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 : 
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Displaying 101 to 181 (from 181) records   Pages: 1 2 of 2  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 101  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01-DPB1*02:01  Germany DKMS - German donors 0.06383,456,066
 102  A*02:06-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India East UCBB 0.06152,403
 103  A*33:03-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Tamil Nadu 0.06062,492
 104  A*26:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Tamil Nadu 0.05802,492
 105  A*02:06:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  China Zhejiang Han 0.05771,734
 106  A*68:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01-DPB1*03:01  Russia Karelia 0.05641,075
 107  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01-DPB1*04:01  Russia Karelia 0.05621,075
 108  A*02:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.054011,446
 109  A*33:03-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Central UCBB 0.05304,204
 110  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01-DPB1*04:01  Germany DKMS - German donors 0.05293,456,066
 111  A*11:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Malaysia Peninsular Malay 0.0526951
 112  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP African 0.048928,557
 113  A*24:02-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India West UCBB 0.04735,829
 114  A*24:02-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India North UCBB 0.04705,849
 115  A*26:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  USA Hispanic pop 2 0.04701,999
 116  A*32:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  USA Hispanic pop 2 0.04701,999
 117  A*24:02-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India East UCBB 0.04482,403
 118  A*02:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  USA Asian pop 2 0.04401,772
 119  A*03:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  USA Asian pop 2 0.04401,772
 120  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Caribean Black 0.042433,328
 121  A*26:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India North UCBB 0.04235,849
 122  A*03:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India East UCBB 0.03942,403
 123  A*02:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India East UCBB 0.03912,403
 124  A*31:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Germany DKMS - Turkey minority 0.03904,856
 125  A*11:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India East UCBB 0.03662,403
 126  A*68:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India West UCBB 0.03545,829
 127  A*68:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India East UCBB 0.03432,403
 128  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.03421,463
 129  A*30:02-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.03421,463
 130  A*03:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 131  A*25:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 132  A*32:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 133  A*02:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01-DPB1*02:01  Germany DKMS - German donors 0.03383,456,066
 134  A*02:11-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India West UCBB 0.03375,829
 135  A*68:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Central UCBB 0.03324,204
 136  A*11:01:01:01-B*37:01:01-C*06:02:01:01-DRB1*10:01:01-DQB1*05:01  Russia Nizhny Novgorod, Russians 0.03311,510
 137  A*68:02:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01  Russia Nizhny Novgorod, Russians 0.03311,510
 138  A*26:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.031511,446
 139  A*32:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.030811,446
 140  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP African American pop 2 0.0303416,581
 141  A*32:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India West UCBB 0.03025,829
 142  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQA1*01:05-DQB1*05:01-DPA1*01:03-DPB1*04:01  Japan pop 17 0.03003,078
 143  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQA1*01:05-DQB1*05:01-DPA1*02:01-DPB1*05:01  Japan pop 17 0.03003,078
 144  A*02:01-B*37:01-C*06:02-DRB1*10:01-DQA1*01:05-DQB1*05:01-DPA1*01:03-DPB1*04:01  Japan pop 17 0.03003,078
 145  A*02:06-B*37:01-C*06:02-DRB1*10:01-DQA1*01:05-DQB1*05:01-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 146  A*24:02-B*37:01-C*06:02-DRB1*10:01-DQA1*01:05-DQB1*05:01-DPA1*02:01-DPB1*05:01  Japan pop 17 0.03003,078
 147  A*31:01-B*37:01-C*06:02-DRB1*10:01-DQA1*01:05-DQB1*05:01-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 148  A*02:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  China Zhejiang Han 0.02881,734
 149  A*11:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India West UCBB 0.02625,829
 150  A*31:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.024511,446
 151  A*30:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.021211,446
 152  A*02:11-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India East UCBB 0.02112,403
 153  A*02:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Germany DKMS - Turkey minority 0.02104,856
 154  A*03:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Germany DKMS - Turkey minority 0.02104,856
 155  A*02:05-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India East UCBB 0.02082,403
 156  A*02:08-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India East UCBB 0.02082,403
 157  A*03:12-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Tamil Nadu 0.02012,492
 158  A*29:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Tamil Nadu 0.02012,492
 159  A*02:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  Poland BMR 0.019323,595
 160  A*02:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India North UCBB 0.01885,849
 161  A*03:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01-DPB1*02:01  Germany DKMS - German donors 0.01513,456,066
 162  A*32:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Germany DKMS - Turkey minority 0.01504,856
 163  A*26:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  Poland BMR 0.014323,595
 164  A*24:02:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  Poland BMR 0.012723,595
 165  A*02:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01-DPB1*04:01  Germany DKMS - German donors 0.01273,456,066
 166  A*23:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Central UCBB 0.01214,204
 167  A*02:20-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Central UCBB 0.01204,204
 168  A*03:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India West UCBB 0.01195,829
 169  A*26:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Germany DKMS - Turkey minority 0.01004,856
 170  A*24:07-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India West UCBB 0.00905,829
 171  A*29:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India West UCBB 0.00895,829
 172  A*02:20-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India West UCBB 0.00865,829
 173  A*30:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India West UCBB 0.00865,829
 174  A*31:12-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India West UCBB 0.00865,829
 175  A*31:16-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India West UCBB 0.00865,829
 176  A*02:09-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.007411,446
 177  A*03:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  Poland BMR 0.005123,595
 178  A*33:03:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  Poland BMR 0.002123,595
 179  A*68:01:02-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  Poland BMR 0.002123,595
 180  A*32:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  Poland BMR 0.001723,595
 181  A*25:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  Poland BMR 0.000539423,595

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 181 (from 181) 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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