Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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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 175 (from 175) records   Pages: 1 2 of 2  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 101  A*03:01:01:01-B*07:02:01-C*07:02:01:01-DRB1*01:01:01-DQB1*05:01  Russia Nizhny Novgorod, Russians 0.03311,510
 102  A*68:01:02:01-B*07:02:01-C*07:02:01:03-DRB1*01:01:01-DQB1*05:01  Russia Nizhny Novgorod, Russians 0.03311,510
 103  A*11:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India North UCBB 0.03305,849
 104  A*01:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01-DPB1*04:01  Germany DKMS - German donors 0.03203,456,066
 105  A*24:02-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India North UCBB 0.03095,849
 106  A*03:01:01:01-B*07:02:01-C*07:02:01-DRB1*01:01:01-DQB1*05:01  Russia Nizhny Novgorod, Russians 0.03031,510
 107  A*02:01-B*07:02-C*07:02-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPA1*01:03-DPB1*05:01  Japan pop 17 0.03003,078
 108  A*02:01-B*07:02-C*07:02-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPA1*02:02-DPB1*03:01  Japan pop 17 0.03003,078
 109  A*02:01-B*07:02-C*07:02-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 110  A*02:06-B*07:02-C*07:02-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPA1*01:03-DPB1*04:01  Japan pop 17 0.03003,078
 111  A*02:06-B*07:02-C*07:02-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPA1*02:01-DPB1*05:01  Japan pop 17 0.03003,078
 112  A*02:06-B*07:02-C*07:02-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 113  A*02:07-B*07:02-C*07:02-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPA1*01:03-DPB1*04:02  Japan pop 17 0.03003,078
 114  A*02:18-B*07:02-C*07:02-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPA1*01:03-DPB1*04:02  Japan pop 17 0.03003,078
 115  A*24:02-B*07:02-C*07:02-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPA1*01:03-DPB1*04:01  Japan pop 17 0.03003,078
 116  A*24:02-B*07:02-C*07:02-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPA1*01:03-DPB1*105:01  Japan pop 17 0.03003,078
 117  A*26:01-B*07:02-C*07:02-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 118  A*26:02-B*07:02-C*07:02-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPA1*01:03-DPB1*04:02  Japan pop 17 0.03003,078
 119  A*33:03-B*07:02-C*07:02-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPA1*02:01-DPB1*09:01  Japan pop 17 0.03003,078
 120  A*02:01:01-B*07:02:01-C*07:02:01-DRB1*01:01:01-DQB1*05:01:01  China Zhejiang Han 0.02881,734
 121  A*24:02-B*07:02-C*07:02-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Mexican or Chicano 0.0283261,235
 122  A*24:02-B*07:02-C*07:02-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Chinese 0.027999,672
 123  A*11:01:01-B*07:02:01-C*07:02:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.027523,595
 124  A*01:01:01-B*07:02:01-C*07:02:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.026623,595
 125  A*26:01:01-B*07:02:01-C*07:02:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.025023,595
 126  A*33:03-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India Central UCBB 0.02474,204
 127  A*24:02-B*07:02-C*07:02-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Hispanic South or Central American 0.0246146,714
 128  A*01:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India Central UCBB 0.02384,204
 129  A*03:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India South UCBB 0.023711,446
 130  A*33:03-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India West UCBB 0.02275,829
 131  A*68:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  USA Asian pop 2 0.02201,772
 132  A*24:02-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India East UCBB 0.02102,403
 133  A*02:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India East UCBB 0.02082,403
 134  A*02:06-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India East UCBB 0.02082,403
 135  A*24:02-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India South UCBB 0.020111,446
 136  A*01:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India Tamil Nadu 0.02012,492
 137  A*24:07-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India Tamil Nadu 0.02012,492
 138  A*24:02-B*07:02-C*07:02-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Caribean Hispanic 0.0189115,374
 139  A*24:02-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01-DPB1*03:01  Germany DKMS - German donors 0.01853,456,066
 140  A*02:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01-DPB1*03:01  Germany DKMS - German donors 0.01793,456,066
 141  A*24:02-B*07:02-C*07:02-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Caribean Black 0.017633,328
 142  A*03:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India North UCBB 0.01765,849
 143  A*31:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India South UCBB 0.017111,446
 144  A*01:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  Germany DKMS - Turkey minority 0.01704,856
 145  A*11:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India South UCBB 0.016711,446
 146  A*24:02-B*07:02-C*07:02-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP African American pop 2 0.0162416,581
 147  A*02:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01-DPB1*02:01  Germany DKMS - German donors 0.01603,456,066
 148  A*01:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India South UCBB 0.014511,446
 149  A*02:01:01-B*07:02:01-C*07:02:01-DRB1*01:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 0.0140356
 150  A*23:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  USA Hispanic pop 2 0.01201,999
 151  A*26:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  USA Hispanic pop 2 0.01201,999
 152  A*11:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India Central UCBB 0.01194,204
 153  A*03:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01-DPB1*06:01  Germany DKMS - German donors 0.01183,456,066
 154  A*01:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01-DPB1*04:02  Germany DKMS - German donors 0.01183,456,066
 155  A*03:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  USA African American pop 4 0.01102,411
 156  A*24:02-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  USA African American pop 4 0.01102,411
 157  A*32:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India Central UCBB 0.01104,204
 158  A*24:02-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01-DPB1*02:01  Germany DKMS - German donors 0.01023,456,066
 159  A*30:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India Tamil Nadu 0.01002,492
 160  A*31:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India West UCBB 0.00865,829
 161  A*68:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India West UCBB 0.00865,829
 162  A*02:06-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India North UCBB 0.00855,849
 163  A*68:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India South UCBB 0.008211,446
 164  A*03:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India Central UCBB 0.00814,204
 165  A*33:03-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India South UCBB 0.007411,446
 166  A*24:02-B*07:02-C*07:02-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP Filipino 0.007250,614
 167  A*24:02-B*07:02-C*07:02-DRB1*01:01-DRBX*NNNN-DQB1*05:01  USA NMDP African 0.007128,557
 168  A*29:02:01-B*07:02:01-C*07:02:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.006423,595
 169  A*74:03-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India South UCBB 0.004411,446
 170  A*26:01-B*07:02-C*07:02-DRB1*01:01-DQB1*05:01  India Tamil Nadu 0.00342,492
 171  A*25:01:01-B*07:02:01-C*07:02:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.003223,595
 172  A*68:01:01-B*07:02:01-C*07:02:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.002723,595
 173  A*02:06:01-B*07:02:01-C*07:02:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.002123,595
 174  A*02:67-B*07:02:01-C*07:02:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.002123,595
 175  A*32:01:01-B*07:02:01-C*07:02:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.000856323,595

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 175 (from 175) records   Pages: 1 2 of 2  


   

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.

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