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 501 to 600 (from 6,248) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 63  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 501  A*32:01:01-B*40:06:01-C*03:02:02-DRB1*04:10:01-DQB1*06:09:01  India Kerala Malayalam speaking 0.1400356
 502  A*32:01:01-B*40:06:01-C*12:02:02-DRB1*15:01:01-DQB1*06:02:01  India Kerala Malayalam speaking 0.1400356
 503  A*32:01:01-B*40:06:01-C*15:02:01-DRB1*07:01:01-DQB1*02:01:01  India Kerala Malayalam speaking 0.1400356
 504  A*32:01:01-B*40:119-C*02:02:02-DRB1*16:02:01  Costa Rica Guanacaste Mestizo (G) 0.4545110
 505  A*32:01:01-B*40:94-C*02:02:02-DRB1*16:02:01-DQB1*05:02:01  Poland BMR 0.004223,595
 506  A*32:01:01-B*40:94-C*03:04:01-DRB1*16:02:01-DQB1*06:02:01  Poland BMR 0.002123,595
 507  A*32:01:01-B*41:01:01-C*17:01:01-DRB1*03:01:01:01-DQB1*02:01:01  Russia Bashkortostan, Tatars 0.2604192
 508  A*32:01:01-B*41:01:01-C*17:01:01-DRB1*03:01:01-DQB1*02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 509  A*32:01:01-B*41:01:01-C*17:01:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.023223,595
 510  A*32:01:01-B*41:01:01-C*17:01:01-DRB1*04:02:01-DQB1*02:01:01  Poland BMR 0.002123,595
 511  A*32:01:01-B*41:01-C*07:01:01-DRB1*04:05-DQB1*03:02:01-DPB1*01:01:01  Saudi Arabia pop 6 (G) 0.124228,927
 512  A*32:01:01-B*41:02:01-C*02:02:02-DRB1*13:03:01-DQB1*03:01:01  Poland BMR 0.002123,595
 513  A*32:01:01-B*41:02:01-C*02:10-DRB1*01:02:01  Costa Rica Guanacaste Mestizo (G) 0.4545110
 514  A*32:01:01-B*41:02:01-C*03:04:01-DRB1*04:04:01-DPB1*15:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00515,266
 515  A*32:01:01-B*41:02:01-C*17:03:01-DRB1*13:03:01-DQA1*05:05:01-DQB1*06:03:01-DPA1*01:03:01-DPB1*03:01  Russian Federation Vologda Region 0.4202119
 516  A*32:01:01-B*41:02:01-C*17:03-DRB1*13:03:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.09931,510
 517  A*32:01:01-B*41:02:01-C*17:03-DRB1*16:02:01-DQB1*05:02:01  Poland BMR 0.001623,595
 518  A*32:01:01-B*42:01:01-C*04:01:01-DRB1*04:03:01-DQB1*03:02:01-DPA1*01:03:01-DPB1*01:01:01  Brazil Rio de Janeiro Parda 1.1765170
 519  A*32:01:01-B*42:02-C*17:01-DRB1*07:01:01-DQB1*02:02:01  Spain, Canary Islands, Gran canaria island 0.2300215
 520  A*32:01:01-B*42:02-C*17:01-DRB1*13:03:02-DQB1*03:01:01  Spain, Canary Islands, Gran canaria island 0.9300215
 521  A*32:01:01-B*44:02:01:01-C*05:01:01:02-DRB1*01:01:01-DQB1*05:01  Russia Nizhny Novgorod, Russians 0.09931,510
 522  A*32:01:01-B*44:02:01:01-C*05:01:01:02-DRB1*01:01:01-DQB1*05:01  Russia Bashkortostan, Tatars 0.5208192
 523  A*32:01:01-B*44:02:01:01-C*05:01:01:02-DRB1*03:01:01-DQB1*02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 524  A*32:01:01-B*44:02:01:01-C*05:01:01:02-DRB1*04:01:01-DQB1*04:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 525  A*32:01:01-B*44:02:01:01-C*05:01:01:02-DRB1*11:01:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.06621,510
 526  A*32:01:01-B*44:02:01:01-C*05:01:01:02-DRB1*11:04:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 527  A*32:01:01-B*44:02:01:01-C*05:01:01:02-DRB1*12:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.13251,510
 528  A*32:01:01-B*44:02:01:01-C*05:01:01:02-DRB1*12:01-DQB1*03:01  Russia Bashkortostan, Tatars 0.2604192
 529  A*32:01:01-B*44:02:01:01-C*05:01:01-DRB1*03:01:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 530  A*32:01:01-B*44:02:01:01-C*05:01:01-DRB1*13:01:01-DQB1*05:01  Russia Nizhny Novgorod, Russians 0.03311,510
 531  A*32:01:01-B*44:02:01:01-C*16:04:01-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 532  A*32:01:01-B*44:02:01-C*01:02:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.002123,595
