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 501 to 600 (from 666) records   Pages: 1 2 3 4 5 6 7 of 7  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 501  A*68:03-B*39:02-DRB1*04:07-DQB1*03:02  Mexico Mexico City Tlalpan 0.1515330
 502  A*01-B*39-DRB1*04-DQB1*03:02  Mexico Michoacan Rural 0.1433348
 503  A*02:01-B*39:06-C*07:02-DRB1*04:03-DQB1*03:02  Italy pop 5 0.1400975
 504  A*11:01:01-B*39:01:01-C*03:03:01-DRB1*04:04:01-DQB1*03:02:01  India Kerala Malayalam speaking 0.1400356
 505  A*24:02-B*39:01-C*12:03-DRB1*04:02-DQB1*03:02  Italy pop 5 0.1400975
 506  A*24:02-B*39:06-C*07:02-DRB1*04:05-DQB1*03:02  Italy pop 5 0.1400975
 507  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*04:04:01-DQB1*03:02:01  India Kerala Malayalam speaking 0.1400356
 508  A*02:01-B*39:01-C*07:02-DRB1*04:04-DQB1*03:02-DPB1*04:01  Russia Karelia 0.13411,075
 509  A*01:01-B*39:05-C*07:02-DRB1*04:07-DQB1*03:02  USA Hispanic pop 2 0.13401,999
 510  A*01-B*39-DRB1*04-DQB1*03:02  Mexico Coahuila, Torreon 0.1250396
 511  A*24:02-B*39:01-C*07:02-DRB1*04:04-DQB1*03:02-DPB1*04:02  Russia Karelia 0.12171,075
 512  A*02:01:01-B*39:01:01-C*07:02:01-DRB1*04:04:01-DQB1*03:02:01  China Zhejiang Han 0.11531,734
 513  A*68:01-B*39:06-C*07:02-DRB1*04:05-DQB1*03:02  USA NMDP Black South or Central American 0.11294,889
 514  A*24:02-B*39:01-C*07:02-DRB1*04:04-DQB1*03:02-DPB1*03:01  Russia Karelia 0.10431,075
 515  A*02:01:01-B*39:24-C*07:01:01-DRB1*04:01:01-DQB1*03:02:01-DPB1*17:01:01  Saudi Arabia pop 6 (G) 0.101028,927
 516  A*68:01-B*39:05-C*07:02-DRB1*04:04-DQB1*03:02  USA Hispanic pop 2 0.09401,999
 517  A*68:05-B*39:08-C*07:02-DRB1*04:07-DQB1*03:02  USA Hispanic pop 2 0.09401,999
 518  A*01-B*39-DRB1*04-DQB1*03:02  Mexico Veracruz Rural 0.0924539
 519  A*11-B*39-DRB1*04-DQB1*03:02  Mexico Veracruz Rural 0.0924539
 520  A*24:02-B*39:06-C*07:02-DRB1*04:07-DQB1*03:02  USA Hispanic pop 2 0.09101,999
 521  A*02-B*39-DRB1*04:11-DQA1*03:01-DQB1*03:02  Brazil Paraná Caucasian 0.0780641
 522  A*29-B*39-DRB1*04:04-DQA1*03:01-DQB1*03:02  Brazil Paraná Caucasian 0.0780641
 523  A*31-B*39-DRB1*04:04-DQA1*03:01-DQB1*03:02  Brazil Paraná Caucasian 0.0780641
 524  A*68:03-B*39:05-C*07:02-DRB1*04:07-DRB4*01:01-DQB1*03:02  USA NMDP Caribean Hispanic 0.0774115,374
 525  A*02:06-B*39:05-C*07:02-DRB1*04:07-DRB4*01:01-DQB1*03:02  USA NMDP Caribean Hispanic 0.0732115,374
 526  A*11:01:01-B*39:01:01-C*07:02:01-DRB1*04:06:01-DQB1*03:02:01  China Zhejiang Han 0.07311,734
 527  A*68:01-B*39:01-C*12:03-DRB1*04:04-DQA1*03:01-DQB1*03:02-DPB1*04:01  Sri Lanka Colombo 0.0700714
 528  A*24:02-B*39:02-C*07:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*02:01-DPB1*05:01  Japan pop 17 0.07003,078
 529  A*26:02-B*39:01-C*07:02-DRB1*04:06-DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.07003,078
 530  A*26:03-B*39:01-C*07:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*02:01-DPB1*05:01  Japan pop 17 0.07003,078
 531  A*03:01:01:01-B*39:01:01:03-C*07:02:01-DRB1*04:04:01-DQB1*03:02  Russia Nizhny Novgorod, Russians 0.06851,510
 532  A*66-B*39-DRB1*04-DQB1*03:02  Mexico Mexico City North 0.0664751
 533  A*01-B*39-DRB1*04-DQB1*03:02  Ecuador Andes Mixed Ancestry 0.0607824
