Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Population:  Country:  Source of dataset : 
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Sample Size:      Sample Year:     Loci Tested: 
Displaying 401 to 500 (from 5,509) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 56  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 401  A*24:08-B*51:01-C*08:01-DRB1*15:01-DQB1*06:03  Iran Gorgan 0.780064
 402  A*29:01-B*15:10-C*08:01-DRB1*13:01-DQB1*03:02  Iran Gorgan 0.780064
 403  A*31:01-B*35:01-C*08:01-DRB1*12:01-DQB1*03:01  Iran Gorgan 0.780064
 404  A*31:01-B*35:27-C*08:01-DRB1*11:01-DQB1*06:02  Iran Gorgan 0.780064
 405  A*32:03-B*14:01-C*08:01-DRB1*04:01-DQB1*05:01  Iran Gorgan 0.780064
 406  A*33:01-B*14:02-C*08:01-DRB1*01:01-DQB1*06:01  Iran Gorgan 0.780064
 407  A*02:01-B*15:02-C*08:01-DRB1*12:01-DQB1*03:01  Malaysia Peninsular Chinese 0.7732194
 408  A*11:01-B*15:02-C*08:01-DRB1*12:02-DQB1*03:01  Malaysia Peninsular Chinese 0.7732194
 409  A*33:01-B*14:02-C*08:02-DRB1*03:01  Germany DKMS - Bosnia and Herzegovina minority 0.76901,028
 410  B*81:01-C*08:04  USA African American pop 4 0.76902,411
 411  A*11:01-B*15:02-C*08:01-DRB1*12:02-DRB3*03:01-DQB1*03:01  USA NMDP Southeast Asian 0.750927,978
 412  A*24:02-B*14:01-C*08:02-DRB1*13:03-DQA1*02:01-DQB1*02:02  Mexico Tixcacaltuyub Maya 0.746367
 413  A*68:01-B*48:01-C*08:03-DRB1*04:11-DQA1*03:01-DQB1*03:02  Mexico Tixcacaltuyub Maya 0.746367
 414  A*68:03-B*48:01-C*08:03-DRB1*04:04-DQA1*03:01-DQB1*03:02  Mexico Tixcacaltuyub Maya 0.746367
 415  A*33:01-B*14:02-C*08:02-DRB1*01:02  Germany DKMS - Greece minority 0.73701,894
 416  A*02:01-C*08:02  Italy pop 5 0.7200975
 417  A*30:04-B*14:01-C*08:02-DRB1*04:04-DRB4*01:01-DQB1*04:02  USA NMDP Korean 0.718777,584
 418  A*02-B*14-C*08-DRB1*01-DQA1*01-DQB1*05  Spain, Castilla y Leon, Northwest, 0.71031,743
 419  A*24:02-B*40:06-C*08:01-DRB1*09:01  Japan pop 16 0.709018,604
 420  B*14:01-C*08:02  USA African American pop 4 0.70602,411
 421  A*11:01-B*48:01-C*08:01-DRB1*08:03-DQB1*06:01  USA NMDP Hawaiian or other Pacific Islander 0.705611,499
 422  A*26:01:01-B*14:01:01-C*08:02:01-DRB1*07:01:01-DQB1*02:02:01  Spain, Canary Islands, Gran canaria island 0.7000215
 423  A*32:01:01-B*14:02:01-C*08:02:01-DRB1*03:01:01-DQB1*02:01:01  Spain, Canary Islands, Gran canaria island 0.7000215
 424  A*68:02-B*14:02-C*08:02-DRB1*01:02-DQB1*05:01  Mexico Mexico City Mestizo population 0.6993143
 425  B*48:01-C*08:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.6993143
 426  A*24:02:01-B*40:06:01-C*08:01:01-DRB1*09:01:02-DQB1*03:03:02  China Zhejiang Han 0.69911,734
 427  A*02:01:01-B*15:01:01-C*08:01:01-DRB1*04:07:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 428  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
 429  A*02:01:01-B*48:01:01-C*08:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 430  A*02:01:01-B*48:01:01-C*08:01:01-DRB1*14:02:01-DQB1*03:01:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 431  A*02:01:01-B*51:01:01-C*08:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 432  A*02:02-B*14:02-C*08:02-DRB1*15:03  Brazil Vale do Ribeira Quilombos 0.6944144
 433  A*02-B*48-C*08-DRB1*04-DQA1*03-DQB1*03  Mexico Tapachula, Chiapas Mestizo Population 0.694472
 434  A*02-B*51-C*08-DRB1*04-DQA1*03-DQB1*03  Mexico Tapachula, Chiapas Mestizo Population 0.694472
