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 101 to 200 (from 663) records   Pages: 1 2 3 4 5 6 7 of 7  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 101  A*02:01-B*50:01-DRB1*03:02-DQB1*04:01  Iran Tabriz Azeris 0.515597
 102  A*02:50-B*35:01-DRB1*11:01-DQB1*04:01  Iran Tabriz Azeris 0.515597
 103  A*02:50-B*39:01-DRB1*08:01-DQB1*04:01  Iran Tabriz Azeris 0.515597
 104  A*02:50-B*44:02-DRB1*04:01-DQB1*04:01  Iran Tabriz Azeris 0.515597
 105  A*24:02-B*51:01-DRB1*08:01-DQB1*04:01  Iran Tabriz Azeris 0.515597
 106  A*26:01-B*55:02-C*01:02-DRB1*04:05-DQB1*04:01  Malaysia Peninsular Chinese 0.5155194
 107  A*31:01-B*54:01-DRB1*15:01-DQB1*04:01  Iran Tabriz Azeris 0.515597
 108  A*31:01-B*55:01-DRB1*08:01-DQB1*04:01  Iran Tabriz Azeris 0.515597
 109  A*68:01-B*18:01-DRB1*08:01-DQB1*04:01  Iran Tabriz Azeris 0.515597
 110  A*11:01-B*38:02-C*07:02-DRB1*04:05-DQB1*04:01  India Northeast UCBB 0.5068296
 111  A*02:03:01-B*46:01:01-C*04:03:01-DRB1*04:05:01-DQB1*04:01:01  Vietnam Kinh 0.4950101
 112  A*02:03:01-B*54:01:01-C*04:03:01-DRB1*04:05:01-DQB1*04:01:01  Vietnam Kinh 0.4950101
 113  A*03:02:01-B*13:02:01-C*06:02:01-DRB1*04:05:01-DQB1*04:01:01  Vietnam Kinh 0.4950101
 114  A*11:01:01-B*40:01:02-C*03:04:01-DRB1*04:05:01-DQB1*04:01:01  Vietnam Kinh 0.4950101
 115  A*11:01:01-B*40:02:01-C*07:02:01-DRB1*04:05:01-DQB1*04:01:01  Vietnam Kinh 0.4950101
 116  A*11:01:01-B*55:18-C*07:02:01-DRB1*04:05:01-DQB1*04:01:01  Vietnam Kinh 0.4950101
 117  A*11:01:01-B*56:01:01-C*01:02:01-DRB1*04:05:01-DQB1*04:01:01  Vietnam Kinh 0.4950101
 118  A*24:02:01-B*15:02:01-C*03:04:01-DRB1*04:05:01-DQB1*04:01:01  Vietnam Kinh 0.4950101
 119  A*33:01:01-B*13:01:01-C*03:04:01-DRB1*04:05:01-DQB1*04:01:01  Vietnam Kinh 0.4950101
 120  A*33:03:01-B*39:01:01-C*07:02:01-DRB1*04:05:01-DQB1*04:01:01  Vietnam Kinh 0.4950101
 121  A*24:02-B*54:01-C*01:02-DRB1*04:05-DRB4*01:01-DQB1*04:01  USA NMDP Chinese 0.475199,672
 122  A*24:02-B*59:01-C*01:02-DRB1*04:05-DQB1*04:01  USA Asian pop 2 0.44401,772
 123  A*11:01-B*54:01-C*01:02-DRB1*04:05-DRB4*01:01-DQB1*04:01  USA NMDP Korean 0.438577,584
 124  DRB1*04:05-DQB1*04:01  Georgia Caucasus Tbilisi 0.4202119
 125  A*02:01:01-B*35:01:01-C*01:02:01-DRB1*08:01:01-DQB1*04:01:01  Russia Bashkortostan, Bashkirs 0.4167120
 126  A*24:02:01-B*15:07:01-C*16:02:01-DRB1*04:05:01-DQB1*04:01:01  Russia Bashkortostan, Bashkirs 0.4167120