 534  A*31:01-B*39:01-C*12:03-DRB1*04:04-DQB1*03:02  India Tamil Nadu 0.06022,492
 535  A*01-B*39-DRB1*04-DQB1*03:02  Mexico Tlaxcala Rural 0.0602830
 536  A*31:01-B*39:01-C*12:03-DRB1*04:04-DQB1*03:02  India South UCBB 0.059411,446
 537  A*68:01-B*39:01-C*07:02-DRB1*04:04-DQB1*03:02-DPB1*04:02  Russia Karelia 0.05651,075
 538  A*03:01-B*39:01-C*12:03-DRB1*04:01-DQB1*03:02-DPB1*04:02  Russia Karelia 0.05651,075
 539  A*24:02-B*39:01-C*07:02-DRB1*04:01-DQB1*03:02-DPB1*02:01  Russia Karelia 0.05581,075
 540  A*02:01-B*39:05-C*07:02-DRB1*04:07-DQB1*03:02  USA Hispanic pop 2 0.05301,999
 541  A*31:01-B*39:05-C*07:02-DRB1*04:11-DQB1*03:02  Colombia Bogotá Cord Blood 0.05061,463
 542  A*03-B*39-DRB1*04-DQB1*03:02  Mexico Puebla, Puebla city 0.05011,994
 543  A*02:06-B*39:06-C*07:02-DRB1*04:07-DQB1*03:02  USA Hispanic pop 2 0.04901,999
 544  A*24:02-B*39:05-C*07:02-DRB1*04:07-DQB1*03:02  USA Hispanic pop 2 0.04901,999
 545  A*02:01-B*39:05-C*03:05-DRB1*04:11-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 546  A*02:01-B*39:06-C*07:02-DRB1*04:07-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 547  A*02:01-B*39:08-C*07:02-DRB1*04:04-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 548  A*02:06-B*39:02-C*03:04-DRB1*04:07-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 549  A*02:22-B*39:05-C*08:03-DRB1*04:11-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 550  A*24:02-B*39:01-C*12:03-DRB1*04:03-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 551  A*24:02-B*39:14-C*07:02-DRB1*04:04-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 552  A*31:01-B*39:01-C*01:02-DRB1*04:03-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 553  A*31:01-B*39:05-C*07:02-DRB1*04:04-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 554  A*31:01-B*39:06-C*01:02-DRB1*04:04-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 555  A*31:01-B*39:06-C*07:02-DRB1*04:11-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 556  A*68:01-B*39:02-C*03:04-DRB1*04:07-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 557  A*68:01-B*39:02-C*07:02-DRB1*04:04-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 558  A*68:01-B*39:05-C*07:02-DRB1*04:07-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 559  A*68:01-B*39:06-C*07:02-DRB1*04:04-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 560  A*68:03-B*39:08-C*07:02-DRB1*04:07-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 561  A*68:07-B*39:08-C*07:02-DRB1*04:03-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 562  A*11:01-B*39:01-C*07:02-DRB1*04:03-DQB1*03:02  USA Asian pop 2 0.04401,772
 563  A*32:01-B*39:01-C*12:03-DRB1*04:03-DQB1*03:02  Germany DKMS - Italy minority 0.04301,159
 564  A*01-B*39-DRB1*04-DQB1*03:02  Ecuador Mixed Ancestry 0.04261,173
 565  A*01-B*39-DRB1*04-DQB1*03:02  Mexico Jalisco, Guadalajara city 0.04191,189
 566  A*30-B*39-DRB1*04-DQB1*03:02  Mexico Jalisco, Guadalajara city 0.04191,189
 567  A*33-B*39-DRB1*04-DQB1*03:02  Mexico Jalisco, Guadalajara city 0.04191,189
 568  A*24:02-B*39:05-C*07:02-DRB1*04:07-DQB1*03:02  Colombia Bogotá Cord Blood 0.04131,463
 569  A*24:02:01-B*39:05:01-C*07:02:01-DRB1*04:06:01-DQB1*03:02:01  China Zhejiang Han 0.03611,734
