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 401 to 500 (from 7,027) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 71  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 401  A*11:01-B*35:01-C*03:03-DRB1*15:01-DQB1*06:02  Malaysia Peninsular Chinese 0.7732194
 402  A*02:01-B*35:01-DRB1*11:01-DQB1*03:02  Chile Mapuche 0.770066
 403  A*03:01-B*35:01-DRB1*14:02-DQB1*03:03  Chile Mapuche 0.770066
 404  A*30:02-B*35:01-DRB1*03:01-DQB1*02:01  Chile Mapuche 0.770066
 405  A*24:02-B*35:01-C*04:01-DRB1*14:02-DRB3*01:01-DQB1*03:01  USA NMDP North American Amerindian 0.758435,791
 406  A*02:01-B*35:01-C*07:02-DRB1*14:02-DQA1*05:03-DQB1*03:04  Mexico Tixcacaltuyub Maya 0.746367
 407  A*03:01-B*35:01-C*04:01-DRB1*11:01-DQA1*05:05-DQB1*03:19  Mexico Tixcacaltuyub Maya 0.746367
 408  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQA1*01:01-DQB1*05:01  Mexico Tixcacaltuyub Maya 0.746367
 409  A*24:02-B*35:01-C*03:04-DRB1*14:02-DQA1*05:03-DQB1*03:01  Mexico Tixcacaltuyub Maya 0.746367
 410  A*24:02-B*35:01-C*04:01-DRB1*04:07-DQA1*03:01-DQB1*03:02  Mexico Tixcacaltuyub Maya 0.746367
 411  A*24:02-B*35:01-C*04:01-DRB1*04:25-DQA1*03:03-DQB1*04:02  Mexico Tixcacaltuyub Maya 0.746367
 412  A*26:01-B*35:01-C*04:01-DRB1*04:02-DQA1*03:01-DQB1*03:02  Mexico Tixcacaltuyub Maya 0.746367
 413  A*31:01-B*35:01-C*07:02-DRB1*16:02-DQA1*05:05-DQB1*03:01  Mexico Tixcacaltuyub Maya 0.746367
 414  A*68:01-B*35:01-C*07:02-DRB1*04:07-DQA1*03:01-DQB1*03:02  Mexico Tixcacaltuyub Maya 0.746367
 415  A*68:03-B*35:01-C*04:01-DRB1*13:02-DQA1*01:02-DQB1*05:01  Mexico Tixcacaltuyub Maya 0.746367
 416  A*02:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  Italy pop 5 0.7400975
 417  A*02:01-B*35:01-C*04:01-DRB1*14:02-DRB3*01:01-DQB1*03:01  USA NMDP North American Amerindian 0.714035,791
 418  B*35:01-DRB1*03:01  Italy pop 5 0.7100975
 419  A*11:01-B*35:01  USA Hispanic pop 2 0.70901,999
 420  A*26:01-B*35:01-DRB1*04:02  Israel Kavkazi Jews 0.70802,840
 421  A*74:01:01-B*35:01:01-C*04:01:01-DRB1*15:03:01-DQB1*06:02:01-DPB1*02:01:02  South African Black 0.7040142
 422  A*24:02:01-B*35:01:01-C*04:01:01-DRB1*11:01:01-DQB1*03:01:01  India Kerala Malayalam speaking 0.7020356
 423  A*02:01:01-B*35:01:01-C*04:01:01-DRB1*01:01:01-DQB1*05:01:01  Spain, Canary Islands, Gran canaria island 0.7000215
 424  A*02:01-B*35:01-C*04:01-DRB1*01:01  Italy pop 5 0.7000975
 425  A*11:01-B*35:01-C*04:01-DRB1*01:01  Italy pop 5 0.7000975
 426  A*24:02-B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.6993143
 427  A*68:01-B*35:01-C*04:01-DRB1*04:04-DQB1*03:02  Mexico Mexico City Mestizo population 0.6993143
 428  B*35:01-C*03:04  Mexico Mexico City Mestizo population 0.6993143
 429  B*35:01-C*03:04-DRB1*04:07-DQB1*03:02  Mexico Mexico City Mestizo population 0.6993143
 430  B*35:01-C*04:01-DRB1*04:04-DQB1*03:02  Mexico Mexico City Mestizo population 0.6993143
 431  B*35:01-C*04:01-DRB1*04:07-DQB1*03:02  Mexico Mexico City Mestizo population 0.6993143
