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 1,403) 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*33:03:01-B*58:01:01-C*03:02:02  South African Indian population 5.000050
 10  B*58:01-C*03:02  Taiwan Thao 5.000030
 11  B*58:01-C*03:02  Taiwan Siraya 4.900051
 12  A*33:03-B*58:01-C*03:02-DRB1*03:01  Hong Kong Chinese BMDR 4.64297,595
 13  A*33:03-B*58:01-C*03:02-DRB1*03:01-DRB3*02:02-DQB1*02:01  USA NMDP Chinese 4.600599,672
 14  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01:01  Vietnam Kinh 4.4550101
 15  A*33:03-B*58:01-C*03:02-DRB1*03:01  China Southwest Dai 4.4000124
 16  B*58:01-C*03:02-DRB1*03:01  China Southwest Dai 4.4000124
 17  B*58:01-C*03:02  Kenya Nandi 4.2000240
 18  A*33:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Chinese 4.1237194
 19  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
 20  A*33:03-B*58:01-C*03:02-DRB1*03:01  Taiwan pop 2 3.9000364
 21  A*33:03-B*58:01-C*03:02-DRB1*03:01-DRB3*02:02-DQB1*02:01  USA NMDP Vietnamese 3.668143,540
 22  B*58:01-C*03:02  Taiwan Pazeh 3.600055
 23  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Vietnam Hanoi Kinh pop 2 3.5000170
 24  B*58:01-C*03:02-DRB1*13:02  South Korea pop 3 3.3000485
 25  A*33:03-B*58:01-C*03:02-DRB1*03:01  China Yunnan Province Han 3.0000101
 26  A*33:03-B*58:01-C*03:02-DRB1*13:02  China Yunnan Province Han 3.0000101
 27  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  South Korea pop 3 3.0000485
 28  A*33:03-B*58:01-C*03:02-DRB1*03:01  Iran Baloch 2.9000100
 29  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Korean 2.716577,584
 30  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
 31  A*33:03-B*58:01-C*03:02-DRB1*13:02  China Southwest Dai 2.4000124
 32  B*58:01-C*03:02-DRB1*13:02  China Southwest Dai 2.4000124
 33  A*33:03-B*58:01-C*03:02-DRB1*03:01  Germany DKMS - China minority 2.22101,282
 34  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  USA Asian pop 2 2.21401,772
 35  B*58:01-C*03:02  USA African American 2.2000252
 36  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
 37  A*33:03-B*58:01-C*03:02-DRB1*13:02  Taiwan pop 2 2.1000364
 38  B*58:01-C*03:02-DRB1*03:01  South Korea pop 3 2.1000485
 39  A*33:03-B*58:01-C*03:02-DRB1*15:04  China Yunnan Hani 2.0000150
 40  B*58:01-C*03:02  Uganda Kampala pop 2 2.0000175
 41  A*33:03-B*58:01-C*03:02-DRB1*03:01-DRB3*02:02-DQB1*02:01  USA NMDP Filipino 1.950950,614
 42  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01/02:02  South Korea pop 3 1.9000485
 43  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Chinese 1.8041194
 44  A*01:01-B*58:01-C*03:02  Kenya Nandi 1.7000240
 45  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
 46  A*33:03-B*58:01-C*03:02-DRB1*13:02  Germany DKMS - China minority 1.63101,282
 47  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India North UCBB 1.52475,849
 48  A*01:02-B*58:01-C*03:02  Kenya Nandi 1.5000240
 49  B*58:01:01-C*03:02:01  China Jingpo Minority 1.4710105
 50  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
 51  A*33:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Malay 1.4138951
 52  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  USA Asian pop 2 1.37701,772
 53  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
 54  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Vietnamese 1.304843,540
 55  B*58:01-C*03:02  Kenya Luo 1.3000265
 56  A*33:03-B*58:01-C*03:02-DRB1*03:01-DRB3*02:02-DQB1*02:01  USA NMDP Korean 1.289377,584
 57  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Chinese 1.262599,672
 58  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
 59  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India Central UCBB 1.22414,204
 60  A*11:01-B*58:01-C*03:02  China Guizhou Province Miao pop 2 1.200085
 61  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:05  Vietnam Hanoi Kinh pop 2 1.2000170
 62  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
 63  A*33:03-B*58:01-C*03:02-DRB1*13:02  Hong Kong Chinese BMDR 1.14087,595
 64  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India East UCBB 1.13112,403
 65  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
 66  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India Tamil Nadu 1.08112,492
 67  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
 68  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India South UCBB 1.047311,446
 69  B*58:01:01-C*03:02:01-DRB1*03:01:01  China Jingpo Minority 1.0420105
 70  B*58:01-C*03:02  USA African American pop 4 1.03902,411
 71  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India Northeast UCBB 1.0135296
 72  A*30:02:01-B*58:01:01-C*03:02:02  South African Mixed ancestry 1.000050
 73  A*11:01:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01:01  Vietnam Kinh 0.9900101
 74  A*33:03:01-B*58:01:01-C*03:02:01  China Jingpo Minority 0.9900105
 75  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
 76  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
 77  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
 78  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.91035,829
 79  A*33:01-B*58:01-C*03:02-DRB1*03:01-DQB1*06:01  Iran Gorgan 0.780064
 80  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
 81  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
 82  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
 83  B*58:01-C*03:02  Mexico Mexico City Mestizo population 0.6993143
 84  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
 85  A*33:03-B*58:01-C*03:02-DRB1*04:01  Brazil Vale do Ribeira Quilombos 0.6944144
 86  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
 87  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
 88  A*33:03-B*58:01-C*03:02  Italy pop 5 0.6300975
 89  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
 90  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
 91  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
 92  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India West UCBB 0.57935,829
 93  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Malay 0.5783951
 94  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
 95  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
 96  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
 97  B*58:01-C*03:02  USA Hispanic pop 2 0.52701,999
 98  A*02:03:01-B*58:01:01-C*03:02:01-DRB1*15:02:01  China Jingpo Minority 0.5210105
 99  A*11:01:01-B*58:01:01-C*03:02:01-DRB1*03:01:01  China Jingpo Minority 0.5210105
 100  A*24:07-B*58:01:01-C*03:02:01-DRB1*13:02:01  China Jingpo Minority 0.5210105

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 1,403) 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