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 100 (from 198) records   Pages: 1 2 of 2  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*02:01-B*51:01-C*14:02-DRB1*04:07-DQA1*03:02-DQB1*03:01  Kosovo 0.8060124
 2  A*24-B*51-C*14:02-DRB1*04-DQB1*03  Russia North Ossetian 0.7800127
 3  A*24:02-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  Malaysia Peninsular Indian 0.5535271
 4  A*24:02:01-B*51:01:01-C*14:02:01-DRB1*04:01:01-DQB1*03:04:01  Russia Bashkortostan, Bashkirs 0.4167120
 5  A*02:01-B*51:01-C*14:02-DRB1*04:07-DQA1*03:01-DQB1*03:01  Kosovo 0.4030124
 6  A*02-B*51-C*14:02-DRB1*04-DQB1*03  Russia North Ossetian 0.3900127
 7  A*02:01-B*51:01-C*14:02-DRB1*04:04-DQB1*03:02  Mexico Mexico City Mestizo population 0.3497143
 8  B*51:01-C*14:02-DRB1*04:04-DQB1*03:02  Mexico Mexico City Mestizo population 0.3497143
 9  A*03:01:01-B*51:01:01-C*14:02:01-DRB1*04:03:01-DQB1*03:02:01  India Kerala Malayalam speaking 0.2810356
 10  A*68:01:02-B*51:01:01-C*14:02:01-DRB1*04:03:01-DQB1*03:02:01  India Kerala Malayalam speaking 0.2810356
 11  A*03:01-B*51:01-C*14:02-DRB1*04:01-DQB1*03:02  USA NMDP Caribean Indian 0.260914,339
 12  A*01:01-B*51:01-C*14:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPB1*04:01  USA San Diego 0.2600496
 13  A*68:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  India Tamil Nadu 0.22702,492
 14  A*03:01:01-B*51:01:01-C*14:02:01-DRB1*04:07-DQB1*03:02  Costa Rica Central Valley Mestizo (G) 0.2262221
 15  A*02:01:01-B*51:01:01-C*14:02:01-DRB1*04:03:01-DQB1*03:02:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.215328,927
 16  A*02:01-B*51:01-C*14:02:01-DRB1*04:01:01-DQB1*03:01  England North West 0.2000298
 17  A*01:01-B*51:01-C*14:02-DRB1*04:01-DQB1*03:02  USA NMDP Caribean Indian 0.185214,339
 18  A*01:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  Malaysia Peninsular Indian 0.1845271
 19  A*11:01-B*51:01-C*14:02-DRB1*04:05-DQB1*03:01  Malaysia Peninsular Indian 0.1845271
 20  A*26:12-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  Malaysia Peninsular Indian 0.1845271
 21  A*68:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  Malaysia Peninsular Indian 0.1845271
 22  A*68:01-B*51:01-C*14:02-DRB1*04:08-DQB1*03:01  Malaysia Peninsular Indian 0.1845271
 23  A*31:01-B*51:01-C*14:02-DRB1*04:04-DQB1*03:02  India Northeast UCBB 0.1689296
 24  A*24:17-B*51:01-C*14:02-DRB1*04:03-DQA1*03:01-DQB1*03:05-DPB1*04:02  Sri Lanka Colombo 0.1401714
 25  A*02:11:01-B*51:01:01-C*14:02:01-DRB1*04:03:01-DQB1*03:02:01  India Kerala Malayalam speaking 0.1400356
 26  A*03:02:01-B*51:06:01-C*14:02:01-DRB1*04:03:01-DQB1*03:02:01  India Kerala Malayalam speaking 0.1400356
 27  A*11:01:01-B*51:01:01-C*14:02:01-DRB1*04:03:01-DQB1*03:02:01  India Kerala Malayalam speaking 0.1400356
 28  A*11:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  India Tamil Nadu 0.10902,492
 29  A*68:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  India South UCBB 0.104211,446
 30  A*03:01-B*51:01-C*14:02-DRB1*04:08-DQB1*03:01  India Tamil Nadu 0.10392,492
 31  A*31:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  USA Asian pop 2 0.08901,772
 32  A*24:02:01-B*51:01:01-C*14:02:01-DRB1*04:06:01-DQB1*03:02:01  China Zhejiang Han 0.08651,734
 33  A*68:01-B*51:01-C*14:02-DRB1*04:08-DQB1*03:01  India South UCBB 0.086211,446
