Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Displaying 301 to 400 (from 485) records   Pages: 1 2 3 4 5 of 5  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 301  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
 302  A*68:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.05042,492
 303  A*03:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.05032,492
 304  A*01:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA Hispanic pop 2 0.05001,999
 305  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India South UCBB 0.049411,446
 306  A*03:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India North UCBB 0.04935,849
 307  A*03:01-B*07:02-C*07:02-DRB1*15:01-DRB5*01:01-DQB1*06:02  USA NMDP Vietnamese 0.048343,540
 308  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA Asian pop 2 0.04801,772
 309  A*02:01-B*07:02-C*07:01-DRB1*15:01-DQB1*06:02  USA Hispanic pop 2 0.04701,999
 310  A*02:05-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA Hispanic pop 2 0.04701,999
 311  A*25:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA Hispanic pop 2 0.04701,999
 312  A*29:02-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA Hispanic pop 2 0.04701,999
 313  A*32:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA Hispanic pop 2 0.04701,999
 314  A*32:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India West UCBB 0.04705,829
 315  A*33:03-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA Hispanic pop 2 0.04701,999
 316  A*66:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA Hispanic pop 2 0.04701,999
 317  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
 318  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
 319  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
 320  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
 321  A*02:05-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA Asian pop 2 0.04401,772
 322  A*31:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA Asian pop 2 0.04401,772
 323  A*32:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  USA Asian pop 2 0.04401,772
 324  A*01:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India East UCBB 0.04372,403
 325  A*29:01-B*07:02-C*05:01-DRB1*15:01-DQB1*06:02  Germany DKMS - Italy minority 0.04301,159
 326  A*29:02-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  Germany DKMS - Italy minority 0.04301,159
 327  A*33:03-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India North UCBB 0.04265,849
 328  A*24:02-B*07:02-C*07:02-DRB1*15:01-DRB5*01:01-DQB1*06:02  USA NMDP Filipino 0.042450,614
 329  A*02:01:01:01-B*07:02:01-C*03:04:01:01-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.04161,510
 330  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
 331  A*02:11-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India Central UCBB 0.04104,204
 332  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
 333  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
 334  A*26:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.03912,492
 335  A*02:11-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India North UCBB 0.03855,849
 336  A*01:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India West UCBB 0.03765,829
 337  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
 338  A*11:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  Colombia Bogotá Cord Blood 0.03571,463
 339  A*26:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India West UCBB 0.03555,829
 340  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
 341  A*24:02-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*04:02  Germany DKMS - German donors 0.03513,456,066
 342  A*02:05-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  Colombia Bogotá Cord Blood 0.03421,463
 343  A*24:02-B*07:02-C*12:03-DRB1*15:01-DQB1*06:02  Colombia Bogotá Cord Blood 0.03421,463
 344  A*01:01-B*07:02-C*07:04-DRB1*15:01-DQB1*06:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 345  A*03:01-B*07:02-C*01:02-DRB1*15:01-DQB1*06:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 346  A*29:02-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 347  A*30:02-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 348  A*31:01-B*07:02-C*12:03-DRB1*15:01-DQB1*06:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 349  A*68:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 350  A*69:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 351  A*03:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*05:01  Germany DKMS - German donors 0.03393,456,066
 352  A*02:01:01:01-B*07:02:01-C*05:01:01:02-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 353  A*02:01:01:01-B*07:02:01-C*15:02:01:01-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 354  A*02:06:01-B*07:02:01-C*07:02:01:03-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 355  A*11:01:01:01-B*07:02:01-C*15:02:01:01-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 356  A*30:02:01:01-B*07:02:01-C*07:02:01:03-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 357  A*33:03:01-B*07:02:01-C*07:02:01:03-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 358  A*02:01-B*07:02-C*07:02-DRB1*15:01-DRB5*01:01-DQB1*06:02  USA NMDP Korean 0.032977,584
 359  A*32:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  Germany DKMS - Turkey minority 0.03104,856
 360  A*02:01-B*07:02-C*07:02-DRB1*15:01-DRB5*01:01-DQB1*06:02  USA NMDP Chinese 0.030799,672
 361  A*01:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*03:01  Germany DKMS - German donors 0.03063,456,066
 362  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India West UCBB 0.03065,829
 363  A*02:01-B*07:02-C*07:02-DRB1*15:01-DRB5*01:01-DQB1*06:02  USA NMDP South Asian Indian 0.0301185,391
 364  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPA1*01:03-DPB1*03:01  Japan pop 17 0.03003,078
 365  A*11:01-B*07:02-C*03:04-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 366  A*24:02-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 367  A*24:02-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPA1*01:03-DPB1*04:02  Japan pop 17 0.03003,078
 368  A*26:01-B*07:02-C*07:02-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPA1*02:02-DPB1*03:01  Japan pop 17 0.03003,078
 369  A*25:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*04:01  Germany DKMS - German donors 0.02983,456,066
 370  A*01:01:01-B*07:02:01-C*07:02:01:03-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.02971,510
 371  A*02:01:01-B*07:02:01-C*03:04:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.029523,595
 372  A*29:02:01-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.029123,595
 373  A*03:01:01-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQB1*06:02:01  China Zhejiang Han 0.02881,734
 374  A*24:02:01-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQB1*06:02:01  China Zhejiang Han 0.02881,734
 375  A*30:01:01-B*07:02:01-C*03:04:01-DRB1*15:01:01-DQB1*06:02:01  China Zhejiang Han 0.02881,734
 376  A*32:01:01-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.028123,595
 377  A*02:01-B*07:02-C*03:04-DRB1*15:01-DQB1*06:02-DPB1*04:01  Germany DKMS - German donors 0.02713,456,066
 378  A*01:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*04:02  Germany DKMS - German donors 0.02613,456,066
 379  A*29:02-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*04:01  Germany DKMS - German donors 0.02583,456,066
 380  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India Central UCBB 0.02574,204
 381  A*31:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India West UCBB 0.02575,829
 382  A*33:03-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.02422,492
 383  A*03:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*13:01  Germany DKMS - German donors 0.02403,456,066
 384  A*32:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India Central UCBB 0.02384,204
 385  A*11:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.02352,492
 386  A*11:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*02:01  Germany DKMS - German donors 0.02273,456,066
 387  A*03:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*11:01  Germany DKMS - German donors 0.02233,456,066
 388  A*33:03-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India South UCBB 0.021211,446
 389  A*33:03-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India East UCBB 0.02082,403
 390  A*03:02-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India West UCBB 0.02065,829
 391  A*26:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*02:01  Germany DKMS - German donors 0.02033,456,066
 392  A*03:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*06:01  Germany DKMS - German donors 0.02013,456,066
 393  A*68:01:01-B*07:02:01-C*07:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.019823,595
 394  A*68:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India West UCBB 0.01905,829
 395  A*03:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*10:01  Germany DKMS - German donors 0.01853,456,066
 396  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*01:01  Germany DKMS - German donors 0.01853,456,066
 397  A*03:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*09:01  Germany DKMS - German donors 0.01813,456,066
 398  A*23:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*04:01  Germany DKMS - German donors 0.01783,456,066
 399  A*02:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02-DPB1*10:01  Germany DKMS - German donors 0.01763,456,066
 400  A*30:01-B*07:02-C*07:02-DRB1*15:01-DQB1*06:02  India Central UCBB 0.01714,204

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 301 to 400 (from 485) records   Pages: 1 2 3 4 5 of 5  


   

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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