 533  A*32:01:01-B*44:02:01-C*02:02:02-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.002123,595
 534  A*32:01:01-B*44:02:01-C*03:03:01-DRB1*13:02:01-DQB1*06:04:01  Poland BMR 0.002123,595
 535  A*32:01:01-B*44:02:01-C*03:04:01-DRB1*12:01:01-DQB1*03:01:01  Poland BMR 0.002123,595
 536  A*32:01:01-B*44:02:01-C*05:01:01  England Blood Donors of Mixed Ethnicity 0.5128519
 537  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.001723,595
 538  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*01:02:01-DQB1*03:01:01  Poland BMR 0.002123,595
 539  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*01:03-DQB1*03:01:01  Poland BMR 0.000576023,595
 540  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*01:03-DQB1*06:02:01  Poland BMR 0.002123,595
 541  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.005623,595
 542  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*04:01:01-DQB1*03:02:01  Poland BMR 0.007723,595
 543  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*04:03:01-DQB1*03:05:01  Poland BMR 0.002023,595
 544  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*04:07:01-DQB1*03:01:01  Poland BMR 0.002123,595
 545  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.006323,595
 546  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*07:01:01-DQB1*03:03:02-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 547  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*07:01:01-DQB1*03:03:02-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 548  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*07:01:01-DQB1*03:03:02-DPA1*01:03:01-DPB1*14:01:01  Brazil Rio de Janeiro Parda 0.5882170
 549  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.008023,595
 550  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.013723,595
 551  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*11:03:01-DQB1*03:01:01  Poland BMR 0.008723,595
 552  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*11:04:01-DQB1*02:01:01  Poland BMR 0.002123,595
 553  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*11:04:01-DQB1*03:01:01  Poland BMR 0.016823,595
 554  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*12:01:01-DQB1*03:01:01  Poland BMR 0.031623,595
 555  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*12:02:01-DPB1*13:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00875,266
 556  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*13:01:01-DQA1*01:03:01-DQB1*06:03-DPA1*01:03:01-DPB1*04:01:01  Russia Belgorod region 0.3268153
 557  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.029723,595
 558  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*13:02:01-DQB1*06:04:01  Poland BMR 0.008523,595
 559  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*13:02:01-DQB1*06:09:01  Poland BMR 0.000849023,595
 560  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.025523,595
 561  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*16:01:01-DQB1*03:01:01  Poland BMR 0.002123,595
 562  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*16:01:01-DQB1*05:02:01  Poland BMR 0.001723,595
 563  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*16:02:01-DQB1*05:02:01  Spain, Canary Islands, Gran canaria island 0.2300215
 564  A*32:01:01-B*44:02:01-C*05:32-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.002123,595
 565  A*32:01:01-B*44:02:01-C*07:04:01-DRB1*04:01:01-DQB1*03:01:01  Poland BMR 0.002123,595
 566  A*32:01:01-B*44:02:01-C*07:04:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.001823,595
