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 3,183) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 32  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 401  A*02:01-B*35:12-C*04:01-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPB1*04:02  Nicaragua Managua 0.6494339
 402  A*02:01-B*15:15-C*01:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.6410234
 403  A*02:01-B*15:30-C*01:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.6410234
 404  A*02:01-B*48:01-C*08:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.6410234
 405  A*02:06-B*48:01-C*08:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.6410234
 406  A*68:01-B*15:15-C*01:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.6410234
 407  B*15:01-C*01:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.6400234
 408  B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.6400234
 409  A*02:05-B*27:03-C*02:02-DRB1*08:04-DQB1*04:02-DPB1*01:01  Tanzania Maasai 0.6390336
 410  A*24:02-B*35:01-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uros 0.6300105
 411  A*01:01:01-B*35:02:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.6250405
 412  A*02:01-B*35:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 0.6061330
 413  A*24:02-B*35:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 0.6061330
 414  A*29:02-B*58:01-C*06:02-DRB1*04:04-DQA1*03:01-DQB1*04:02-DPB1*40:01  South Africa Worcester 0.6000159
 415  A*34:02-B*08:01-C*07:01-DRB1*03:02-DQA1*04:01-DQB1*04:02-DPB1*01:01  South Africa Worcester 0.6000159
 416  DRB1*04:11-DQB1*04:02  USA Hispanic pop 2 0.60001,999
 417  A*01:01-B*15:01-DRB1*08:02-DQB1*04:02  Mexico Veracruz Xalapa 0.595284
 418  A*02:01-B*35:01-DRB1*04:11-DQB1*04:02  Mexico Veracruz Xalapa 0.595284
 419  A*02:01-B*35:01-DRB1*08:01-DQB1*04:02  Mexico Veracruz Xalapa 0.595284
 420  A*02:01-B*40:02-DRB1*08:02-DQB1*04:02  Mexico Veracruz Xalapa 0.595284
 421  A*02:01-B*51:01-DRB1*08:02-DQB1*04:02  Mexico Veracruz Xalapa 0.595284
 422  A*03:01-B*48:01-DRB1*04:11-DQB1*04:02  Mexico Veracruz Xalapa 0.595284
 423  A*03:01-B*51:01-DRB1*08:01-DQB1*04:02  Mexico Veracruz Xalapa 0.595284
 424  A*03:01-B*51:01-DRB1*08:02-DQB1*04:02  Mexico Veracruz Xalapa 0.595284
 425  A*11:01-B*15:01-DRB1*08:02-DQB1*04:02  Mexico Veracruz Xalapa 0.595284
 426  A*23:01-B*35:02-DRB1*04:04-DQB1*04:02  Mexico Veracruz Xalapa 0.595284
 427  A*24:02-B*39:01-DRB1*04:07-DQB1*04:02  Mexico Veracruz Xalapa 0.595284
 428  A*30:01-B*08:01-DRB1*03:02-DQB1*04:02  Mexico Veracruz Xalapa 0.595284
 429  A*31:01-B*52:01-DRB1*08:02-DQB1*04:02  Mexico Veracruz Xalapa 0.595284
 430  A*32:01-B*40:02-DRB1*10:01-DQB1*04:02  Mexico Veracruz Xalapa 0.595284
 431  A*68:01-B*39:01-DRB1*08:02-DQB1*04:02  Mexico Veracruz Xalapa 0.595284
 432  A*68:01-B*48:01-DRB1*08:02-DQB1*04:02  Mexico Veracruz Xalapa 0.595284
 433  DRB1*04:06-DQA1*04:01-DQB1*04:02  Spain Las Alpujarras 0.590085
 434  A*24:02-B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  USA NMDP Alaska Native or Aleut 0.58981,376
 435  A*01:01:01-B*41:02:01-C*17:03:01-DRB1*01:01:01-DQB1*04:02:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Parda 0.5882170
 436  A*02:01:01-B*15:01:01-C*04:01:01-DRB1*15:03:01-DQB1*04:02:01-DPA1*03:01:01-DPB1*03:01:01  Brazil Rio de Janeiro Parda 0.5882170