 570  A*02:01-B*39:05-C*08:03-DRB1*04:11-DQB1*03:02  Colombia Bogotá Cord Blood 0.03421,463
 571  A*02:04-B*39:05-C*07:02-DRB1*04:11-DQB1*03:02  Colombia Bogotá Cord Blood 0.03421,463
 572  A*02:22-B*39:05-C*07:02-DRB1*04:11-DQB1*03:02  Colombia Bogotá Cord Blood 0.03421,463
 573  A*02:22-B*39:08-C*07:02-DRB1*04:07-DQB1*03:02  Colombia Bogotá Cord Blood 0.03421,463
 574  A*11:01-B*39:01-C*01:02-DRB1*04:07-DQB1*03:02  Colombia Bogotá Cord Blood 0.03421,463
 575  A*11:01-B*39:06-C*07:02-DRB1*04:01-DQB1*03:02  Colombia Bogotá Cord Blood 0.03421,463
 576  A*24:02-B*39:05-C*08:01-DRB1*04:04-DQB1*03:02  Colombia Bogotá Cord Blood 0.03421,463
 577  A*24:02-B*39:06-C*07:02-DRB1*04:07-DQB1*03:02  Colombia Bogotá Cord Blood 0.03421,463
 578  A*24:02-B*39:11-C*07:02-DRB1*04:04-DQB1*03:02  Colombia Bogotá Cord Blood 0.03421,463
 579  A*26:01-B*39:05-C*07:02-DRB1*04:07-DQB1*03:02  Colombia Bogotá Cord Blood 0.03421,463
 580  A*32:01-B*39:11-C*07:02-DRB1*04:07-DQB1*03:02  Colombia Bogotá Cord Blood 0.03421,463
 581  A*68:01-B*39:08-C*07:02-DRB1*04:07-DQB1*03:02  Colombia Bogotá Cord Blood 0.03421,463
 582  A*01:01-B*39:01-C*12:03-DRB1*04:04-DQB1*03:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 583  A*02:22-B*39:09-C*07:02-DRB1*04:04-DQB1*03:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 584  A*24:02-B*39:06-C*07:02-DRB1*04:04-DQB1*03:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 585  A*68:01-B*39:14-C*07:02-DRB1*04:04-DQB1*03:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 586  A*03:01:01:01-B*39:01:01-C*12:03:01:01-DRB1*04:01:01-DQB1*03:02  Russia Nizhny Novgorod, Russians 0.03311,510
 587  A*24:02:01:01-B*39:01:01-C*07:02:01-DRB1*04:04:01-DQB1*03:02  Russia Nizhny Novgorod, Russians 0.03311,510
 588  A*24:02:01:01-B*39:06:02-C*16:02:01-DRB1*04:03:01-DQB1*03:02  Russia Nizhny Novgorod, Russians 0.03311,510
 589  A*03:01-B*39:01-C*07:02-DRB1*04:03-DQB1*03:02  Germany DKMS - Turkey minority 0.03104,856
 590  A*02:06-B*39:01-C*07:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*04:02  Japan pop 17 0.03003,078
 591  A*02:06-B*39:01-C*07:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*02:01-DPB1*05:01  Japan pop 17 0.03003,078
 592  A*24:02-B*39:04-C*07:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 593  A*31:01-B*39:04-C*07:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 594  A*02:06:01-B*39:01:01-C*07:02:01-DRB1*04:06:01-DQB1*03:02:01  China Zhejiang Han 0.02881,734
 595  A*11:01:01-B*39:01:01-C*07:02:06-DRB1*04:03:01-DQB1*03:02:01  China Zhejiang Han 0.02881,734
 596  A*68:03-B*39:05-C*07:02-DRB1*04:07-DRB4*01:01-DQB1*03:02  USA NMDP North American Amerindian 0.025135,791
 597  A*01-B*39-DRB1*04-DQB1*03:02  Mexico Puebla, Puebla city 0.02511,994
 598  A*11-B*39-DRB1*04-DQB1*03:02  Mexico Puebla, Puebla city 0.02511,994
 599  A*02:01-B*39:08-C*07:02-DRB1*04:07-DQB1*03:02  USA Hispanic pop 2 0.02301,999
 600  A*02:01-B*39:09-C*07:02-DRB1*04:07-DQB1*03:02  USA Hispanic pop 2 0.02301,999

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 501 to 600 (from 666) records   Pages: 1 2 3 4 5 6 7 of 7  


   

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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