Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Population:  Country:  Source of dataset : 
Region:  Ethnic Origin:     Type of study :  Sort by: 
Sample Size:      Sample Year:     Loci Tested: 
Displaying 401 to 500 (from 7,533) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 76  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 401  A*31:01:02-B*35:03:01-C*12:03:01-DRB1*04:08-DQB1*03:04:01  Poland BMR 0.004823,595
 402  A*31:01:02-B*35:03:01-C*12:03:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.001623,595
 403  A*31:01:02-B*35:03:01-C*12:03:01-DRB1*08:03:02-DQB1*02:01:01  India Kerala Malayalam speaking 0.1400356
 404  A*31:01:02-B*35:03:01-C*12:03:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.001723,595
 405  A*31:01:02-B*35:03:01-C*12:03:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.002523,595
 406  A*31:01:02-B*35:03:01-C*12:03:01-DRB1*14:02:01-DQB1*03:01:01  Poland BMR 0.002123,595
 407  A*31:01:02-B*35:03-DRB1*01:03  Portugal North 1.100046
 408  A*31:01:02-B*35:04:01-C*04:01:01-DRB1*08:07-DQB1*04:02:01-DPA1*01:03:01-DPB1*04:02:01  Brazil Rio de Janeiro Caucasian 0.1946521
 409  A*31:01:02-B*35:05-DRB1*04:03-DQB1*03:02  Peru Titikaka Lake Uros 0.4800105
 410  A*31:01:02-B*35:05-DRB1*08:02-DQB1*03:02  Peru Titikaka Lake Uros 0.4900105
 411  A*31:01:02-B*35:08:01-C*04:01:01-DRB1*01:01:01-DQB1*03:02:01  Poland BMR 0.002123,595
 412  A*31:01:02-B*35:08:01-C*04:01:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.004223,595
 413  A*31:01:02-B*35:08:01-C*04:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.000779523,595
 414  A*31:01:02-B*35:08:01-C*04:01:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.001723,595
 415  A*31:01:02-B*35:08:01-C*04:01:01-DRB1*11:03:01-DQB1*03:01:01  Poland BMR 0.001723,595
 416  A*31:01:02-B*35:08:01-C*04:01:01-DRB1*11:04:01-DQB1*03:01:01  Poland BMR 0.006823,595
 417  A*31:01:02-B*35:08:01-C*04:01:01-DRB1*11:04:01-DQB1*06:02:01  Poland BMR 0.002123,595
 418  A*31:01:02-B*35:08:01-C*04:01:01-DRB1*16:01:01-DQB1*05:02:01  China Zhejiang Han 0.02881,734
 419  A*31:01:02-B*35:08-C*04:01:01-DRB1*15:01:01-DQB1*06:02:01-DPB1*02:01:02  Saudi Arabia pop 6 (G) 0.180228,927
 420  A*31:01:02-B*35:10-C*04:01:01-DRB1*04:17:02-DQB1*03:01  Costa Rica Central Valley Mestizo (G) 0.0205221
 421  A*31:01:02-B*35:10-C*04:01:01-DRB1*04:17:02-DQB1*03:02  Costa Rica Central Valley Mestizo (G) 0.0223221
 422  A*31:01:02-B*35:10-C*04:01:01-DRB1*04:17:02-DQB1*03:03  Costa Rica Central Valley Mestizo (G) 0.0169221
 423  A*31:01:02-B*35:10-C*04:01:01-DRB1*04:17:02-DQB1*04:02:01  Costa Rica Central Valley Mestizo (G) 0.0223221
 424  A*31:01:02-B*35:10-C*04:01:01-DRB1*04:17:02-DQB1*05:02  Costa Rica Central Valley Mestizo (G) 0.0267221
 425  A*31:01:02-B*35:10-C*04:01:01-DRB1*04:17:02-DQB1*05:03  Costa Rica Central Valley Mestizo (G) 0.0107221
 426  A*31:01:02-B*35:10-C*04:01:01-DRB1*04:17:02-DQB1*06:01  Costa Rica Central Valley Mestizo (G) 0.0267221
 427  A*31:01:02-B*35:10-C*04:01:01-DRB1*04:17:02-DQB1*06:03  Costa Rica Central Valley Mestizo (G) 0.0240221
 428  A*31:01:02-B*35:10-C*04:01:01-DRB1*04:17:02-DQB1*06:04  Costa Rica Central Valley Mestizo (G) 0.0267221
 429  A*31:01:02-B*35:10-C*04:01:01-DRB1*04:17:02-DQB1*06:09:01  Costa Rica Central Valley Mestizo (G) 0.0151221
 430  A*31:01:02-B*35:12  Mexico Guadalajara Mestizo pop 2 1.5000103
 431  A*31:01:02-B*35:12:01-C*04:01:01-DRB1*04:11:01-DQB1*03:02  Costa Rica Central Valley Mestizo (G) 0.0583221
