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 1,436) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 15  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  B*58:01-C*03:02  Taiwan Hakka 10.900055
 2  B*58:01-C*03:02  Taiwan Minnan pop 1 8.8000102
 3  A*33:03-B*58:01-C*03:02  China Southwest Dai 7.7000124
 4  A*33:03-B*58:01-C*03:02  China Canton Han 7.4000264
 5  B*58:01-C*03:02  USA Asian 7.2000358
 6  A*33:03-B*58:01-C*03:02  USA Asian 5.9000358
 7  A*33:03-B*58:01-C*03:02  South Korea pop 3 5.8000485
 8  B*58:01-C*03:02  USA Asian pop 2 5.54301,772
 9  A*33-B*58-C*03:02  South Korea pop 1 5.4000324
 10  A*33:03:01-B*58:01:01-C*03:02:02  South African Indian population 5.000050
 11  B*58:01-C*03:02  Taiwan Thao 5.000030
 12  B*58:01-C*03:02  Taiwan Siraya 4.900051
 13  A*33:03-B*58:01-C*03:02-DRB1*03:01  Hong Kong Chinese BMDR 4.64297,595
 14  A*33:03-B*58:01-C*03:02-DRB1*03:01-DRB3*02:02-DQB1*02:01  USA NMDP Chinese 4.600599,672
 15  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01:01  Vietnam Kinh 4.4550101
 16  A*33:03-B*58:01-C*03:02-DRB1*03:01  China Southwest Dai 4.4000124
 17  B*58:01-C*03:02-DRB1*03:01  China Southwest Dai 4.4000124
 18  B*58:01-C*03:02  Kenya Nandi 4.2000240
 19  A*33:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Chinese 4.1237194
 20  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01:01  China Zhejiang Han 4.01521,734
 21  A*33:03-B*58:01-C*03:02-DRB1*03:01  Taiwan pop 2 3.9000364
 22  A*33:03-B*58:01-C*03:02-DRB1*03:01-DRB3*02:02-DQB1*02:01  USA NMDP Vietnamese 3.668143,540
 23  B*58:01-C*03:02  Taiwan Pazeh 3.600055
 24  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Vietnam Hanoi Kinh pop 2 3.5000170
 25  B*58:01-C*03:02-DRB1*13:02  South Korea pop 3 3.3000485
 26  A*33:03-B*58:01-C*03:02-DRB1*03:01  China Yunnan Province Han 3.0000101
 27  A*33:03-B*58:01-C*03:02-DRB1*13:02  China Yunnan Province Han 3.0000101
 28  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  South Korea pop 3 3.0000485
 29  A*33:03-B*58:01-C*03:02-DRB1*03:01  Iran Baloch 2.9000100
 30  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Korean 2.716577,584
 31  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DPB1*04:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 2.56105,266
 32  A*33:03-B*58:01-C*03:02-DRB1*13:02  China Southwest Dai 2.4000124
 33  B*58:01-C*03:02-DRB1*13:02  China Southwest Dai 2.4000124
 34  A*33:03-B*58:01-C*03:02-DRB1*03:01  Germany DKMS - China minority 2.22101,282
 35  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  USA Asian pop 2 2.21401,772
 36  B*58:01-C*03:02  USA African American 2.2000252
 37  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01:01  India Andhra Pradesh Telugu Speaking 2.1050186
 38  A*33:03-B*58:01-C*03:02-DRB1*13:02  Taiwan pop 2 2.1000364
 39  B*58:01-C*03:02-DRB1*03:01  South Korea pop 3 2.1000485
 40  A*33:03-B*58:01-C*03:02-DRB1*15:04  China Yunnan Hani 2.0000150
 41  B*58:01-C*03:02  Uganda Kampala pop 2 2.0000175
 42  A*33:03-B*58:01-C*03:02-DRB1*03:01-DRB3*02:02-DQB1*02:01  USA NMDP Filipino 1.950950,614
 43  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01/02:02  South Korea pop 3 1.9000485
 44  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Chinese 1.8041194
 45  A*01:01-B*58:01-C*03:02  Kenya Nandi 1.7000240
 46  A*33:03-B*58:01-C*03:02-DRB1*03:01-DRB3*02:02-DQB1*02:01  USA NMDP Southeast Asian 1.678627,978
 47  A*33:03-B*58:01-C*03:02-DRB1*13:02  Germany DKMS - China minority 1.63101,282
 48  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India North UCBB 1.52475,849
 49  A*01:02-B*58:01-C*03:02  Kenya Nandi 1.5000240
 50  B*58:01:01-C*03:02:01  China Jingpo Minority 1.4710105
 51  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
 52  A*33:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Malay 1.4138951
 53  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  USA Asian pop 2 1.37701,772
 54  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
 55  A*33-B*58-C*03:02-DRB1*03:01-DQB1*02  Russia Transbaikal Territory Buryats 1.3340150