 437  A*02:01:01-B*35:01:01-C*17:01:01-DRB1*03:02:01-DQB1*04:02:01-DPA1*02:02:02-DPB1*04:01:01  Brazil Rio de Janeiro Parda 0.5882170
 438  A*02:01:01-B*42:01:01-C*16:01:01-DRB1*07:01:01-DQB1*04:02:01-DPA1*02:02:02-DPB1*01:01:01  Brazil Rio de Janeiro Parda 0.5882170
 439  A*02:04-B*58:01:01-C*03:02:02-DRB1*04:11:01-DQB1*04:02:01-DPA1*02:01:01-DPB1*14:01:01  Brazil Rio de Janeiro Parda 0.5882170
 440  A*02:06:01-B*39:01:03-C*07:02:01-DRB1*11:04:01-DQB1*04:02:01-DPA1*01:03:01-DPB1*104:01:01  Brazil Rio de Janeiro Parda 0.5882170
 441  A*03:01:01-B*07:02:01-C*07:02:01-DRB1*08:01:01-DQB1*04:02:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Parda 0.5882170
 442  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
 443  A*30:02:01-B*35:01:01-C*17:01:01-DRB1*04:03:01-DQB1*04:02:01-DPA1*02:02:02-DPB1*04:01:01  Brazil Rio de Janeiro Parda 0.5882170
 444  A*30:02:01-B*53:01:01-C*04:01:01-DRB1*03:02:01-DQB1*04:02:01-DPA1*02:02:02-DPB1*02:01:02  Brazil Rio de Janeiro Parda 0.5882170
 445  A*33:01:01-B*15:03:01-C*03:03:01-DRB1*03:02:01-DQB1*04:02:01-DPA1*02:02:02-DPB1*01:01:01  Brazil Rio de Janeiro Parda 0.5882170
 446  A*69-B*40-DRB1*08:02-DQB1*04:02  Bolivia La Paz Aymaras 0.575087
 447  A*01:01-B*08:01-DRB1*08:01-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 448  A*02:01-B*14:02-DRB1*08:04-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 449  A*02:01-B*35:02-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 450  A*02:01-B*40:02-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 451  A*02:01-B*52:01-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 452  A*24:02-B*35:01-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 453  A*24:02-B*35:02-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 454  A*24:02-B*51:01-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 455  A*24:02-B*52:01-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 456  A*26:01-B*35:01-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 457  A*26:01-B*40:02-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 458  A*31:01-B*40:01-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 459  A*36-B*39:01-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 460  A*68:01-B*15:01-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 461  A*30:01-B*42:01-C*17:01-DRB1*03:02-DQB1*04:02  USA NMDP Caribean Indian 0.568014,339
 462  A*02:01-B*27:05-C*02:02-DRB1*08:01-DQB1*04:02-DPB1*03:01  Russia Karelia 0.55871,075
 463  A*30:01-B*42:01-C*17:01-DRB1*03:02-DRB3*01:01-DQB1*04:02  USA NMDP Caribean Hispanic 0.5406115,374
 464  A*02:01-B*18:01-C*07:01-DRB1*08:01-DQB1*04:02  USA NMDP Caribean Indian 0.530214,339
 465  DRB1*08:02-DQB1*04:02  USA Asian pop 2 0.52901,772
 466  A*02:01-B*51:01-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uros 0.5000105
 467  A*03:01-B*15:03-C*02:10-DRB1*03:01-DQA1*04:01-DQB1*04:02-DPB1*04:02  Kenya, Nyanza Province, Luo tribe 0.5000100