 435  A*03:01:01-B*48:01:01-C*08:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 436  A*03:01:02-B*48:01:01-C*08:01:01-DRB1*14:02:01-DQB1*03:01:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 437  A*24:02:01-B*39:01:01-C*08:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 438  A*24:02:01-B*40:02:01-C*08:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 439  A*24:02:01-B*48:01:01-C*08:01:01-DRB1*01:02:01-DQB1*05:01:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 440  A*24:02:01-B*48:01:01-C*08:01:01-DRB1*04:04:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 441  A*24:02:01-B*51:01:01-C*08:01:01-DRB1*04:07:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 442  A*26-B*07-C*08-DRB1*04-DQA1*03-DQB1*03  Mexico Tapachula, Chiapas Mestizo Population 0.694472
 443  A*29:02-B*14:02-C*08:02-DRB1*08:02  Brazil Vale do Ribeira Quilombos 0.6944144
 444  A*30:02-B*13:02-C*08:04-DRB1*08:04  Brazil Vale do Ribeira Quilombos 0.6944144
 445  A*31:01:02-B*48:01:01-C*08:01:01-DRB1*04:07:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 446  A*33:01:01-B*14:02:01-C*08:01:01-DRB1*01:02:01-DQB1*05:01:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 447  A*33-B*14-C*08-DRB1*04-DQA1*03-DQB1*03  Mexico Tapachula, Chiapas Mestizo Population 0.694472
 448  A*33-B*14-C*08-DRB1*15-DQA1*01-DQB1*06  Mexico Tapachula, Chiapas Mestizo Population 0.694472
 449  A*66:01:01-B*48:01:01-C*08:01:01-DRB1*04:04:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 450  A*68:01:01-B*48:01:01-C*08:01:01-DRB1*04:07:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 451  A*68:01:01-B*48:01:01-C*08:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 452  A*68:01:01-B*48:01:01-C*08:01:01-DRB1*14:06:01-DQB1*03:01:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 453  A*68-B*51-C*08-DRB1*01-DQA1*01-DQB1*05  Mexico Tapachula, Chiapas Mestizo Population 0.694472
 454  A*74:01-B*14:02-C*08:02-DRB1*08:04  Brazil Vale do Ribeira Quilombos 0.6944144
 455  B*07-C*08  Mexico Tapachula, Chiapas Mestizo Population 0.694472
 456  B*07-C*08-DRB1*04-DQA1*03-DQB1*03  Mexico Tapachula, Chiapas Mestizo Population 0.694472
 457  B*14-C*08-DRB1*04-DQA1*03-DQB1*03  Mexico Tapachula, Chiapas Mestizo Population 0.694472
 458  B*14-C*08-DRB1*15-DQA1*01-DQB1*06  Mexico Tapachula, Chiapas Mestizo Population 0.694472
 459  B*48-C*08  Mexico Tapachula, Chiapas Mestizo Population 0.694472
 460  B*48-C*08-DRB1*04-DQA1*03-DQB1*03  Mexico Tapachula, Chiapas Mestizo Population 0.694472
 461  B*51-C*08-DRB1*01-DQA1*01-DQB1*05  Mexico Tapachula, Chiapas Mestizo Population 0.694472
 462  B*51-C*08-DRB1*04-DQA1*03-DQB1*03  Mexico Tapachula, Chiapas Mestizo Population 0.694472
 463  A*02:01-B*15:13-C*08:01-DRB1*12:02-DQB1*03:01  Malaysia Peninsular Malay 0.6835951
 464  A*32:01:01-B*14:01:01-C*08:02:01  England Blood Donors of Mixed Ethnicity 0.6686519
 465  A*02-B*48-C*08:03-DRB1*09:01-DQB1*03  Russia Transbaikal Territory Buryats 0.6670150
 466  A*31:01-B*39:05-C*08:03-DRB1*16:02-DQA1*01:02-DQB1*03:02  Brazil Puyanawa 0.6667150
 467  A*74:01-B*14:02-C*08:02-DRB1*01:02-DQA1*01:01-DQB1*05:01  Brazil Puyanawa 0.6667150
 468  A*68:02-B*14:02-C*08:02-DRB1*01:02-DQA1*01:01-DQB1*05:01-DPB1*04:02  Nicaragua Managua 0.6494339
 469  A*02:01:01-B*48:01:01-C*08:01:01-DRB1*04:07  Nicaragua Mestizo (G) 0.6452155
 470  A*33:01:01-B*14:02:01-C*08:02:01-DRB1*13:02:01  Nicaragua Mestizo (G) 0.6452155
