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 188) records   Pages: 1 2 of 2  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  B*58:01-DRB1*13:02-DQB1*06:09  South Korea pop 3 3.3000485
 2  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  South Korea pop 3 3.0000485
 3  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Korean 2.716577,584
 4  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01-DPA1*02:01:01-DPB1*30:01:01  Brazil Rio de Janeiro Black 1.470668
 5  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  USA Asian pop 2 1.37701,772
 6  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  China Zhejiang Han 1.35381,734
 7  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Vietnamese 1.304843,540
 8  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Chinese 1.262599,672
 9  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  India Kerala Malayalam speaking 1.1240356
 10  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*03:01  Sri Lanka Colombo 0.7703714
 11  A*31:01-B*58:01-DRB1*13:02-DQB1*06:09  Chile Mapuche 0.770066
 12  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Southeast Asian 0.658827,978
 13  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP South Asian Indian 0.6448185,391
 14  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India West UCBB 0.57935,829
 15  A*33:03:01-B*58:01:01-C*03:02:01-DRB1*13:02:01-DQB1*06:09:01  India Kerala Malayalam speaking 0.5620356
 16  A*33:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Chinese 0.5155194
 17  A*01:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  Vietnam Kinh 0.4950101
 18  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India South UCBB 0.490211,446
 19  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  Sri Lanka Colombo 0.4902714
 20  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Filipino 0.486850,614
 21  A*02:01-B*58:01-C*03:04-E*01:03:02-F*01:03:01-G*01:01-DRB1*13:02-DQA1*01:02-DQB1*06:09  Portugal Azores Terceira Island 0.4386130
 22  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQA1*01:02:01-DQB1*06:09:01-DPA1*01:03:01-DPB1*02:01  Russian Federation Vologda Region 0.4202119
 23  A*33:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Malay 0.3680951
 24  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India North UCBB 0.36155,849
 25  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India Central UCBB 0.35904,204
 26  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India Tamil Nadu 0.33182,492
 27  A*68:02-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*03:01  South Africa Worcester 0.3000159
 28  A*33:03:01-B*58:01:01-C*08:22-DRB1*13:02:01-DQB1*06:09:01  Russia Bashkortostan, Tatars 0.2604192
 29  A*11:01-B*58:01-C*07:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Chinese 0.2577194
 30  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India East UCBB 0.24182,403
 31  A*23:01-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  Nicaragua Managua 0.2165339
 32  A*29:02-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  Nicaragua Managua 0.2165339
 33  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*04:01  Sri Lanka Colombo 0.2101714
 34  A*02:05-B*58:01-C*07:01-DRB1*13:02-DQB1*06:09  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.20504,335
 35  A*33:03-B*58:01-C*03:02-DRB1*13:02:01-DQB1*06:09  England North West 0.2000298
 36  A*68:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 37  A*02:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Indian 0.1845271
 38  A*24:02-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Indian 0.1845271
 39  A*32:01-B*58:01-C*12:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Indian 0.1845271
 40  A*33:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Indian 0.1845271
 41  A*11:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  USA Asian pop 2 0.17801,772
 42  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Japanese 0.175624,582
 43  A*11:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  China Zhejiang Han 0.17321,734
 44  A*01:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Germany DKMS - Italy minority 0.17301,159
 45  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPA1*01:03-DPB1*03:01  Japan pop 17 0.16003,078
 46  A*03:01-B*58:01-C*07:136-DRB1*13:02-DQB1*06:09-DPB1*02:01  Tanzania Maasai 0.1597336
 47  A*24:02-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*09:01  Sri Lanka Colombo 0.1401714
 48  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*09:01  Sri Lanka Colombo 0.1401714
 49  A*26:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  India Kerala Malayalam speaking 0.1400356
 50  A*30:02:01-B*58:01:01-C*03:146-DRB1*13:02:01-DQB1*06:09:01  India Kerala Malayalam speaking 0.1400356