 432  A*02:01:01-B*35:01:01-C*03:02:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 433  A*02:01:01-B*35:01:01-C*03:03:01-DRB1*14:06:01-DQB1*03:01:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 434  A*02:01:01-B*35:01:01-C*04:01:01-DRB1*01:02:01-DQB1*05:01:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 435  A*02:01:01-B*35:01:01-C*04:01:01-DRB1*04:04:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 436  A*02:01:01-B*35:01:01-C*04:01:01-DRB1*04:07:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 437  A*02:01:01-B*35:01:01-C*08:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 438  A*02:01-B*35:01-C*04:01-DRB1*01:01  Brazil Vale do Ribeira Quilombos 0.6944144
 439  A*03:01-B*35:01-C*04:01-DRB1*08:01  Brazil Vale do Ribeira Quilombos 0.6944144
 440  A*11:01:01-B*35:01:01-C*07:01:01-DRB1*04:07:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 441  A*24:02:01-B*35:01:01-C*04:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 442  A*31:01:02-B*35:01:01-C*04:01:01-DRB1*01:03:01-DQB1*05:01:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 443  A*31:01:02-B*35:01:01-C*04:01:01-DRB1*04:11:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 444  A*31:01:02-B*35:01:01-C*15:02:01-DRB1*04:07:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 445  A*68:01:01-B*35:01:01-C*04:01:01-DRB1*03:01:01-DQB1*03:01:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 446  A*68:01:01-B*35:01:01-C*04:01:01-DRB1*04:07:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 447  A*68:01:01-B*35:01:01-C*04:01:01-DRB1*16:02:01-DQB1*03:01:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 448  A*68:03:01-B*35:01:01-C*04:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 449  A*03:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  USA NMDP Alaska Native or Aleut 0.69131,376
 450  A*24:14-B*35:01-C*04:01-DRB1*04:04-DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.6881218
 451  A*68:03-B*35:01-C*07:02-DRB1*04:07-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*05:01  Mexico Chiapas Lacandon Mayans 0.6881218
 452  A*03:01-B*35:01-C*04:01-DRB1*01:01  Germany DKMS - Bosnia and Herzegovina minority 0.68601,028
 453  A*11:01-B*35:01-C*04:01-DRB1*01:01  Germany DKMS - Romania minority 0.68501,234
 454  A*33:03-B*35:01-C*04:01-DRB1*13:01-DQB1*06:03  India Northeast UCBB 0.6757296
 455  A*03:01:01-B*35:01:01-C*04:01:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.673223,595
 456  A*11:01:01:01-B*35:01:01-C*04:01:01-DRB1*01:01:01-DQB1*05:01  Russia Nizhny Novgorod, Russians 0.67021,510
 457  A*11:01-B*35:01-DRB1*01:01  Croatia pop 4 0.67004,000
 458  A*03:01-B*35:01-C*04:01-DRB1*01:02-DQA1*01:01-DQB1*05:01  Brazil Puyanawa 0.6667150
 459  A*24:02-B*35:01-C*04:01-DRB1*14:02-DQB1*03:01  USA NMDP Alaska Native or Aleut 0.66491,376
 460  A*24:04-B*35:01-DRB1*04:02  Israel Kavkazi Jews 0.65402,840
 461  B*35:01-DRB1*07:01  Italy pop 5 0.6500975
 462  A*24:02-B*35:01-C*04:01-DRB1*04:04-DQA1*03:01-DQB1*03:02-DPB1*04:02  Nicaragua Managua 0.6494339
 463  A*01:01-B*35:01-DRB1*11:04  Israel Bukhara Jews 0.64702,317
 464  A*11:01:01-B*35:01:01-C*04:01:01-DRB1*01:01  Nicaragua Mestizo (G) 0.6452155
 465  A*11:01:01-B*35:01:01-C*04:01:01-DRB1*15:03  Nicaragua Mestizo (G) 0.6452155
 466  A*24:02:01-B*35:01:01-C*04:01:01-DRB1*04:07  Nicaragua Mestizo (G) 0.6452155
 467  B*35:01-C*03:05-DRB1*04:07-DQB1*03:02  Mexico Mexico City Mestizo pop 2 0.6400234
