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 275) records   Pages: 1 2 3 of 3  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  B*58:01-C*03:02-DRB1*13:02  South Korea pop 3 3.3000485
 2  A*33:03-B*58:01-C*03:02-DRB1*13:02  China Yunnan Province Han 3.0000101
 3  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  South Korea pop 3 3.0000485
 4  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Korean 2.716577,584
 5  A*33:03-B*58:01-C*03:02-DRB1*13:02  China Southwest Dai 2.4000124
 6  B*58:01-C*03:02-DRB1*13:02  China Southwest Dai 2.4000124
 7  A*33:03-B*58:01-C*03:02-DRB1*13:02  Taiwan pop 2 2.1000364
 8  A*33:03-B*58:01-C*03:02-DRB1*13:02  Germany DKMS - China minority 1.63101,282
 9  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
 10  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  USA Asian pop 2 1.37701,772
 11  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
 12  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Vietnamese 1.304843,540
 13  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Chinese 1.262599,672
 14  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:05  Vietnam Hanoi Kinh pop 2 1.2000170
 15  A*33:03-B*58:01-C*03:02-DRB1*13:02  Hong Kong Chinese BMDR 1.14087,595
 16  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
 17  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
 18  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
 19  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
 20  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India West UCBB 0.57935,829
 21  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
 22  A*24:07-B*58:01:01-C*03:02:01-DRB1*13:02:01  China Jingpo Minority 0.5210105
 23  B*58:01:01-C*03:02:01-DRB1*13:02:01  China Jingpo Minority 0.5210105
 24  A*33:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Chinese 0.5155194
 25  A*01:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  Vietnam Kinh 0.4950101
 26  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India South UCBB 0.490211,446
 27  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
 28  A*34:02:01-B*58:01:01-C*03:02:01-DRB1*13:02:01  Costa Rica African -Caribbean (G) 0.4902102
 29  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Filipino 0.486850,614
 30  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
 31  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DPB1*09:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.37365,266
 32  A*33:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Malay 0.3680951
 33  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India North UCBB 0.36155,849
 34  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India Central UCBB 0.35904,204
 35  A*33:03-B*58:01-C*03:02-DRB1*13:02  Brazil Vale do Ribeira Quilombos 0.3472144
 36  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India Tamil Nadu 0.33182,492
 37  A*23:01:01-B*58:01:01-C*03:02:01-DRB1*13:02:01  Nicaragua Mestizo (G) 0.3226155
 38  A*33:03-B*58:01-C*03:02-DRB1*13:02  Japan pop 16 0.308018,604
 39  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
 40  A*33:03-B*58:01-C*03:02-DRB1*13:02  Germany DKMS - Austria minority 0.26001,698
 41  A*33:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:05  Malaysia Peninsular Chinese 0.2577194
 42  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India East UCBB 0.24182,403
 43  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
 44  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
 45  A*33:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:05  Malaysia Peninsular Malay 0.2103951
 46  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
 47  A*01:01-B*58:01-C*03:02-DRB1*13:02:01-DQB1*03:01  England North West 0.2000298
 48  A*33:03-B*58:01-C*03:02-DRB1*13:02:01-DQB1*06:09  England North West 0.2000298
 49  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
 50  A*02:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Indian 0.1845271
 51  A*02:05-B*58:01-C*03:02-DRB1*13:02-DQB1*06:05  Malaysia Peninsular Indian 0.1845271
 52  A*24:02-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Indian 0.1845271
 53  A*26:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:01  Malaysia Peninsular Indian 0.1845271
 54  A*33:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Indian 0.1845271
 55  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:04  USA NMDP Hawaiian or other Pacific Islander 0.179411,499
 56  A*11:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  USA Asian pop 2 0.17801,772
 57  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Japanese 0.175624,582
 58  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
 59  A*01:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Germany DKMS - Italy minority 0.17301,159
 60  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DPB1*13:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.17285,266
 61  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DPB1*04:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.17135,266
 62  A*33:03-B*58:01-C*03:02-DRB1*13:02  Germany DKMS - Croatia minority 0.17002,057
 63  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
 64  A*68:02-B*58:01-C*03:02-DRB1*13:02-DQB1*06:04-DPB1*03:01  Tanzania Maasai 0.1597336
 65  A*11:01-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:04-DPB1*02:01  Sri Lanka Colombo 0.1401714
 66  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
 67  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
 68  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
 69  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DPB1*02:01:02  Hong Kong Chinese HKBMDR HLA 11 loci 0.13755,266
 70  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
 71  A*01:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India East UCBB 0.12482,403
 72  A*24:02-B*58:01-C*03:02-DRB1*13:02  Germany DKMS - China minority 0.12101,282
 73  A*01:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India Central UCBB 0.12064,204
 74  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
 75  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.11405,266
 76  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Malay 0.1052951
 77  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
 78  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
 79  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
 80  A*02:01-B*58:01-C*03:02-DRB1*13:02  Germany DKMS - Bosnia and Herzegovina minority 0.09701,028
 81  A*02:01-B*58:01-C*03:02-DRB1*13:02  Germany DKMS - Croatia minority 0.09702,057
 82  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:05  India Tamil Nadu 0.09492,492
 83  A*01:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India North UCBB 0.09235,849
 84  A*02:06-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  USA Asian pop 2 0.08901,772
 85  A*68:02-B*58:01-C*03:02-DRB1*13:02-DQB1*06:04  USA African American pop 4 0.08702,411
 86  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Germany DKMS - Italy minority 0.08601,159
 87  A*68:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India Tamil Nadu 0.07992,492
 88  A*33:03-B*58:01-C*03:02-DRB1*13:02  Poland DKMS 0.079620,653
 89  A*01:01-B*58:01-C*03:02-DRB1*13:02  Germany DKMS - China minority 0.07801,282
 90  A*01:01-B*58:01-C*03:02-DRB1*13:02  Germany DKMS - Netherlands minority 0.07301,374
 91  A*01:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India West UCBB 0.07275,829
 92  A*26:01-B*58:01-C*03:02-DRB1*13:02  Germany DKMS - France minority 0.07101,406
 93  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
 94  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
 95  A*02:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09-DPB1*03:01  Russia Karelia 0.05771,075
 96  A*24:02-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India East UCBB 0.05692,403
 97  A*01:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India South UCBB 0.055311,446
 98  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP African 0.055228,557
 99  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
 100  A*24:02-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India South UCBB 0.054111,446

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 275) records   Pages: 1 2 3 of 3  


   

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