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 401 to 500 (from 9,063) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 91  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 401  A*26-B*44-DRB1*07-DQB1*02  Mexico Mexico City East 0.625079
 402  A*26-B*27-DRB1*15-DQB1*06  Mexico Hidalgo Rural 0.617381
 403  A*26:01-B*38:01-DRB1*14:01  Israel Arab pop 2 0.615012,301
 404  A*26:01-B*38:01-C*12:03-DRB1*13:01  Germany DKMS - Bosnia and Herzegovina minority 0.61401,028
 405  A*26-B*07-DRB1*03:01-DQB1*02  Mexico Guanajuato Rural 0.6135162
 406  A*26-B*18-DRB1*15-DQB1*06  Mexico Guanajuato Rural 0.6135162
 407  A*26-B*07-DRB1*04-DQB1*03:02  Mexico Tabasco, Villahermosa 0.609882
 408  A*26-B*38-DRB1*04-DQB1*03:02  Mexico Tabasco, Villahermosa 0.609882
 409  A*26-B*40:01-DRB1*01-DQB1*05  Mexico Tabasco, Villahermosa 0.609882
 410  A*26-B*44-DRB1*07-DQB1*02  Mexico Morelos, Cuernavaca 0.609882
 411  A*26-B*44-DRB1*13-DQB1*06  Mexico Tabasco, Villahermosa 0.609882
 412  A*26:01-B*35:05-C*04:01-DRB1*12:02-DQB1*03:01  USA NMDP Hawaiian or other Pacific Islander 0.601311,499
 413  A*26-B*07-DRB1*15  Germany pop 7 0.600013,386
 414  A*26:01-B*38:01-DRB1*14:01  Israel Bukhara Jews 0.59702,317
 415  A*26:01-B*14:01-DRB1*07:01-DQB1*02:02  Mexico Veracruz Xalapa 0.595284
 416  A*26:01-B*14:01-DRB1*14:01-DQB1*03:02  Mexico Veracruz Xalapa 0.595284
 417  A*26:01-B*35:01-DRB1*14:02-DQB1*03:01  Mexico Veracruz Xalapa 0.595284
 418  A*26:01-B*35:02-DRB1*01:02-DQB1*05:01  Mexico Veracruz Xalapa 0.595284
 419  A*26:01-B*38:01-DRB1*07:01-DQB1*02:02  Mexico Veracruz Xalapa 0.595284
 420  A*26-B*07-DRB1*14-DQB1*05  Mexico Zacatecas, Zacatecas city 0.595284
 421  A*26-B*14:01-DRB1*07-DQB1*02  Mexico Zacatecas, Zacatecas city 0.595284
 422  A*26-B*15:01-DRB1*11-DQB1*03:01  Mexico Jalisco, Zapopan 0.5952168
 423  A*26-B*38-DRB1*13-DQB1*06  Mexico Jalisco, Zapopan 0.5952168
 424  A*26-B*38-DRB1*13-DQB1*06  Mexico Zacatecas, Zacatecas city 0.595284
 425  A*26-B*58-DRB1*03:02-DQB1*04  Mexico Jalisco, Zapopan 0.5952168
 426  A*26:01-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  India Tamil Nadu 0.59482,492
 427  A*26:01-B*38:01-DRB1*13:02  Israel Druze 0.59405,914
 428  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.593328,927
 429  A*26:01-B*38:01-C*12:03-DRB1*13:01-DQB1*06:03  Italy pop 5 0.5900975
 430  A*26-B*07-C*07  Brazil Parana Japanese 0.5900192
 431  A*26:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DQB1*06:02:01-DPA1*02:01:01-DPB1*17:01:01  Brazil Rio de Janeiro Parda 0.5882170
 432  A*26:01:01-B*15:10:01-C*03:04:02-DRB1*13:01:01-DQB1*06:03:01-DPA1*02:02:02-DPB1*01:01:01  Brazil Rio de Janeiro Parda 0.5882170
 433  A*26:01:01-B*27:05:02-C*02:02:02-DRB1*04:04:01-DQB1*03:02:01-DPA1*01:03:05-DPB1*02:01:02  Brazil Rio de Janeiro Parda 0.5882170
 434  A*26:01:01-B*35:03:01-C*12:03:01-DRB1*15:01:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Parda 0.5882170
 435  A*26:01:01-B*51:01:01-C*07:06:01-DRB1*14:54:01-DQB1*03:02:01-DPA1*02:02:02-DPB1*04:02:01  Brazil Rio de Janeiro Parda 0.5882170
 436  A*26:01:01-B*57:01:01-C*07:01:01-DRB1*07:01:01-DQB1*03:01:04-DPA1*01:03:01-DPB1*10:01:01  Brazil Rio de Janeiro Parda 0.5882170
 437  A*26:01:01-B*07:02:01-C*07:02:01-DRB1*13:02:01-DQB1*06:04:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.5837521
 438  A*26-B*53-DRB1*13-DQB1*03:01  Mexico Veracruz, Veracruz city 0.5814171
 439  A*26:01-B*51:01-DRB1*07:01  Israel Kavkazi Jews 0.58102,840
 440  A*26:01-B*38:01-DRB1*11:04  Israel Ashkenazi Jews pop 3 0.58004,625
 441  A*26:01:01-B*35:01:01-C*04:01:01-DRB1*04:03:01-DQB1*03:02:01  India Karnataka Kannada Speaking 0.5750174
 442  A*26-B*38-DRB1*08-DQB1*04  Mexico San Luis Potosi Rural 0.574787
