Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

Please specify your search by selecting options from boxes. Then, click "Search" to find HLA Haplotype frequencies that match your criteria. Remember at least one option must be selected.
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 97 (from 97) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*02:01-B*50:01-C*06:02-DRB1*07:01-DQB1*02:02  Tunisia 3.0000100
 2  A*02:01:01-B*50:01-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02  Morocco Atlantic Coast Chaouya 2.900098
 3  A*02:01-B*50:01-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02  United Arab Emirates Abu Dhabi 2.880052
 4  A*02-B*50-C*06:02-DRB1*07-DQB1*02  Russia North Ossetian 1.1800127
 5  A*02-B*50-C*06-DRB1*07-DQB1*02  Sudan Khartoum 1.020098
 6  A*02:05-B*50:01-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02  United Arab Emirates Abu Dhabi 0.960052
 7  A*02:01:01:01-B*50:01:01-C*06:02:01:02-DRB1*07:01:01:01-DQB1*02:02  Russia Bashkortostan, Bashkirs 0.8333120
 8  A*02:01:01-B*50:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:01:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.807228,927
 9  A*02-B*50-C*06-DRB1*07-DQA1*02-DQB1*02  Spain, Castilla y Leon, Northwest, 0.74831,743
 10  A*02:05-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01  Germany DKMS - Turkey minority 0.73304,856
 11  A*02:05-B*50:01-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Middle Eastern or North Coast of Africa 0.616970,890
 12  A*02:05:01-B*50:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:01:01-DPB1*03:01:01  Saudi Arabia pop 6 (G) 0.599428,927
 13  A*02:05-B*50:01-C*06:02-DRB1*07:01-DQB1*02:02  India North UCBB 0.55835,849
 14  A*02:01:01-B*50:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:01:01-DPB1*14:01:01  Saudi Arabia pop 6 (G) 0.527428,927
 15  A*02:05:01-B*50:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:01:01-DPB1*02:01:02  Saudi Arabia pop 6 (G) 0.515428,927
 16  A*02:05-B*50:01-C*06:02-DRB1*07:01:01-DQB1*02:01  England North West 0.5000298
 17  A*02:05-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01  Germany DKMS - Italy minority 0.46301,159
 18  A*02:05-B*50:01-C*06:02-DRB1*07:01-DQB1*02:02  India Central UCBB 0.46104,204
 19  A*02:05-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.41011,463
 20  A*02:05-B*50:01-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP South Asian Indian 0.4022185,391
 21  A*02:01:01-B*50:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.3891521
 22  A*02:05:01-B*50:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:01:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.359228,927
 23  A*02:05-B*50:01-C*06:02-DRB1*07:01-DQB1*02:02  India West UCBB 0.35685,829
 24  A*02:01:01-B*50:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:01:01-DPB1*03:01:01  Saudi Arabia pop 6 (G) 0.346428,927
 25  A*02:05-B*50:01-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Southeast Asian 0.345927,978
 26  A*02:01-B*50:01-C*06:02-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.34204,335
 27  A*02-B*50-C*06:02-DRB1*07:01-DQB1*02  Russia Transbaikal Territory Buryats 0.3340150
 28  A*02:01-B*50:01-C*06:02-DRB1*07:01:01-DQB1*02:01  England North West 0.3000298
 29  A*02:05:01-B*50:01:01-C*06:02:01:02-DRB1*07:01:01-DQB1*02:02  Russia Nizhny Novgorod, Russians 0.29801,510
 30  A*02:05-B*50:01-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP European Caucasian 0.28841,242,890
 31  A*02:05:01-B*50:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.268623,595
 32  A*02:08-B*50:01:01-C*06:02:01:01-DRB1*07:01:01:01-DQB1*02:01:01  Russia Bashkortostan, Tatars 0.2604192
 33  A*02:05-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01  USA NMDP American Indian South or Central America 0.20675,926
 34  A*02:05-B*50:01-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Hispanic South or Central American 0.1946146,714
 35  A*02:05-B*50:01-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Mexican or Chicano 0.1843261,235
 36  A*02:05-B*50:01-C*06:02-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.17104,335
 37  A*02:05-B*50:01-C*06:02-DRB1*07:01-DQB1*02:02  India East UCBB 0.17072,403
 38  A*02:01-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01  USA NMDP Alaska Native or Aleut 0.17041,376
 39  A*02:05-B*50:01-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP North American Amerindian 0.163535,791
 40  A*02:01:01-B*50:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:01:01-DPB1*02:01:02  Saudi Arabia pop 6 (G) 0.159128,927
 41  A*02:01-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01  Germany DKMS - Turkey minority 0.15104,856
 42  A*02:05-B*50:01-C*06:02-DRB1*07:01-DQB1*02:02  India South UCBB 0.146711,446
 43  A*02:08-B*50:01-C*06:02-DRB1*07:01-DQB1*02:02  India North UCBB 0.14515,849
 44  A*02:01-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01  USA Hispanic pop 2 0.14001,999
 45  A*02:05-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01  India Tamil Nadu 0.13252,492
 46  A*02:01-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.12821,463
