Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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A B C DRB1 DPA1 DPB1 DQA1 DQB1

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Displaying 1 to 100 (from 150) records   Pages: 1 2 of 2  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  South Korea pop 3 3.0000485
 2  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Korean 2.716577,584
 3  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
 4  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  USA Asian pop 2 1.37701,772
 5  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
 6  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Vietnamese 1.304843,540
 7  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Chinese 1.262599,672
 8  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
 9  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
 10  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
 11  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
 12  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India West UCBB 0.57935,829
 13  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
 14  A*33:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Chinese 0.5155194
 15  A*01:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  Vietnam Kinh 0.4950101
 16  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India South UCBB 0.490211,446
 17  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
 18  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Filipino 0.486850,614
 19  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
 20  A*33:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Malay 0.3680951
 21  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India North UCBB 0.36155,849
 22  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India Central UCBB 0.35904,204
 23  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India Tamil Nadu 0.33182,492
 24  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
 25  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India East UCBB 0.24182,403
 26  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
 27  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
 28  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
 29  A*33:03-B*58:01-C*03:02-DRB1*13:02:01-DQB1*06:09  England North West 0.2000298
 30  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
 31  A*02:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Indian 0.1845271
 32  A*24:02-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Indian 0.1845271
 33  A*33:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Indian 0.1845271
 34  A*11:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  USA Asian pop 2 0.17801,772
 35  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Japanese 0.175624,582
 36  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
 37  A*01:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Germany DKMS - Italy minority 0.17301,159
 38  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
 39  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
 40  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
 41  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
 42  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
 43  A*01:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India East UCBB 0.12482,403
 44  A*01:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India Central UCBB 0.12064,204
 45  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
 46  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Malay 0.1052951
 47  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
 48  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
 49  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
 50  A*01:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India North UCBB 0.09235,849
 51  A*02:06-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  USA Asian pop 2 0.08901,772
 52  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Germany DKMS - Italy minority 0.08601,159
 53  A*68:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India Tamil Nadu 0.07992,492
 54  A*01:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India West UCBB 0.07275,829
 55  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
 56  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
 57  A*02:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09-DPB1*03:01  Russia Karelia 0.05771,075
 58  A*24:02-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India East UCBB 0.05692,403
 59  A*01:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India South UCBB 0.055311,446
 60  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP African 0.055228,557
 61  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
 62  A*24:02-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India South UCBB 0.054111,446
 63  A*02:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Malay 0.0526951
 64  A*11:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India West UCBB 0.05205,829
 65  A*68:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India South UCBB 0.050211,446
 66  A*24:02-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India North UCBB 0.04785,849
 67  A*11:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India North UCBB 0.04735,849
 68  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  USA Hispanic pop 2 0.04701,999
 69  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Germany DKMS - Turkey minority 0.04104,856
 70  A*11:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India Tamil Nadu 0.04012,492
 71  A*23:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India Tamil Nadu 0.04012,492
 72  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
 73  A*68:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Germany DKMS - Turkey minority 0.03904,856
 74  A*02:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Germany DKMS - Turkey minority 0.03704,856
 75  A*23:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India Central UCBB 0.03574,204
 76  A*32:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India North UCBB 0.03425,849
 77  A*02:02-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Colombia Bogotá Cord Blood 0.03421,463
 78  A*02:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 79  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP European Caucasian 0.03351,242,890
 80  A*25:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  Russia Nizhny Novgorod, Russians 0.03311,510
 81  A*31:01:02:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  Russia Nizhny Novgorod, Russians 0.03311,510
 82  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  Russia Nizhny Novgorod, Russians 0.03311,510
 83  A*68:13:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  Russia Nizhny Novgorod, Russians 0.03311,510
 84  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP North American Amerindian 0.031135,791
 85  A*02:01-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 86  A*24:02-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 87  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQA1*01:03-DQB1*06:09-DPA1*01:03-DPB1*04:01  Japan pop 17 0.03003,078
 88  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Hispanic South or Central American 0.0295146,714
 89  A*31:01:02-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  China Zhejiang Han 0.02951,734
 90  A*02:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  China Zhejiang Han 0.02941,734
 91  A*68:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India North UCBB 0.02925,849
 92  A*30:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  China Zhejiang Han 0.02891,734
 93  A*01:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  China Zhejiang Han 0.02881,734
 94  A*26:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  China Zhejiang Han 0.02881,734
 95  A*68:01:02-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  China Zhejiang Han 0.02881,734
 96  A*02:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  Poland BMR 0.028723,595
 97  A*26:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Germany DKMS - Turkey minority 0.02804,856
 98  A*24:02-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India Central UCBB 0.02724,204
 99  A*03:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India West UCBB 0.02665,829
 100  A*03:02-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India North UCBB 0.02565,849

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 150) 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.
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