 468  B*35:01-C*04:01-DRB1*04:04-DQB1*03:02  Mexico Mexico City Mestizo pop 2 0.6400234
 469  B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.6400234
 470  A*31:04-B*35:01-C*15:05-DRB1*13:02-DQB1*06:04-DPB1*02:01  Tanzania Maasai 0.6390336
 471  A*03:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01-DPB1*04:02  Germany DKMS - German donors 0.63673,456,066
 472  A*11:01-B*35:01-C*04:01-DRB1*01:01  Germany DKMS - Portugal minority 0.63201,176
 473  A*24:02-B*35:01-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uros 0.6300105
 474  B*35:01-DRB1*14:01  Italy pop 5 0.6300975
 475  A*03:01:01-B*35:01:01-C*04:01:01-DRB1*01:01:01-DQB1*05:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.6250405
 476  A*11:01:01-B*35:01:01-C*04:01:01-DRB1*01:03:01-DQB1*05:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.6250405
 477  A*11:01:01-B*35:01:01-C*04:01:01-DRB1*07:01:01-DQB1*05:01:01-DPA1*02:01:01-DPB1*17:01:01  Brazil Barra Mansa Rio State Caucasian 0.6250405
 478  A*03:01-B*35:01-C*04:01-DRB1*01:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.61381,463
 479  A*02:01-B*35:01-DRB1*03:01-DQB1*02:01  Mexico Mexico City Tlalpan 0.6061330
 480  A*24:02-B*35:01-DRB1*04:07-DQB1*03:02  Mexico Mexico City Tlalpan 0.6061330
 481  A*24:02-B*35:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 0.6061330
 482  A*11:01-B*35:01-C*04:01-DRB1*01:01  Germany DKMS - Austria minority 0.60401,698
 483  A*03:01-B*35:01-C*04:01-DRB1*15:03-DQA1*01:02-DQB1*06:02-DPB1*02:01  South Africa Worcester 0.6000159
 484  A*11:01-B*35:01-C*04:01-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPB1*02:01  South Africa Worcester 0.6000159
 485  A*74:01-B*35:01-C*04:01-DRB1*04:05-DQA1*03:01-DQB1*03:02-DPB1*02:01  South Africa Worcester 0.6000159
 486  A*11:01-B*35:01-C*04:01-DRB1*15:02-DQB1*06:01  India East UCBB 0.59882,403
 487  A*31:01-B*35:01  USA Hispanic pop 2 0.59801,999
 488  A*03:01-B*35:01-C*04:01-DRB1*01:01  Germany DKMS - Portugal minority 0.59601,176
 489  A*02:01-B*35:01-DRB1*03:01-DQB1*02:01  Mexico Veracruz Xalapa 0.595284
 490  A*02:01-B*35:01-DRB1*04:04-DQB1*03:02  Mexico Veracruz Xalapa 0.595284
 491  A*02:01-B*35:01-DRB1*04:11-DQB1*04:02  Mexico Veracruz Xalapa 0.595284
 492  A*02:01-B*35:01-DRB1*08:01-DQB1*04:02  Mexico Veracruz Xalapa 0.595284
 493  A*02:01-B*35:01-DRB1*13:01-DQB1*06:03  Mexico Veracruz Xalapa 0.595284
 494  A*02:02-B*35:01-DRB1*04:07-DQB1*03:02  Mexico Veracruz Xalapa 0.595284
 495  A*23:01-B*35:01-DRB1*04:04-DQB1*03:02  Mexico Veracruz Xalapa 0.595284
 496  A*26:01-B*35:01-DRB1*14:02-DQB1*03:01  Mexico Veracruz Xalapa 0.595284
 497  A*31:01-B*35:01-DRB1*04:07-DQB1*03:02  Mexico Veracruz Xalapa 0.595284
 498  A*31:01-B*35:01-DRB1*14:02-DQB1*03:01  Mexico Veracruz Xalapa 0.595284
 499  A*68:01-B*35:01-DRB1*04:02-DQB1*03:02  Mexico Veracruz Xalapa 0.595284
 500  A*68:01-B*35:01-DRB1*04:03-DQB1*03:02  Mexico Veracruz Xalapa 0.595284

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 7,027) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 71  


   

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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