 127  A*11:01:01-B*54:01:01-C*01:02:01-DRB1*04:05:01-DQB1*04:01:01  China Zhejiang Han 0.40431,734
 128  DRB1*08:02-DQB1*04:01  Cretan Islanders 0.4032124
 129  A*11:01:01-B*40:01:02-C*07:02:01-DRB1*04:05:01-DQB1*04:01:01  China Zhejiang Han 0.38661,734
 130  DRB1*04:05-DQA1*03:03-DQB1*04:01-DPA1*02:02-DPB1*02:02  China Zhejiang Han pop 2 0.3818833
 131  A*11:01-B*54:01-C*01:02-DRB1*04:05-DRB4*01:01-DQB1*04:01  USA NMDP Chinese 0.369099,672
 132  A*24:02-B*54:01-C*01:02-DRB1*04:05-DRB4*01:01-DQB1*04:01  USA NMDP Vietnamese 0.365143,540
 133  A*24:02-B*54:01-C*01:02-DRB1*04:05-DQB1*04:01  USA Asian pop 2 0.36301,772
 134  A*02:07:01-B*46:01:01-C*01:02:01-DRB1*04:05:01-DQB1*04:01:01  China Zhejiang Han 0.31411,734
 135  DRB1*04:05-DQA1*03:03-DQB1*04:01-DPA1*02:02-DPB1*02:01  China Zhejiang Han pop 2 0.3098833
 136  A*24:02-B*54:01-C*01:02-DRB1*04:05-DQA1*03:03-DQB1*04:01-DPA1*01:03-DPB1*02:01  Japan pop 17 0.29003,078
 137  A*11:01:01-B*40:06:01-C*08:01:01-DRB1*04:05:01-DQB1*04:01:01  India Karnataka Kannada Speaking 0.2870174
 138  A*11:01:01-B*55:01:01-C*01:02:01-DRB1*15:01:01-DQB1*04:01:01  India Karnataka Kannada Speaking 0.2870174
 139  DQB1*04:01-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 0.2690496
 140  A*02:11:01-B*40:06:01-C*06:02:01-DRB1*04:05:01-DQB1*04:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 141  A*11:01:01-B*35:01:01-C*01:02:01-DRB1*13:01:01-DQB1*04:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 142  A*68:01:02-B*39:01:01-C*03:03:01-DRB1*04:05:01-DQB1*04:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 143  A*24:02:01:01-B*52:01:01:02-C*12:02:02-DRB1*04:05:01-DQB1*04:01:01  Russia Bashkortostan, Tatars 0.2604192
 144  A*02:01-B*40:01-C*01:02-DRB1*04:05-DQA1*03:01-DQB1*04:01-DPB1*05:01  USA San Diego 0.2600496
 145  A*02:03-B*40:01-C*01:02-DRB1*11:01-DQA1*05:01-DQB1*04:01-DPB1*14:01  USA San Diego 0.2600496
 146  A*02:06-B*54:01-C*01:02-DRB1*04:05-DQA1*03:01-DQB1*04:01-DPB1*05:01  USA San Diego 0.2600496
 147  A*24:02-B*54:01-C*01:02-DRB1*04:05-DQA1*01:03-DQB1*04:01-DPB1*05:01  USA San Diego 0.2600496
 148  A*24:02-B*59:01-C*01:02-DRB1*04:05-DQA1*03:03-DQB1*04:01-DPA1*02:02-DPB1*05:01  Japan pop 17 0.26003,078
 149  A*31:01-B*46:01-C*14:02-DRB1*12:01-DQA1*03:01-DQB1*04:01-DPB1*05:01  USA San Diego 0.2600496
 150  A*31:01-B*54:01-C*14:02-DRB1*04:05-DQA1*03:01-DQB1*04:01-DPB1*02:01  USA San Diego 0.2600496
 151  A*02:01-B*13:01-C*03:04-DRB1*04:05-DQB1*04:01  Malaysia Peninsular Chinese 0.2577194