 56  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Vietnamese 1.304843,540
 57  B*58:01-C*03:02  Kenya Luo 1.3000265
 58  A*33:03-B*58:01-C*03:02-DRB1*03:01-DRB3*02:02-DQB1*02:01  USA NMDP Korean 1.289377,584
 59  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Chinese 1.262599,672
 60  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQA1*05:01-DQB1*02:01-DPB1*04:01  Sri Lanka Colombo 1.2605714
 61  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India Central UCBB 1.22414,204
 62  A*11:01-B*58:01-C*03:02  China Guizhou Province Miao pop 2 1.200085
 63  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:05  Vietnam Hanoi Kinh pop 2 1.2000170
 64  A*33:03:01-B*58:01:01-C*03:02:01-DRB1*15:01:01-DQB1*06:01:01  India Karnataka Kannada Speaking 1.1490174
 65  A*33:03-B*58:01-C*03:02-DRB1*13:02  Hong Kong Chinese BMDR 1.14087,595
 66  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India East UCBB 1.13112,403
 67  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
 68  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India Tamil Nadu 1.08112,492
 69  A*33:03-B*58:01-C*03:02-DRB1*03:01-DRB3*02:02-DQB1*02:01  USA NMDP South Asian Indian 1.0562185,391
 70  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India South UCBB 1.047311,446
 71  B*58:01:01-C*03:02:01-DRB1*03:01:01  China Jingpo Minority 1.0420105
 72  B*58:01-C*03:02  USA African American pop 4 1.03902,411
 73  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India Northeast UCBB 1.0135296
 74  A*30:02:01-B*58:01:01-C*03:02:02  South African Mixed ancestry 1.000050
 75  A*11:01:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01:01  Vietnam Kinh 0.9900101
 76  A*33:03:01-B*58:01:01-C*03:02:01  China Jingpo Minority 0.9900105
 77  A*01:01-B*58:01-C*03:02-DRB1*03:01-DQA1*05:01-DQB1*02:01  United Arab Emirates Abu Dhabi 0.960052
 78  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQA1*05:05-DQB1*02:01  United Arab Emirates Abu Dhabi 0.960052
 79  A*33:03-B*58:01-C*03:02-DRB1*15:01-DQA1*05:05-DQB1*06:02  United Arab Emirates Abu Dhabi 0.960052
 80  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.91035,829
 81  A*33:01-B*58:01-C*03:02-DRB1*03:01-DQB1*06:01  Iran Gorgan 0.780064
 82  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
 83  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  USA NMDP Hawaiian or other Pacific Islander 0.732811,499
 84  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.72025,266
 85  B*58:01-C*03:02  Mexico Mexico City Mestizo population 0.6993143
 86  A*31:01:02-B*58:01:01-C*03:02:01-DRB1*03:01:01-DQB1*02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 87  A*33:03-B*58:01-C*03:02-DRB1*04:01  Brazil Vale do Ribeira Quilombos 0.6944144
 88  A*33-B*58-C*03:02-DRB1*13:02-DQB1*06  Russia Transbaikal Territory Buryats 0.6670150
 89  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
 90  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
 91  A*33:03-B*58:01-C*03:02  Italy pop 5 0.6300975
 92  A*02:01:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.6250405
 93  A*02:04-B*58:01:01-C*03:02:02-DRB1*04:11:01-DQB1*04:02:01-DPA1*02:01:01-DPB1*14:01:01  Brazil Rio de Janeiro Parda 0.5882170
 94  A*03:01:01-B*58:01:01-C*03:02:02-DRB1*15:01:01-DQB1*06:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Parda 0.5882170
 95  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India West UCBB 0.57935,829
 96  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Malay 0.5783951
 97  A*33:03:01-B*58:01:01-C*03:02:01-DRB1*03:01:01-DQB1*02:01:01  India Karnataka Kannada Speaking 0.5750174
 98  A*33:03:01-B*58:01:01-C*03:02:01-DRB1*07:01:01-DQB1*06:05:02  India Karnataka Kannada Speaking 0.5750174
 99  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
 100  B*58:01-C*03:02  USA Hispanic pop 2 0.52701,999

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 1,436) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 15  


   

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