 34  A*02:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:05  Germany DKMS - Turkey minority 0.08204,856
 35  A*02:01-B*51:07-C*14:02-DRB1*04:03-DQB1*03:05  Germany DKMS - Turkey minority 0.07804,856
 36  A*02:11-B*51:06-C*14:02-DRB1*04:08-DQA1*03:01-DQB1*03:01-DPB1*04:01  Sri Lanka Colombo 0.0700714
 37  A*02:16-B*51:01-C*14:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPB1*81:01  Sri Lanka Colombo 0.0700714
 38  A*02:01-B*51:01-C*14:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*03:01  Japan pop 17 0.07003,078
 39  A*31:01-B*51:01-C*14:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.07003,078
 40  A*68:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  India East UCBB 0.05122,403
 41  A*11:01-B*51:01-C*14:02-DRB1*04:02-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 42  A*68:01-B*51:01-C*14:02-DRB1*04:05-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 43  A*02:01-B*51:01-C*14:02-DRB1*04:01-DQB1*03:02  Colombia Bogotá Cord Blood 0.04681,463
 44  A*02:01-B*51:01-C*14:02-DRB1*04:01-DQB1*03:01  USA Asian pop 2 0.04401,772
 45  A*02:03-B*51:01-C*14:02-DRB1*04:06-DQB1*03:02  USA Asian pop 2 0.04401,772
 46  A*02:06-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  USA Asian pop 2 0.04401,772
 47  A*24:02-B*51:01-C*14:02-DRB1*04:06-DQB1*03:02  USA Asian pop 2 0.04401,772
 48  A*02:01-B*51:01-C*14:02-DRB1*04:05-DQB1*03:02  Germany DKMS - Italy minority 0.04301,159
 49  A*02:01-B*51:07-C*14:02-DRB1*04:01-DQB1*03:02  Germany DKMS - Italy minority 0.04301,159
 50  A*03:01-B*51:07-C*14:02-DRB1*04:03-DQB1*03:05  Germany DKMS - Italy minority 0.04301,159
 51  A*11:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  India South UCBB 0.042311,446
 52  A*11:01-B*51:01-C*14:02-DRB1*04:02-DQB1*03:02  Germany DKMS - Turkey minority 0.04104,856
 53  A*24:02-B*51:01-C*14:02-DRB1*04:01-DQB1*03:02  India Tamil Nadu 0.03962,492
 54  A*01:01-B*51:01-C*14:02-DRB1*04:01-DQB1*03:01  Colombia Bogotá Cord Blood 0.03421,463
 55  A*26:01-B*51:07-C*14:02-DRB1*04:03-DQB1*03:05  Colombia Bogotá Cord Blood 0.03421,463
 56  A*29:02-B*51:01-C*14:02-DRB1*04:01-DQB1*03:01  Colombia Bogotá Cord Blood 0.03421,463
 57  A*02:01-B*51:01-C*14:02-DRB1*04:01-DQB1*03:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 58  A*02:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:05  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 59  A*03:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 60  A*11:01-B*51:01-C*14:02-DRB1*04:01-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 61  A*11:01-B*51:01-C*14:02-DRB1*04:07-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 62  A*68:01-B*51:01-C*14:02-DRB1*04:04-DQB1*03:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 63  A*01:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  India South UCBB 0.033211,446
 64  A*24:02:01:01-B*51:01:01:01-C*14:02:01-DRB1*04:08:01-DQB1*03:04:01  Russia Nizhny Novgorod, Russians 0.03311,510
 65  A*29:02:01:01-B*51:01:01:01-C*14:02:01-DRB1*04:01:01-DQB1*03:02  Russia Nizhny Novgorod, Russians 0.03311,510
 66  A*68:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  India North UCBB 0.03175,849
 67  A*02:06-B*51:01-C*14:02-DRB1*04:04-DQB1*03:02  Germany DKMS - Turkey minority 0.03104,856