 443  A*26:01-B*07:02-DRB1*15:01-DQB1*06:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 444  A*26:01-B*14:01-DRB1*04:13-DQB1*03:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 445  A*26:01-B*14:01-DRB1*10:01-DQB1*05:01  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 446  A*26:01-B*15:03-DRB1*11:01-DQB1*03:01  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 447  A*26:01-B*35:01-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 448  A*26:01-B*39:01-DRB1*04:07-DQB1*03:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 449  A*26:01-B*40:02-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 450  A*26:01-B*44:02-DRB1*04:04-DQB1*03:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 451  A*26:01-B*48:01-DRB1*04:04-DQB1*03:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 452  A*26:01:01-B*15:18:01-C*07:04:01-DRB1*04:03:01-DQB1*03:02:01  India Kerala Malayalam speaking 0.5620356
 453  A*26-B*38-DRB1*11  Iran pop 4 0.5602855
 454  A*26:01-B*38:01-C*12:03-DRB1*15:01-DQB1*06:02-DPB1*04:01  Russia Karelia 0.55991,075
 455  A*26:01-B*38:01-DRB1*11:04  Israel Kavkazi Jews 0.55702,840
 456  A*26:01-B*53:01-DRB1*11:04  Israel Iran Jews 0.55708,153
 457  A*26-B*38-DRB1*13-DQB1*05  Mexico Tlaxcala, Tlaxcala city 0.5525181
 458  A*26:01-B*38:01-C*12:03-DRB1*13:01  Germany DKMS - Austria minority 0.54801,698
 459  A*26-B*14:01-DRB1*15-DQB1*06  Mexico Sinaloa Rural 0.5464183
 460  A*26-B*35-DRB1*07-DQB1*02  Mexico Sinaloa Rural 0.5464183
 461  A*26-B*44-DRB1*13-DQB1*06  Mexico Sinaloa Rural 0.5464183
 462  A*26:02-B*40:06-C*08:01-DRB1*09:01  Japan pop 16 0.542018,604
 463  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  India Andhra Pradesh Telugu Speaking 0.5376186
 464  A*26-B*41-DRB1*15-DQB1*06  Mexico Veracruz, Xalapa 0.5348187
 465  A*26:01-B*38:01-C*12:03-DRB1*04:02  Germany DKMS - Croatia minority 0.53302,057
 466  A*26-B*38-C*12-DRB1*13  Macedonia MBMDR - Macedonian 0.53241,283
 467  A*26:01-B*35:01-DRB1*04:02  Israel Poland Jews 0.532013,871
 468  A*26:01-B*38:01-C*12:03-DRB1*04:02  Germany DKMS - Romania minority 0.52701,234
 469  A*26-B*08-DRB1*13-DQB1*03:01  Mexico Aguascalientes state 0.526395
 470  A*26-B*07  Macedonia 0.5245286
 471  A*26-B*07-C*12  Macedonia 0.5245286
 472  A*26-B*07-C*12-DRB1*15  Macedonia 0.5245286
 473  A*26-B*07-DRB1*15  Macedonia 0.5245286
 474  A*26-B*08  Macedonia 0.5245286
 475  A*26-B*08-C*07  Macedonia 0.5245286
 476  A*26-B*08-C*07-DRB1*03  Macedonia 0.5245286
 477  A*26-B*08-DRB1*03  Macedonia 0.5245286
 478  A*26-B*38-C*12-DRB1*13  Macedonia 0.5245286
 479  A*26-B*38-DRB1*13  Macedonia 0.5245286
 480  A*26-C*03  Macedonia 0.5245286
 481  A*26-DRB1*03  Macedonia 0.5245286
 482  A*26-DRB1*13  Macedonia 0.5245286
 483  A*26-DRB1*14  Macedonia 0.5245286
 484  A*26-DRB1*15  Macedonia 0.5245286
 485  A*26:01-B*08:01  USA Asian pop 2 0.52301,772
 486  A*26:01:01-B*46:01:01-C*01:02:01-DRB1*09:01:02  China Jingpo Minority 0.5210105
 487  A*26:01:01-B*46:01:01-DRB1*09:01:02  China Jingpo Minority 0.5210105
 488  A*26:01:01-B*46:01:01-DRB1*15:01:01  China Jingpo Minority 0.5210105
 489  A*26:01:01-B*48:01:01-C*08:03-DRB1*08:03:02  China Jingpo Minority 0.5210105
 490  A*26:01-B*27:05-C*01:02-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPB1*04:02  USA San Diego 0.5210496
 491  A*26-B*38-C*12  Brazil Parana Japanese 0.5200192
 492  A*26:01-B*08:01-DRB1*11:01-DQB1*02:01  Iran Tabriz Azeris 0.515597
 493  A*26:01-B*18:01-DRB1*01:01-DQB1*03:02  Iran Tabriz Azeris 0.515597
 494  A*26:01-B*50:01-DRB1*11:01-DQB1*03:01  Iran Tabriz Azeris 0.515597
 495  A*26:01-B*55:02-C*01:02-DRB1*04:05-DQB1*04:01  Malaysia Peninsular Chinese 0.5155194
 496  A*26:19-B*40:01-DRB1*04:01-DQB1*03:02  Iran Tabriz Azeris 0.515597
 497  A*26-B*07-DRB1*16-DQB1*05  Mexico Nayarit, Tepic 0.515597
 498  A*26-B*08-DRB1*13-DQB1*03:01  Mexico Nayarit, Tepic 0.515597
 499  A*26-B*27-DRB1*04-DQB1*03:02  Mexico Nayarit, Tepic 0.515597
 500  A*26-B*44-DRB1*04-DQB1*03:02  Mexico Nayarit, Tepic 0.515597

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 401 to 500 (from 9,063) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 91  


   

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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