 152  A*02:01-B*40:01-C*03:03-DRB1*11:01-DQB1*04:01  Malaysia Peninsular Chinese 0.2577194
 153  A*02:01-B*40:04-C*01:02-DRB1*08:03-DQB1*04:01  Malaysia Peninsular Chinese 0.2577194
 154  A*02:01-B*46:01-C*01:02-DRB1*04:05-DQB1*04:01  Malaysia Peninsular Chinese 0.2577194
 155  A*02:07-B*40:01-C*03:04-DRB1*04:05-DQB1*04:01  Malaysia Peninsular Chinese 0.2577194
 156  A*02:07-B*46:01-C*01:02-DRB1*04:05-DQB1*04:01  Malaysia Peninsular Chinese 0.2577194
 157  A*11:01-B*15:01-C*04:03-DRB1*04:05-DQB1*04:01  Malaysia Peninsular Chinese 0.2577194
 158  A*11:01-B*54:01-C*01:02-DRB1*04:05-DQB1*04:01  Malaysia Peninsular Chinese 0.2577194
 159  A*24:02-B*46:01-C*14:02-DRB1*14:04-DQB1*04:01  Malaysia Peninsular Chinese 0.2577194
 160  A*24:02-B*51:02-C*01:02-DRB1*12:02-DQB1*04:01  Malaysia Peninsular Chinese 0.2577194
 161  A*24:02-B*58:01-C*12:02-DRB1*03:19-DQB1*04:01  Malaysia Peninsular Chinese 0.2577194
 162  A*33:01-B*52:01-C*03:03-DRB1*09:01-DQB1*04:01  Malaysia Peninsular Chinese 0.2577194
 163  DRB1*04:05:01-DQB1*04:01-DPB1*02:02  China Inner Mongolia Autonomous Region Northeast 0.2540496
 164  DRB1*04:05-DQA1*03:03-DQB1*04:01-DPA1*01:03-DPB1*04:02  China Zhejiang Han pop 2 0.2530833
 165  DQB1*04:01-DPB1*02:02  China Inner Mongolia Autonomous Region Northeast 0.2460496
 166  A*02:10-B*40:06-C*08:01-DRB1*04:05-DQA1*03:03-DQB1*04:01-DPA1*01:03-DPB1*02:01  Japan pop 17 0.23003,078
 167  A*11:01-B*55:02-C*01:02-DRB1*04:05-DQA1*03:03-DQB1*04:01-DPA1*02:02-DPB1*05:01  Japan pop 17 0.23003,078
 168  A*02:01-B*54:01-C*01:02-DRB1*04:05-DQB1*04:01  USA Asian pop 2 0.22601,772
 169  A*02:06-B*59:01-C*01:02-DRB1*04:05-DQB1*04:01  USA Asian pop 2 0.22201,772
 170  DQA1*03:03-DQB1*04:01-DPA1*04:01-DPB1*13:01  Hong Kong Chinese HKBMDR. DQ and DP 0.20861,064
 171  DRB1*03:01:01:01-DQB1*04:01  China Inner Mongolia Autonomous Region Northeast 0.2020496
 172  DRB1*11:01:01-DQB1*04:01-DPB1*05:01:01  China Inner Mongolia Autonomous Region Northeast 0.2020496
 173  A*69:01:01-B*52:01:01-C*12:02:02-DRB1*04:05:01-DQB1*04:01:01  China Zhejiang Han 0.20181,734
 174  A*02:06-B*59:01-C*01:02-DRB1*04:05-DQA1*03:03-DQB1*04:01-DPA1*01:03-DPB1*04:02  Japan pop 17 0.20003,078
 175  A*24:02-B*40:02-C*03:04-DRB1*04:05-DQA1*03:03-DQB1*04:01-DPA1*02:02-DPB1*05:01  Japan pop 17 0.20003,078
 176  A*24:02-B*59:01-C*01:02-DRB1*04:05-DQA1*03:03-DQB1*04:01-DPA1*01:03-DPB1*02:01  Japan pop 17 0.20003,078