 68  A*03:02-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  Germany DKMS - Turkey minority 0.03104,856
 69  A*02:01-B*51:01-C*14:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*02:01-DPB1*14:01  Japan pop 17 0.03003,078
 70  A*02:01-B*51:01-C*14:02-DRB1*04:04-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*03:01  Japan pop 17 0.03003,078
 71  A*02:07-B*51:01-C*14:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 72  A*24:02-B*51:01-C*14:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 73  A*24:02-B*51:01-C*14:02-DRB1*04:04-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*03:01  Japan pop 17 0.03003,078
 74  A*24:02-B*51:01-C*14:02-DRB1*04:06-DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 75  A*26:01-B*51:01-C*14:02-DRB1*04:06-DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 76  A*26:02-B*51:01-C*14:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*02:01  Japan pop 17 0.03003,078
 77  A*31:01-B*51:01-C*14:02-DRB1*04:01-DQA1*03:03-DQB1*03:01-DPA1*02:02-DPB1*02:02  Japan pop 17 0.03003,078
 78  A*31:01-B*51:01-C*14:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 79  A*01:01-B*51:01-C*14:02-DRB1*04:04-DQB1*03:02  Germany DKMS - Turkey minority 0.02904,856
 80  A*02:01:01-B*51:01:01-C*14:02:01-DRB1*04:03:01-DQB1*03:02:01  China Zhejiang Han 0.02881,734
 81  A*02:01:01-B*51:01:01-C*14:02:01-DRB1*04:04:01-DQB1*03:02:01  China Zhejiang Han 0.02881,734
 82  A*24:02:01-B*51:01:01-C*14:02:01-DRB1*04:03:01-DQB1*03:02:01  China Zhejiang Han 0.02881,734
 83  A*24:02:01-B*51:01:01-C*14:02:01-DRB1*04:04:01-DQB1*03:02:01  China Zhejiang Han 0.02881,734
 84  A*11:01-B*51:01-C*14:02-DRB1*04:08-DQB1*03:01  India Tamil Nadu 0.02672,492
 85  A*11:01-B*51:06-C*14:02-DRB1*04:02-DQB1*03:02  India Tamil Nadu 0.02672,492
 86  A*24:02-B*51:01-C*14:02-DRB1*04:03-DQB1*03:05  India West UCBB 0.02575,829
 87  A*68:01-B*51:01-C*14:02-DRB1*04:02-DQB1*03:02  India North UCBB 0.02565,849
 88  A*01:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  India North UCBB 0.02465,849
 89  A*02:11-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  India North UCBB 0.02385,849
 90  A*11:01-B*51:01-C*14:02-DRB1*04:04-DQB1*03:02  USA Asian pop 2 0.02201,772
 91  A*31:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  India South UCBB 0.021911,446
 92  A*26:01-B*51:06-C*14:02-DRB1*04:03-DQB1*03:02  India Tamil Nadu 0.02182,492
 93  A*24:02-B*51:01-C*14:02-DRB1*04:03-DQB1*03:05  India South UCBB 0.021811,446
 94  A*33:03-B*51:01-C*14:02-DRB1*04:01-DQB1*03:02  Colombia Bogotá Cord Blood 0.02161,463
 95  A*11:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  India East UCBB 0.02112,403
 96  A*03:01-B*51:01-C*14:02-DRB1*04:05-DQB1*03:02  Germany DKMS - Turkey minority 0.02104,856
 97  A*24:02-B*51:01-C*14:02-DRB1*04:02-DQB1*03:02  Germany DKMS - Turkey minority 0.02104,856
 98  A*26:01-B*51:01-C*14:02-DRB1*04:04-DQB1*03:02  Germany DKMS - Turkey minority 0.02104,856
 99  A*31:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:05  Germany DKMS - Turkey minority 0.02104,856
 100  A*11:01-B*51:01-C*14:02-DRB1*04:07-DQB1*03:01  India East UCBB 0.02082,403

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).


Displaying 1 to 100 (from 198) records   Pages: 1 2 of 2  


   

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