 51  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPA1*01:03-DPB1*02:01  Japan pop 17 0.13003,078
 52  A*01:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India East UCBB 0.12482,403
 53  A*01:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India Central UCBB 0.12064,204
 54  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  Poland BMR 0.120623,595
 55  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Malay 0.1052951
 56  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Caribean Black 0.104833,328
 57  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPA1*02:02-DPB1*05:01  Japan pop 17 0.10003,078
 58  A*03:01:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  Russia Nizhny Novgorod, Russians 0.09931,510
 59  A*02:05-B*58:01-C*07:01-DRB1*13:02-DQB1*06:09  USA Hispanic pop 2 0.09401,999
 60  A*01:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India North UCBB 0.09235,849
 61  A*02:06-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  USA Asian pop 2 0.08901,772
 62  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Germany DKMS - Italy minority 0.08601,159
 63  A*68:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India Tamil Nadu 0.07992,492
 64  A*30:02-B*58:01-C*03:146-DRB1*13:02-DQB1*06:09  India South UCBB 0.074211,446
 65  A*01:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India West UCBB 0.07275,829
 66  A*24:07-B*58:01-C*07:01-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*10:01  Sri Lanka Colombo 0.0700714
 67  A*24:17-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  Sri Lanka Colombo 0.0700714
 68  A*01:01-B*58:01-C*07:01-DRB1*13:02-DQB1*06:09  Colombia Bogotá Cord Blood 0.06841,463
 69  A*02:05-B*58:01-C*07:01-DRB1*13:02-DQB1*06:09  Colombia Bogotá Cord Blood 0.06841,463
 70  A*33:03-B*58:01-C*07:01-DRB1*13:02-DQB1*06:09  Colombia Bogotá Cord Blood 0.06841,463
 71  A*23:01-B*58:01-C*07:01-DRB1*13:02-DQB1*06:09  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 72  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP African American pop 2 0.0656416,581
 73  A*02:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09-DPB1*03:01  Russia Karelia 0.05771,075
 74  A*24:02-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India East UCBB 0.05692,403
 75  A*01:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India South UCBB 0.055311,446
 76  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP African 0.055228,557
 77  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Middle Eastern or North Coast of Africa 0.054770,890
 78  A*24:02-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India South UCBB 0.054111,446
 79  A*02:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Malay 0.0526951
 80  A*33:03-B*58:01-C*01:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Malay 0.0526951
 81  A*11:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India West UCBB 0.05205,829
 82  A*68:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India South UCBB 0.050211,446
 83  A*24:02-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India North UCBB 0.04785,849
 84  A*11:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India North UCBB 0.04735,849
 85  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  USA Hispanic pop 2 0.04701,999
 86  A*11:01-B*58:01-C*07:01-DRB1*13:02-DQB1*06:09  Germany DKMS - Italy minority 0.04301,159
 87  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Germany DKMS - Turkey minority 0.04104,856
 88  A*11:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India Tamil Nadu 0.04012,492
 89  A*23:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India Tamil Nadu 0.04012,492
 90  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Caribean Hispanic 0.0390115,374
 91  A*68:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Germany DKMS - Turkey minority 0.03904,856
 92  A*02:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Germany DKMS - Turkey minority 0.03704,856
 93  A*23:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India Central UCBB 0.03574,204
 94  A*32:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India North UCBB 0.03425,849
 95  A*01:01-B*58:01-C*16:01-DRB1*13:02-DQB1*06:09  Colombia Bogotá Cord Blood 0.03421,463
 96  A*02:02-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Colombia Bogotá Cord Blood 0.03421,463
 97  A*03:01-B*58:01-C*07:01-DRB1*13:02-DQB1*06:09  Colombia Bogotá Cord Blood 0.03421,463
 98  A*01:01-B*58:01-C*07:01-DRB1*13:02-DQB1*06:09  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 99  A*02:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 100  A*02:05-B*58:01-C*07:18-DRB1*13:02-DQB1*06:09  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335

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 188) 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