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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Sample Size:      Sample Year:     Loci Tested: 
Displaying 201 to 300 (from 398) records   Pages: 1 2 3 4 of 4  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 201  A*03:01-B*07:02-C*07:02-DRB1*15:01-DRB5*01:01-DQB1*06:02  USA NMDP Japanese 0.128324,582
 202  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*01:01  Russia Karelia 0.12451,075
 203  A*26:01:01-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQB1*06:02:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.119228,927
 204  A*29:01:01-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQB1*06:02:01-DPB1*13:01:01  Saudi Arabia pop 6 (G) 0.117928,927
 205  A*03:01-B*07:02-C*07:02-DRB1*15:01-DRB5*01:01-DQB1*06:02  USA NMDP Southeast Asian 0.114227,978
 206  A*11:01:01:01-B*07:02:01-C*07:02:01:03-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.11001,510
 207  A*02:01:01-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQB1*06:02:01-DPB1*03:01:01  Saudi Arabia pop 6 (G) 0.109328,927
 208  A*11:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India West UCBB 0.10795,829
 209  A*03:01-B*07:02-C*07:02-DRB1*15:01-DRB5*01:01-DQB1*06:02  USA NMDP Chinese 0.106899,672
 210  A*24:02-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA Hispanic pop 2 0.10601,999
 211  A*29:01:01-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQB1*06:02:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.105028,927
 212  A*24:02-B*07:02-C*07:02-DRB1*15:01-DRB5*01:01-DQB1*06:02  USA NMDP Caribean Black 0.103333,328
 213  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*03:01  Germany DKMS - German donors 0.10263,456,066
 214  A*24:02-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India West UCBB 0.09975,829
 215  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*04:02  Germany DKMS - German donors 0.09793,456,066
 216  A*01:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India North UCBB 0.09725,849
 217  A*68:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*04:01  Russia Karelia 0.09501,075
 218  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.09412,492
 219  A*01:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India South UCBB 0.092911,446
 220  A*25:01:01-B*07:02:01-C*07:02:01:03-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.08941,510
 221  A*24:02-B*07:02-C*07:02-DRB1*15:01-DRB5*01:01-DQB1*06:02  USA NMDP Japanese 0.088324,582
 222  A*68:02-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA African American pop 4 0.08702,411
 223  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*04:02  Russia Karelia 0.08401,075
 224  A*01:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.08352,492
 225  A*11:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India East UCBB 0.08322,403
 226  A*26:01:01-B*07:02:01-C*07:02:01-DRB1*15:01-DQB1*06:02  Costa Rica Central Valley Mestizo (G) 0.0832221
 227  A*26:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*04:01  Germany DKMS - German donors 0.08113,456,066
 228  A*03:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India South UCBB 0.080511,446
 229  A*02:01-B*07:02-C*07:02-DRB1*15:01-DRB5*01:01-DQB1*06:02  USA NMDP Filipino 0.079350,614
 230  A*03:01-B*07:02-C*07:02-DRB1*15:01-DRB5*01:01-DQB1*06:02  USA NMDP Korean 0.078277,584
 231  A*11:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India South UCBB 0.074311,446
 232  A*32:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*04:01  Russia Karelia 0.07271,075
 233  A*32:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*04:01  Germany DKMS - German donors 0.07153,456,066
 234  A*24:02-B*07:02-C*07:02-DRB1*15:01-DRB5*01:01-DQB1*06:02  USA NMDP Chinese 0.071599,672
 235  A*24:02-B*07:02-C*07:02-DRB1*15:01-DRB5*01:01-DQB1*06:02  USA NMDP African 0.071428,557
 236  A*02:01-B*07:02-C*07:02-DRB1*15:01-DRB5*01:01-DQB1*06:02  USA NMDP Southeast Asian 0.071027,978
 237  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*06:01  Sri Lanka Colombo 0.0700714
 238  A*33:03-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*03:01  Sri Lanka Colombo 0.0700714
 239  A*03:01-B*07:02-C*07:02-DRB1*15:01-DRB5*01:01-DQB1*06:02  USA NMDP South Asian Indian 0.0698185,391
 240  A*31:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*04:01  Germany DKMS - German donors 0.06953,456,066
 241  A*31:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  Colombia Bogotá Cord Blood 0.06841,463
 242  A*32:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  Colombia Bogotá Cord Blood 0.06841,463
 243  A*25:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 244  A*31:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 245  A*68:01:02:02-B*07:02:01-C*07:02:01:03-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.06641,510
 246  A*02:01:01:01-B*07:02:01-C*07:02:01:01-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.06621,510
 247  A*03:01:01:01-B*07:02:01-C*07:02:01:01-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.06621,510
 248  A*11:01-B*07:02:01-C*07:02:01:03-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.06621,510