 432  A*31:01:02-B*35:12:01-C*04:01:01-DRB1*04:11:01-DQB1*04:02:01  Costa Rica Central Valley Mestizo (G) 0.0960221
 433  A*31:01:02-B*35:12:01-C*04:01:01-DRB1*04:11:01-DQB1*06:02  Costa Rica Central Valley Mestizo (G) 0.0720221
 434  A*31:01:02-B*35:17:01-C*01:02:01-DRB1*04:02:01  Costa Rica Guanacaste Mestizo (G) 0.4545110
 435  A*31:01:02-B*35:17:01-C*01:02:01-DRB1*04:07  Nicaragua Mestizo (G) 0.3226155
 436  A*31:01:02-B*35:17:01-C*04:01:01-DRB1*04:07  Nicaragua Mestizo (G) 0.9677155
 437  A*31:01:02-B*35:17:01-C*04:01:01-DRB1*13:01  Nicaragua Mestizo (G) 0.3226155
 438  A*31:01:02-B*35:20:01-C*04:01:01-DRB1*04:04:01  Nicaragua Mestizo (G) 0.3226155
 439  A*31:01:02-B*35:20:01-C*04:01:01-DRB1*04:10:01  Nicaragua Mestizo (G) 0.3226155
 440  A*31:01:02-B*35:20:01-C*04:01:01-DRB1*14:02  Nicaragua Mestizo (G) 0.6452155
 441  A*31:01:02-B*35:20:01-C*04:01:01-DRB1*16:02:01-DQB1*06:04:01-DPA1*02:01:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 442  A*31:01:02-B*35:20-DRB1*04:03-DQB1*03:02  Peru Titikaka Lake Uros 0.4800105
 443  A*31:01:02-B*35:21-DRB1*09:01-DQB1*03:03  Peru Titikaka Lake Uros 0.4800105
 444  A*31:01:02-B*35:43:01-C*01:02:01-DRB1*04:07  Costa Rica Guanacaste Mestizo (G) 0.4545110
 445  A*31:01:02-B*37:01:01-C*02:02:02-DRB1*15:01:01-DQB1*05:02:01  Poland BMR 0.010123,595
 446  A*31:01:02-B*37:01:01-C*06:02:01:01-DRB1*13:05:01-DQB1*03:01  Russia Bashkortostan, Bashkirs 0.4167120
 447  A*31:01:02-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQA1*03:01:01-DQB1*03:02:01-DPA1*01:03:01-DPB1*04:01:01  Russian Federation Vologda Region 0.4202119
 448  A*31:01:02-B*38:01:01-C*07:01:01-DRB1*11:03:01-DQB1*03:01:01  Poland BMR 0.004223,595
 449  A*31:01:02-B*38:01:01-C*12:03:01-DRB1*03:01:01-DQB1*03:01:01  Poland BMR 0.002123,595
 450  A*31:01:02-B*38:01:01-C*12:03:01-DRB1*04:01:01-DQB1*03:02:01  Poland BMR 0.002023,595
 451  A*31:01:02-B*38:01:01-C*12:03:01-DRB1*04:02:01-DQB1*03:02:01  Poland BMR 0.004923,595
 452  A*31:01:02-B*38:01:01-C*12:03:01-DRB1*04:05:01-DQB1*03:02:01  Poland BMR 0.002123,595
 453  A*31:01:02-B*38:01:01-C*12:03:01-DRB1*04:07:01-DQB1*03:01:01  Poland BMR 0.003923,595
 454  A*31:01:02-B*38:01:01-C*12:03:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.004323,595
 455  A*31:01:02-B*38:01:01-C*12:03:01-DRB1*08:04:01-DQB1*04:02:01  Poland BMR 0.002123,595
 456  A*31:01:02-B*38:01:01-C*12:03:01-DRB1*10:01:01-DQB1*03:01:01  Poland BMR 0.002123,595
 457  A*31:01:02-B*38:01:01-C*12:03:01-DRB1*11:01:01-DQB1*02:02:01  Poland BMR 0.002123,595
 458  A*31:01:02-B*38:01:01-C*12:03:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.008723,595
 459  A*31:01:02-B*38:01:01-C*12:03:01-DRB1*11:03:01-DQB1*03:01:01  Poland BMR 0.004223,595
 460  A*31:01:02-B*38:01:01-C*12:03:01-DRB1*13:03:01-DQB1*03:01:01  Poland BMR 0.002123,595
 461  A*31:01:02-B*38:01:01-C*12:03:01-DRB1*15:01:01-DQB1*06:03:01  Poland BMR 0.007123,595
 462  A*31:01:02-B*38:01:01-C*12:03:01-DRB1*16:01:01-DQB1*05:02:01  Poland BMR 0.002323,595
 463  A*31:01:02-B*38:01:01-C*12:03:01-DRB1*16:02:01-DQB1*06:03:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 464  A*31:01:02-B*38:01:06-C*12:03:01-DRB1*11:01:01-DQB1*06:02:01  Poland BMR 0.002123,595
 465  A*31:01:02-B*38:02:01  China Jingpo Minority 0.4950105
 466  A*31:01:02-B*38:02:01-C*07:02:01  China Jingpo Minority 0.4950105
 467  A*31:01:02-B*38:02:01-C*07:02:01-DRB1*09:01:02-DPB1*02:02:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00505,266
 468  A*31:01:02-B*38:02:01-C*07:02:01-DRB1*15:02:01  China Jingpo Minority 0.5210105
