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 3,734) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 38  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*33:03-B*44:03-C*14:03  Japan pop 5 10.7000117
 2  A*33:03-B*58:01-DRB1*03:01  Taiwan Tzu Chi Morrow Donor Registry 8.361046,682
 3  A*33:03-C*03:02  Taiwan Minnan pop 1 8.3000102
 4  A*33:03-B*58:01  Taiwan Hakka 8.200055
 5  A*33:03-C*03:02  Taiwan Hakka 8.200055
 6  A*33:03-B*58:01  Singapore Chinese 8.0000149
 7  A*33:03-B*58:01  Taiwan Minnan pop 1 7.8000102
 8  A*33:03-B*58:01-C*03:02  China Southwest Dai 7.7000124
 9  A*33:03-B*58:01-C*03:02  China Canton Han 7.4000264
 10  A*33:03-B*58:01-DRB1*03:01  Taiwan Tzu Chi Cord Blood Bank 6.6000710
 11  A*33:03-B*58:01  Hong Kong Chinese 6.4000569
 12  A*33:03-B*58:01  USA Asian 6.1000358
 13  A*33:03-B*58:01-DRB1*03:01  Malaysia Patani 6.000025
 14  A*33:03-B*58:01-C*03:02  USA Asian 5.9000358
 15  A*33:03-B*58:01-C*03:02  South Korea pop 3 5.8000485
 16  A*33:03-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India East UCBB 5.40472,403
 17  A*33:03-B*44:03-DRB1*07:01  Malaysia Kelantan 5.357128
 18  A*33:03-B*44:06-C*15:02:01  India Mumbai Maratha 5.100091
 19  A*33:03:01-B*44:03:02-C*07:06  South African Indian population 5.000050
 20  A*33:03:01-B*58:01:01-C*03:02:02  South African Indian population 5.000050
 21  A*33:03-B*58:01  Taiwan Thao 5.000030
 22  A*33:03-C*03:02  Taiwan Thao 5.000030
 23  A*33:03-B*53:01  Cuba Mixed Race 4.800042
 24  A*33:03-B*44:03-C*14:03  South Korea pop 3 4.7000485
 25  A*33:03-B*58:01-C*03:02-DRB1*03:01  Hong Kong Chinese BMDR 4.64297,595
 26  A*33:03-B*58:01-C*03:02-DRB1*03:01-DRB3*02:02-DQB1*02:01  USA NMDP Chinese 4.600599,672
 27  A*33:03-B*35:03-DRB1*13:01  China Yunnan Province Wa 4.6000119
 28  A*33:03-B*44:03-DRB1*13:02  South Korea pop 3 4.6000485
 29  A*33:03-B*44:03-DRB1*13:02  South Korea pop 10 4.60004,128
 30  A*33:03-B*58:01  USA Asian pop 2 4.53101,772
 31  A*33:03-B*44:03-C*14:03-DRB1*13:02  Japan pop 16 4.473018,604
 32  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01:01  Vietnam Kinh 4.4550101
 33  A*33:03-B*58:01-C*03:02-DRB1*03:01  China Southwest Dai 4.4000124
 34  A*33:03-B*58:01-DRB1*03:01  China Southwest Dai 4.4000124
 35  A*33:03:01-C*07:01:01  China Jingpo Minority 4.3600105
 36  A*33:03-B*58:01-DRB1*03:01  Hong Kong Chinese cord blood registry 4.20043,892
 37  A*33:03-B*44:03-C*14:03-DRB1*13:02-DQB1*06:04  South Korea pop 3 4.2000485
 38  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
 39  A*33:03-B*40:01-DRB1*15:02  Malaysia Patani 4.000025
 40  A*33:03-B*44:03-C*14:03-DRB1*13:02-DRB3*03:01-DQB1*06:04  USA NMDP Japanese 3.926724,582
 41  A*33:03-B*58:01-C*03:02-DRB1*03:01  Taiwan pop 2 3.9000364
 42  A*33:03-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India Northeast UCBB 3.7162296
 43  A*33:03-B*58:01-DRB1*03:01  China Guangxi Region Maonan 3.7000108
 44  A*33:03-B*58:01-C*03:02-DRB1*03:01-DRB3*02:02-DQB1*02:01  USA NMDP Vietnamese 3.668143,540
 45  A*33:03-B*44:03  USA Asian 3.6000358
 46  A*33:03-B*44:03-C*14:03-DRB1*13:02-DQB1*06:04-DPB1*04:01  Japan Central 3.6000371
 47  A*33:03-B*58:01  Taiwan Pazeh 3.600055
 48  A*33:03-C*03:02  Taiwan Pazeh 3.600055
 49  A*33:03-B*18:01-DRB1*07:01  Malaysia Kelantan 3.571428
 50  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Vietnam Hanoi Kinh pop 2 3.5000170
 51  A*33:03-B*44:03-C*14:03-DRB1*13:02-DRB3*03:01-DQB1*06:04  USA NMDP Korean 3.491577,584
 52  A*33:03:01-B*44:03:02  China Jingpo Minority 3.4650105
 53  A*33:03:01-B*44:03:02-C*07:01:01  China Jingpo Minority 3.4650105