 567  A*32:01:01-B*44:02:01-C*16:04:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.002123,595
 568  A*32:01:01-B*44:02:01-C*16:04:01-DRB1*11:04:01-DQB1*03:01:01  Poland BMR 0.008223,595
 569  A*32:01:01-B*44:03:01-C*04:01:01  England Blood Donors of Mixed Ethnicity 0.0963519
 570  A*32:01:01-B*44:03:01-C*04:01:01-DRB1*01:01:01-DQB1*02:02:01  Poland BMR 0.002123,595
 571  A*32:01:01-B*44:03:01-C*04:01:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.002123,595
 572  A*32:01:01-B*44:03:01-C*04:01:01-DRB1*07:01:01-DPB1*21:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.03805,266
 573  A*32:01:01-B*44:03:01-C*04:01:01-DRB1*07:01:01-DQB1*02:02:01  China Zhejiang Han 0.08651,734
 574  A*32:01:01-B*44:03:01-C*04:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.014023,595
 575  A*32:01:01-B*44:03:01-C*04:01:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.004023,595
 576  A*32:01:01-B*44:03:01-C*04:01:01-DRB1*11:01:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 577  A*32:01:01-B*44:03:01-C*04:01:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.004823,595
 578  A*32:01:01-B*44:03:01-C*04:01:01-DRB1*11:01:01-DQB1*06:02:01  Poland BMR 0.002123,595
 579  A*32:01:01-B*44:03:01-C*04:01:01-DRB1*11:04:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 580  A*32:01:01-B*44:03:01-C*04:01:01-DRB1*12:01:01-DQB1*03:01:01  Poland BMR 0.002123,595
 581  A*32:01:01-B*44:03:01-C*04:01:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.008023,595
 582  A*32:01:01-B*44:03:01-C*04:01:01-DRB1*14:54:01-DQB1*05:03:01  Poland BMR 0.004223,595
 583  A*32:01:01-B*44:03:01-C*04:01:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.002923,595
 584  A*32:01:01-B*44:03:01-C*04:01:01-DRB1*15:02:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00925,266
 585  A*32:01:01-B*44:03:01-C*08:02:01  South African Indian population 1.000050
 586  A*32:01:01-B*44:03:01-C*16:01:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.002123,595
 587  A*32:01:01-B*44:03:01-C*16:01:01-DRB1*01:02:01-DQB1*05:01:01  Poland BMR 0.002123,595
 588  A*32:01:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.004223,595
 589  A*32:01:01-B*44:03:01-C*16:01:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.002123,595
 590  A*32:01:01-B*44:05:01-C*02:02:02-DRB1*12:01:01-DQB1*03:01:01  Poland BMR 0.005923,595
 591  A*32:01:01-B*44:05:01-C*02:02:02-DRB1*15:01:01-DQB1*05:02:01  Poland BMR 0.002123,595
 592  A*32:01:01-B*44:05:01-C*02:02:02-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.002023,595
 593  A*32:01:01-B*44:05:01-C*16:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.002123,595
 594  A*32:01:01-B*44:05-C*02:02:02-DRB1*03:01:01-DQB1*02:01:01  Spain, Canary Islands, Gran canaria island 0.2300215
 595  A*32:01:01-B*44:27:01-C*07:04:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.002223,595
 596  A*32:01:01-B*44:27:01-C*07:04:01-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 597  A*32:01:01-B*44:27:01-C*07:04:01-DRB1*16:01:01-DQB1*05:02:01  Poland BMR 0.004723,595
 598  A*32:01:01-B*45:01:01-C*07:01:02-DRB1*07:01:01-DQB1*02:02:01-DPA1*03:01:01-DPB1*105:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 599  A*32:01:01-B*45:01:01-C*12:03:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.006423,595
 600  A*32:01:01-B*45:01:01-C*16:01:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.002123,595

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 501 to 600 (from 6,248) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 63  


   

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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