 249  A*25:01:01-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.066023,595
 250  A*68:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*04:01  Germany DKMS - German donors 0.06593,456,066
 251  A*02:01-B*07:02-C*07:02-DRB1*15:01-DRB5*01:01-DQB1*06:02  USA NMDP Japanese 0.065224,582
 252  A*03:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India Central UCBB 0.06434,204
 253  A*03:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India East UCBB 0.06242,403
 254  A*31:01:02-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.061323,595
 255  A*02:01:01-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQB1*06:02:01  China Zhejiang Han 0.05771,734
 256  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India North UCBB 0.05625,849
 257  A*68:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*04:02  Russia Karelia 0.05591,075
 258  A*25:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*06:01  Russia Karelia 0.05581,075
 259  A*03:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India West UCBB 0.05535,829
 260  A*01:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  Colombia Bogotá Cord Blood 0.05401,463
 261  A*26:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India East UCBB 0.05392,403
 262  A*24:02-B*07:02-C*07:02-DRB1*15:01-DRB5*01:01-DQB1*06:02  USA NMDP Korean 0.053677,584
 263  A*11:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India North UCBB 0.05285,849
 264  A*24:02-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*02:01  Germany DKMS - German donors 0.05133,456,066
 265  A*68:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.05042,492
 266  A*03:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.05032,492
 267  A*01:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA Hispanic pop 2 0.05001,999
 268  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India South UCBB 0.049411,446
 269  A*03:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India North UCBB 0.04935,849
 270  A*03:01-B*07:02-C*07:02-DRB1*15:01-DRB5*01:01-DQB1*06:02  USA NMDP Vietnamese 0.048343,540
 271  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA Asian pop 2 0.04801,772
 272  A*02:05-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA Hispanic pop 2 0.04701,999
 273  A*25:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA Hispanic pop 2 0.04701,999
 274  A*29:02-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA Hispanic pop 2 0.04701,999
 275  A*32:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA Hispanic pop 2 0.04701,999
 276  A*32:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India West UCBB 0.04705,829
 277  A*33:03-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA Hispanic pop 2 0.04701,999
 278  A*66:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA Hispanic pop 2 0.04701,999
 279  A*11:01:79-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.045823,595
 280  A*68:01:01:02-B*07:02:01-C*07:02:01:03-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.04551,510
 281  A*03:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*01:01  Germany DKMS - German donors 0.04543,456,066
 282  A*68:01:02-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.044423,595
 283  A*02:05-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA Asian pop 2 0.04401,772
 284  A*31:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA Asian pop 2 0.04401,772
 285  A*32:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA Asian pop 2 0.04401,772
 286  A*01:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India East UCBB 0.04372,403
 287  A*29:02-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  Germany DKMS - Italy minority 0.04301,159
 288  A*33:03-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India North UCBB 0.04265,849
 289  A*24:02-B*07:02-C*07:02-DRB1*15:01-DRB5*01:01-DQB1*06:02  USA NMDP Filipino 0.042450,614
 290  A*01:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*02:01  Germany DKMS - German donors 0.04133,456,066
 291  A*02:11-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India Central UCBB 0.04104,204
 292  A*31:01:02:01-B*07:02:01-C*07:02:01:03-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.04011,510
 293  A*24:02-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*03:01  Germany DKMS - German donors 0.03923,456,066
 294  A*26:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.03912,492
 295  A*02:11-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India North UCBB 0.03855,849
 296  A*01:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India West UCBB 0.03765,829
 297  A*03:01:01:01-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.03601,510
 298  A*11:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  Colombia Bogotá Cord Blood 0.03571,463
 299  A*26:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India West UCBB 0.03555,829
 300  A*03:01:01-B*07:02:01-C*07:02:01:03-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.03531,510

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 201 to 300 (from 398) records   Pages: 1 2 3 4 of 4  


   

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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