*15:02-DQB1*06:01  India Tamil Nadu 0.00362,492
 65  A*24:02-B*56:04-C*01:02-DRB1*15:01-DQB1*06:01  India Tamil Nadu 0.00362,492
 66  A*24:02-B*56:04-C*01:02-DRB1*15:02-DQB1*06:01  India Tamil Nadu 0.00362,492
 67  A*01:01:01-B*56:01:01-C*01:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.003523,595
 68  A*02:11-B*56:01-C*04:01-DRB1*15:02-DQB1*06:01  India West UCBB 0.00325,829
 69  A*24:02-B*56:01-C*01:02-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.00292,492
 70  A*24:02-B*56:04-C*01:02-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.00292,492
 71  A*24:03:01-B*56:01:01-C*01:02:01-DRB1*15:01:01-DQB1*06:03:01  Poland BMR 0.002123,595
 72  A*32:01:01-B*56:01:01-C*01:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.002123,595
 73  A*26:01:40-B*56:01:01-C*01:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.001723,595
 74  A*68:01-B*56:01-C*04:01-DRB1*15:01-DQB1*06:01  India Tamil Nadu 0.00000252,492
 75  A*68:01-B*56:01-C*04:01-DRB1*15:02-DQB1*06:01  India Tamil Nadu 0.00000252,492
 76  A*68:01-B*56:01-C*04:01-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.00000042,492

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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