 468  A*23:01-B*42:01-C*17:01-DRB1*03:02-DQA1*04:01-DQB1*04:02-DPB1*01:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 469  A*30:01-B*58:02-C*06:02-DRB1*07:01-DQA1*04:01-DQB1*04:02-DPB1*01:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 470  A*30:02-B*42:01-C*17:01-DRB1*03:02-DQA1*01:02-DQB1*04:02-DPB1*01:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 471  A*32:01-B*58:01-C*04:01-DRB1*03:02-DQA1*04:01-DQB1*04:02-DPB1*01:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 472  A*34:02-B*42:01-C*17:01-DRB1*03:02-DQA1*04:01-DQB1*04:02-DPB1*04:02  Kenya, Nyanza Province, Luo tribe 0.5000100
 473  A*68:01-B*42:01-C*16:01-DRB1*03:02-DQA1*02:01-DQB1*04:02-DPB1*01:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 474  A*34:01:01-B*56:01:01-C*04:03:01-DRB1*04:05:01-DQB1*04:02:01  Vietnam Kinh 0.4950101
 475  A*34:01:01-B*56:01:01-C*07:02:01-DRB1*04:05:01-DQB1*04:02:01  Vietnam Kinh 0.4950101
 476  A*02:01-B*35:05-DRB1*04:03-DQB1*04:02  Peru Titikaka Lake Uros 0.4900105
 477  DRB1*04:05-DQB1*04:02  USA Asian pop 2 0.48501,772
 478  A*02:01-B*07:02-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uros 0.4800105
 479  A*02:01-B*35:04-DRB1*04:02-DQB1*04:02  Peru Titikaka Lake Uros 0.4800105
 480  A*02:01-B*35:06-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uros 0.4800105
 481  A*24:02-B*35:05-DRB1*04:07-DQB1*04:02  Peru Titikaka Lake Uros 0.4800105
 482  A*31:01:02-B*15:01-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uros 0.4800105
 483  A*31:01:02-B*78:02-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uros 0.4800105
 484  A*68:01:02-B*40:02-DRB1*08:01-DQB1*04:02  Peru Titikaka Lake Uros 0.4800105
 485  A*68:01:02-B*40:03-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uros 0.4800105
 486  A*02:01-B*15:01-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*03:01  Russia Karelia 0.47831,075
 487  A*02:01-B*35:12-C*04:01-DRB1*08:02-DRBX*NNNN-DQB1*04:02  USA NMDP Hispanic South or Central American 0.4762146,714
 488  A*24:02:01-B*15:01:01-C*03:03:01-DRB1*08:01:01-DQB1*04:02:01  Spain, Canary Islands, Gran canaria island 0.4700215
 489  A*02:01-B*35:17-C*04:01-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.46301,999
 490  DRB1*03:02-DQB1*04:02-DPB1*17:01  Gambia pop 3 0.4589939
 491  A*02:01-B*35:12-C*04:01-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.4587218
 492  A*24:02-B*39:05-C*07:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.4587218
 493  A*68:03-B*39:05-C*07:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.4587218
 494  A*02:01-B*40:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 0.4545330
 495  A*24:02-B*39:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 0.4545330
 496  A*02-B*07-DRB1*08:01-DQA1*04:01-DQB1*04:02  Brazil Paraná Caucasian 0.4537641
 497  A*68:01:02-B*39:08-C*07:02:01-DRB1*08:02:01-DQB1*04:02:01  Costa Rica Central Valley Mestizo (G) 0.4525221
 498  A*02:01-B*35:03-C*04:01-E*01:01:01-F*01:03:01-G*01:01-DRB1*03:04-DQA1*05:01-DQB1*04:02  Portugal Azores Terceira Island 0.4386130
 499  A*02:01-B*51:01-C*14:02-E*01:03:01-F*01:01:01-G*01:01-DRB1*08:01-DQA1*04:01-DQB1*04:02  Portugal Azores Terceira Island 0.4386130
 500  A*02:05-B*35:27-C*12:03-E*01:01:01-F*01:01:02-G*01:03-DRB1*08:01-DQA1*01:01-DQB1*04:02  Portugal Azores Terceira Island 0.4386130

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 3,183) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 32  


   

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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