 177  A*24:02:01-B*46:01:01-C*01:02:01-DRB1*04:05:01-DQB1*04:01:01  China Zhejiang Han 0.19071,734
 178  A*02:01-B*40:02-C*03:04-DRB1*04:01-DQB1*04:01-DPB1*04:01  Panama 0.1900462
 179  DRB1*04:05-DQA1*03:03-DQB1*04:01-DPA1*01:03-DPB1*14:01  China Zhejiang Han pop 2 0.1801833
 180  A*11:01-B*55:02-C*01:02-DRB1*04:05-DQB1*04:01  USA Asian pop 2 0.17901,772
 181  A*24:02-B*40:01-C*03:04-DRB1*04:05-DQB1*04:01  USA Asian pop 2 0.17801,772
 182  A*02:06-B*51:01-C*14:02-DRB1*04:05-DQB1*04:01  USA Asian pop 2 0.17701,772
 183  DQA1*03:03-DQB1*04:01-DPA1*02:02-DPB1*135:01  Hong Kong Chinese HKBMDR. DQ and DP 0.17671,064
 184  DRB1*04:05:01-DQB1*04:01-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 0.1720496
 185  DRB1*04:05-DQA1*03:03-DQB1*04:01-DPA1*01:03-DPB1*03:01  China Zhejiang Han pop 2 0.1714833
 186  A*02:03-B*15:08-C*01:02-DRB1*04:05-DQB1*04:01  India Northeast UCBB 0.1689296
 187  A*11:01-B*51:02-C*15:02-DRB1*09:01-DQB1*04:01  India Northeast UCBB 0.1689296
 188  A*24:02-B*40:01-C*03:04-DRB1*15:02-DQB1*04:01  India Northeast UCBB 0.1689296
 189  A*74:02-B*38:02-C*04:01-DRB1*10:01-DQB1*04:01  India Northeast UCBB 0.1689296
 190  DRB1*04:05-DQA1*03:03-DQB1*04:01-DPA1*02:01-DPB1*14:01  China Zhejiang Han pop 2 0.1655833
 191  A*02:01-B*54:01-C*01:02-DRB1*04:05-DQA1*03:03-DQB1*04:01-DPA1*02:02-DPB1*05:01  Japan pop 17 0.16003,078
 192  DRB1*04:05-DQA1*03:03-DQB1*04:01-DPA1*02:02-DPB1*135:01  China Zhejiang Han pop 2 0.1550833
 193  DQA1*03:03-DQB1*04:01-DPA1*02:02-DPB1*13:01  Hong Kong Chinese HKBMDR. DQ and DP 0.15301,064
 194  A*11:01-B*51:01-C*14:02-DRB1*04:05-DQB1*04:01  USA Asian pop 2 0.13301,772
 195  A*26:01-B*40:06-C*08:01-DRB1*04:05-DQB1*04:01  USA Asian pop 2 0.13301,772
 196  A*02:01-B*54:01-C*01:02-DRB1*04:05-DQA1*03:03-DQB1*04:01-DPA1*01:03-DPB1*02:01  Japan pop 17 0.13003,078
 197  A*11:01-B*35:01-C*03:03-DRB1*04:05-DQA1*03:03-DQB1*04:01-DPA1*02:02-DPB1*05:01  Japan pop 17 0.13003,078
 198  A*11:01-B*54:01-C*01:02-DRB1*04:05-DQA1*03:03-DQB1*04:01-DPA1*01:03-DPB1*02:01  Japan pop 17 0.13003,078
 199  A*24:02-B*40:01-C*03:04-DRB1*04:05-DQA1*03:03-DQB1*04:01-DPA1*02:02-DPB1*05:01  Japan pop 17 0.13003,078
 200  A*24:02-B*52:01-C*12:02-DRB1*04:05-DQA1*03:03-DQB1*04:01-DPA1*02:02-DPB1*05:01  Japan pop 17 0.13003,078

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 101 to 200 (from 663) records   Pages: 1 2 3 4 5 6 7 of 7  


   

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