 469  A*31:01:02-B*38:02:01-DRB1*12:02:01  China Jingpo Minority 0.5210105
 470  A*31:01:02-B*38:03-C*12:03:01-DRB1*13:01-DQB1*06:03  Costa Rica Central Valley Mestizo (G) 0.2262221
 471  A*31:01:02-B*39:01:01-C*02:02:02-DRB1*04:01:01-DQA1*03:01:01-DQB1*03:02:01-DPA1*01:03:01-DPB1*04:01:01  Russian Federation Vologda Region 0.4202119
 472  A*31:01:02-B*39:01:01-C*03:04:01-DRB1*09:01:02-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00875,266
 473  A*31:01:02-B*39:01:01-C*03:04:01-DRB1*09:01:02-DQB1*03:03:02  China Zhejiang Han 0.02881,734
 474  A*31:01:02-B*39:01:01-C*03:04:01-DRB1*14:54:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00935,266
 475  A*31:01:02-B*39:01:01-C*03:04:01-DRB1*15:01:01-DQB1*06:02:01  China Zhejiang Han 0.02881,734
 476  A*31:01:02-B*39:01:01-C*04:01:01-DRB1*11:01:01-DQB1*03:01:01  India Kerala Malayalam speaking 0.1400356
 477  A*31:01:02-B*39:01:01-C*07:01:01-DRB1*04:07:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 478  A*31:01:02-B*39:01:01-C*07:01:01-DRB1*11:01:01-DQB1*06:02:01  Poland BMR 0.001523,595
 479  A*31:01:02-B*39:01:01-C*07:01:01-DRB1*11:04:01-DQB1*06:02:01  Poland BMR 0.001023,595
 480  A*31:01:02-B*39:01:01-C*07:02:01-DRB1*04:05:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00505,266
 481  A*31:01:02-B*39:01:01-C*07:02:01-DRB1*08:03:02-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.02105,266
 482  A*31:01:02-B*39:01:01-C*07:02:01-DRB1*08:03:02-DQB1*06:01:01  China Zhejiang Han 0.03271,734
 483  A*31:01:02-B*39:01:01-C*07:02:01-DRB1*10:01:01-DQB1*05:01:01  China Zhejiang Han 0.02881,734
 484  A*31:01:02-B*39:01:01-C*07:02:01-DRB1*14:54:01-DQB1*05:03:01  Poland BMR 0.002123,595
 485  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*01:01:01-DQB1*03:01:01  Poland BMR 0.002223,595
 486  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*01:01:01-DQB1*03:02:01  Poland BMR 0.001323,595
 487  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*01:01:01-DQB1*03:03:02  Poland BMR 0.002123,595
 488  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.006823,595
 489  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*01:01:01-DQB1*06:03:01  Poland BMR 0.006523,595
 490  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*01:01:01-DQB1*06:09:01  Poland BMR 0.002123,595
 491  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.013523,595
 492  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*03:01:01-DQB1*03:01:01  Poland BMR 0.004223,595
 493  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*04:01:01-DQB1*03:02:01  Poland BMR 0.001923,595
 494  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*04:02:01-DQB1*03:01:01  Poland BMR 0.002123,595
 495  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*04:03:01-DQB1*03:02:01  Poland BMR 0.001623,595
 496  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*04:04:01-DQA1*03:01:01-DQB1*03:02:01-DPA1*01:03:01-DPB1*04:01:01  Russia Belgorod region 0.3268153
 497  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*04:04:01-DQB1*02:01:01  Poland BMR 0.002123,595
 498  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
 499  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.007223,595
 500  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.018623,595

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 7,533) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 76  


   

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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