 471  A*02:01-B*48:01-C*08:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.6410234
 472  A*02:06-B*48:01-C*08:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.6410234
 473  B*14:01-C*08:02-DRB1*07:01-DQB1*02:02  Mexico Mexico City Mestizo pop 2 0.6400234
 474  B*48:01-C*08:01-DRB1*04:04-DQB1*03:02  Mexico Mexico City Mestizo pop 2 0.6400234
 475  B*48:01-C*08:03  Mexico Mexico City Mestizo pop 2 0.6400234
 476  A*02:06-B*15:02-C*08:01-DRB1*12:02  Hong Kong Chinese BMDR 0.62907,595
 477  A*02:01:01-B*14:02:01-C*08:02:01-DRB1*01:02:01-DQB1*05:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.6250405
 478  A*11:01:01-B*15:02:01-C*08:01:01-DRB1*15:01:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.62405,266
 479  A*24:02-B*15:13-C*08:01-DRB1*12:01-DQB1*03:01  Malaysia Peninsular Malay 0.6186951
 480  A*33:01-B*14:02-C*08:02-DRB1*01:02  Germany DKMS - Romania minority 0.60801,234
 481  A*33:01-B*14:02-C*08:02-DRB1*01:02-DRBX*NNNN-DQB1*05:01  USA NMDP Caribean Hispanic 0.6030115,374
 482  A*02:11-B*14:02-C*08:02-DRB1*01:02-DQA1*01:03-DQB1*06:01-DPB1*13:01  South Africa Worcester 0.6000159
 483  A*68:02-B*14:02-C*08:02-DRB1*15:03-DQA1*01:02-DQB1*06:02-DPB1*34:01  South Africa Worcester 0.6000159
 484  A*68:02-B*15:10-C*08:04-DRB1*11:01-DQA1*01:02-DQB1*06:02-DPB1*03:01  South Africa Worcester 0.6000159
 485  A*03:01:01-B*14:03-C*08:02:01-DRB1*01:02:01-DQB1*05:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Parda 0.5882170
 486  A*23:01:01-B*14:02:01-C*08:02:01-DRB1*03:02:01-DQB1*04:02:01-DPA1*02:02:02-DPB1*01:01:01  Brazil Rio de Janeiro Parda 0.5882170
 487  A*30:02:01-B*13:02:01-C*08:04:01-DRB1*13:02:01-DQB1*06:04:01-DPA1*01:03:01-DPB1*02:01:19  Brazil Rio de Janeiro Parda 0.5882170
 488  A*30:02:01-B*14:02:01-C*08:02:01-DRB1*15:03:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Parda 0.5882170
 489  A*33:01:01-B*44:03:01-C*08:02:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Parda 0.5882170
 490  A*33:01:01-B*57:01:01-C*08:02:01-DRB1*07:01:01-DQB1*03:01:04-DPA1*02:01:08-DPB1*03:01:01  Brazil Rio de Janeiro Parda 0.5882170
 491  A*33:03:01-B*18:01:01-C*08:02:01-DRB1*15:03:01-DQB1*06:02:01-DPA1*03:01:01-DPB1*105:01:01  Brazil Rio de Janeiro Parda 0.5882170
 492  A*36:01-B*14:01:01-C*08:02:01-DRB1*01:01:01-DQB1*05:01:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Parda 0.5882170
 493  A*68:02:01-B*13:02:01-C*08:04:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*01:03:01-DPB1*01:01:01  Brazil Rio de Janeiro Parda 0.5882170
 494  A*33:01-B*14:02-C*08:02-DRB1*01:02  Germany DKMS - Bosnia and Herzegovina minority 0.58201,028
 495  A*68:02-B*14:02-C*08:02-DRB1*01:02-DQB1*05:01  Colombia Bogotá Cord Blood 0.58011,463
 496  A*24:17-B*15:02-C*08:01-DRB1*12:02-DRB3*03:01-DQB1*03:01  USA NMDP South Asian Indian 0.5793185,391
 497  A*68:01-B*48:01-C*08:01-DRB1*04:04-DRB4*01:01-DQB1*03:02  USA NMDP Mexican or Chicano 0.5750261,235
 498  A*24:17-B*15:02-C*08:01-DRB1*12:02-DQA1*06:01-DQB1*03:01-DPB1*02:01  Sri Lanka Colombo 0.5602714
 499  A*11:01-B*15:02-C*08:01-DRB1*15:01  Germany DKMS - China minority 0.54701,282
 500  A*26:02-B*40:06-C*08:01-DRB1*09:01  Japan pop 16 0.542018,604

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 5,509) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 56  


   

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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