 54  A*33:03-B*44:03-DRB1*07:01  Malaysia Champa 3.448329
 55  A*33:03-B*58:01-DRB1*03:01  Malaysia Champa 3.448329
 56  A*33:03-B*14:05-C*05:09  India West Coast Parsi 3.300050
 57  A*33:03-B*44:03-C*14:03-DRB1*13:02-DQA1*01:02-DQB1*06:04-DPA1*01:03-DPB1*04:01  Japan pop 17 3.13003,078
 58  A*33:03-B*18:01-DRB1*12:01  Sao Tome Island Angolar 3.100032
 59  A*33:03-B*44:03-C*07:01/07:06  South Korea pop 3 3.1000485
 60  A*33:03-B*44:03-C*07:01/07:06-DRB1*07:01-DQB1*02:01/02:02  South Korea pop 3 3.0000485
 61  A*33:03-B*58:01-C*03:02-DRB1*03:01  China Yunnan Province Han 3.0000101
 62  A*33:03-B*58:01-C*03:02-DRB1*13:02  China Yunnan Province Han 3.0000101
 63  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  South Korea pop 3 3.0000485
 64  A*33:03-B*58:01-DRB1*13:02  South Korea pop 3 3.0000485
 65  A*33:03-B*58:01-DRB1*13:02  South Korea pop 10 3.00004,128
 66  A*33:03-B*44:03  USA Asian pop 2 2.93801,772
 67  A*33:03-B*44:03-DRB1*07:01  South Korea pop 3 2.9000485
 68  A*33:03-B*58:01  Taiwan Siraya 2.900051
 69  A*33:03-B*58:01-C*03:02-DRB1*03:01  Iran Baloch 2.9000100
 70  A*33:03-C*03:02  Taiwan Siraya 2.900051
 71  A*33:03-B*58:01-DRB1*03:01-DPB1*04:01  China Canton Han 2.8000264
 72  A*33:03-B*44:03-C*07:01-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP South Asian Indian 2.7980185,391
 73  A*33:03-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India West UCBB 2.79385,829
 74  A*33:03-B*58:01-DRB1*03:01  China Jiangsu Province Han 2.7900334
 75  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Korean 2.716577,584
 76  A*33:03-B*78:01-C*16:01  Mali Bandiagara 2.7000138
 77  A*33:03-B*44:03-C*07:01-DRB1*07:01-DQB1*02:01  Vietnam Hanoi Kinh pop 2 2.6000170
 78  A*33:03-B*44:03-C*07:01-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Korean 2.596977,584
 79  A*33:03-B*58:01-DRB1*03:01  China Jiangsu Han 2.59003,238
 80  A*33:03-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India Central UCBB 2.58154,204
 81  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
 82  A*33:03-B*44:03-C*07:01-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Southeast Asian 2.512727,978
 83  A*33:03-B*44:03-DRB1*07:01  South Korea pop 10 2.46004,128
 84  A*33:03-B*58:01-C*03:02-DRB1*13:02  China Southwest Dai 2.4000124
 85  A*33:03-B*58:01-DRB1*13:02  China Southwest Dai 2.4000124
 86  A*33:03-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India South UCBB 2.381211,446
 87  A*33:03-B*44:03-C*07:01-DRB1*07:01-DQB1*02:01  India Tamil Nadu 2.30612,492
 88  A*33:03-B*58:01-C*03:02-DRB1*03:01  Germany DKMS - China minority 2.22101,282
 89  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  USA Asian pop 2 2.21401,772
 90  A*33:03-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India North UCBB 2.18365,849
 91  A*33:03-B*44:03-DRB1*13:02  China Jiangsu Han 2.14003,238
 92  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
 93  A*33:03-B*44:03-C*14:03  USA Asian 2.1000358
 94  A*33:03-B*58:01-C*03:02-DRB1*13:02  Taiwan pop 2 2.1000364
 95  A*33:03:01-B*44:03:02-C*07:01:01-DRB1*07:01:01  China Jingpo Minority 2.0830105
 96  A*33:03:01-B*44:03:02-DRB1*07:01:01  China Jingpo Minority 2.0830105
 97  A*33:03:01-C*07:01:01-DRB1*07:01:01  China Jingpo Minority 2.0620105
 98  A*33:03:01-B*40:01:02-C*12:03:01  South African Indian population 2.000050
 99  A*33:03-B*15:02-DRB1*12:02  Malaysia Patani 2.000025
 100  A*33:03-B*18:01-DRB1*10:01  Malaysia Patani 2.000025

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 3,734) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 38  


   

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