 47  A*02:01-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01  USA NMDP Black South or Central American 0.11554,889
 48  A*02:05-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01-DPB1*03:01  Russia Karelia 0.11141,075
 49  A*02:05-B*50:01-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP African 0.101028,557
 50  A*02:05-B*50:01-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Caribean Hispanic 0.0939115,374
 51  A*02:01:01-B*50:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.090023,595
 52  A*02:05-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01-DPB1*04:01  Germany DKMS - German donors 0.08603,456,066
 53  A*02:01-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01  Germany DKMS - Italy minority 0.08601,159
 54  A*02:05-B*50:01-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Chinese 0.085999,672
 55  A*02:08-B*50:01-C*06:02-DRB1*07:01-DQB1*02:02  India Central UCBB 0.08334,204
 56  A*02:05-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01-DPB1*03:01  Germany DKMS - German donors 0.07313,456,066
 57  A*02:05-B*50:01-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Vietnamese 0.070143,540
 58  A*02:01-B*50:01-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*04:01  Sri Lanka Colombo 0.0700714
 59  A*02:05:01-B*50:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  China Zhejiang Han 0.05771,734
 60  A*02:07-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01-DPB1*09:01  Russia Karelia 0.05651,075
 61  A*02:05-B*50:01-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Korean 0.052877,584
 62  A*02:05-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01  USA Hispanic pop 2 0.04701,999
 63  A*02:05-B*50:01-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP African American pop 2 0.0419416,581
 64  A*02:08-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01  Germany DKMS - Turkey minority 0.04004,856
 65  A*02:05-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01-DPB1*02:01  Germany DKMS - German donors 0.03733,456,066
 66  A*02:05-B*50:01-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Caribean Black 0.034533,328
 67  A*02:01:01:01-B*50:01:01-C*06:02:01:02-DRB1*07:01:01-DQB1*02:02  Russia Nizhny Novgorod, Russians 0.03311,510
 68  A*02:01:04-B*50:01:01-C*06:02:01:02-DRB1*07:01:01-DQB1*02:02  Russia Nizhny Novgorod, Russians 0.03311,510
 69  A*02-B*50-C*06-DRB1*07-DQA1*01-DQB1*02  Spain, Castilla y Leon, Northwest, 0.03281,743
 70  A*02:01-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01-DPB1*04:01  Germany DKMS - German donors 0.03263,456,066
 71  A*02-B*50-C*06-DRB1*07-DQB1*02-DPB1*04  Norway ethnic Norwegians 0.03004,510
 72  A*02:06-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01  India Tamil Nadu 0.02212,492
 73  A*02:11-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01  India Tamil Nadu 0.02212,492
 74  A*02:16-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01  India Tamil Nadu 0.02212,492
 75  A*02:05-B*50:01-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Japanese 0.018324,582
 76  A*02:01-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01  India Tamil Nadu 0.01812,492
 77  A*02:11-B*50:01-C*06:02-DRB1*07:01-DQB1*02:02  India South UCBB 0.015711,446
 78  A*02:01-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01-DPB1*03:01  Germany DKMS - German donors 0.01543,456,066
 79  A*02:05-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01-DPB1*04:02  Germany DKMS - German donors 0.01483,456,066
 80  A*02:05-B*50:01-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Filipino 0.014250,614
 81  A*02:01-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01-DPB1*02:01  Germany DKMS - German donors 0.01313,456,066
 82  A*02:05-B*50:01-C*06:03-DRB1*07:01-DQB1*02:02  India Central UCBB 0.01194,204
 83  A*02:20-B*50:01-C*06:02-DRB1*07:01-DQB1*02:02  India Central UCBB 0.01194,204
 84  A*02-B*50-C*06-DRB1*07-DQB1*02-DPB1*03  Myanmar Bamar 0.010946
 85  A*02:27-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01-DPB1*02:01  Germany DKMS - German donors 0.01063,456,066
 86  A*02:11-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01  Germany DKMS - Turkey minority 0.01004,856
 87  A*02:20-B*50:01-C*06:02-DRB1*07:01-DQB1*02:01  Germany DKMS - Turkey minority 0.01004,856
 88  A*02:01-B*50:01-C*06:02-DRB1*07:01-DQB1*02:02  India West UCBB 0.00955,829
 89  A*02:01-B*50:01-C*06:02-DRB1*07:01-DQB1*02:02  India South UCBB 0.008711,446
 90  A*02:08-B*50:01-C*06:02-DRB1*07:01-DQB1*02:02  India West UCBB 0.00865,829
 91  A*02:11-B*50:01-C*06:02-DRB1*07:01-DQB1*02:02  India North UCBB 0.00865,849
 92  A*02:03-B*50:01-C*06:02-DRB1*07:01-DQB1*02:02  India North UCBB 0.00855,849
 93  A*02:05-B*50:01-C*06:03-DRB1*07:01-DQB1*02:02  India North UCBB 0.00855,849
 94  A*02:05-B*50:04-C*06:02-DRB1*07:01-DQB1*02:02  India North UCBB 0.00855,849
 95  A*02:06-B*50:01-C*06:02-DRB1*07:01-DQB1*02:02  India North UCBB 0.00855,849
 96  A*02:06-B*50:01-C*06:02-DRB1*07:01-DQB1*02:02  India West UCBB 0.00825,829
 97  A*02:12-B*50:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.002123,595

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.

support@allelefrequencies.net

Valid XHTML 1.0 Transitional