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 701 to 800 (from 6,248) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 63  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 701  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*01:01:01-DPB1*02:01:02  Hong Kong Chinese HKBMDR HLA 11 loci 0.01905,266
 702  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*01:01:01-DQB1*03:02:01  Poland BMR 0.002123,595
 703  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*01:01:01-DQB1*05:01:01  China Zhejiang Han 0.03071,734
 704  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.001923,595
 705  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.001923,595
 706  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*03:01:01-DQB1*06:01:01  Poland BMR 0.002123,595
 707  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*04:01:01-DQB1*03:02:01  Poland BMR 0.002023,595
 708  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*04:03:01-DQB1*03:02:01  Poland BMR 0.001923,595
 709  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.001923,595
 710  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*07:01:01-DQB1*03:03:02  China Zhejiang Han 0.02881,734
 711  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.002123,595
 712  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*09:01:02-DQB1*03:03:02  China Zhejiang Han 0.02881,734
 713  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.004223,595
 714  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*11:04:01-DQB1*03:01  Costa Rica Central Valley Mestizo (G) 0.4525221
 715  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*15:01:01-DQB1*06:02:01  China Zhejiang Han 0.08651,734
 716  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*15:02:01  Nicaragua Mestizo (G) 0.6452155
 717  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*15:02:01-DPB1*04:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.06635,266
 718  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*15:02:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.02865,266
 719  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*15:02:01-DPB1*135:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00875,266
 720  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*15:02:01-DPB1*21:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00765,266
 721  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*15:02:01-DQB1*06:01:01  China Zhejiang Han 0.22881,734
 722  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*15:02:01-DQB1*06:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 723  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*15:02:01-DQB1*06:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.3891521
 724  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*15:02:02-DQA1*01:03:01-DQB1*06:01:01-DPA1*01:03:01-DPB1*04:01:01  Russian Federation Vologda Region 0.4202119
 725  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*16:02:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00925,266
 726  A*32:01:01-B*53:01:01-C*04:01:01-DRB1*07:01  Costa Rica Guanacaste Mestizo (G) 0.9091110
 727  A*32:01:01-B*53:01:01-C*04:01:01-DRB1*07:01-DQB1*02:01  Costa Rica Central Valley Mestizo (G) 0.1022221
 728  A*32:01:01-B*53:01:01-C*04:01:01-DRB1*07:01-DQB1*03:01  Costa Rica Central Valley Mestizo (G) 0.0803221
 729  A*32:01:01-B*53:01:01-C*04:01:01-DRB1*07:01-DQB1*03:03  Costa Rica Central Valley Mestizo (G) 0.0438221
 730  A*32:01:01-B*53:01:01-C*04:01:01-DRB1*10:01:01  Costa Rica African -Caribbean (G) 0.4902102
 731  A*32:01:01-B*53:01:01-C*04:01:01-DRB1*13:02:01-DQB1*06:04:01  Poland BMR 0.004223,595
 732  A*32:01:01-B*53:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01-DPB1*17:01:01  Saudi Arabia pop 6 (G) 0.166228,927
 733  A*32:01:01-B*53:01:01-C*06:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.002123,595
 734  A*32:01:01-B*53:01:01-C*07:02:01-DRB1*08:04:01-DQB1*04:02:01  Poland BMR 0.002123,595
 735  A*32:01:01-B*55:01:01-C*01:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.002123,595
 736  A*32:01:01-B*55:01:01-C*03:03:01  England Blood Donors of Mixed Ethnicity 0.2854519
 737  A*32:01:01-B*55:01:01-C*03:03:01-DRB1*04:01:01-DQB1*03:02:01  Poland BMR 0.011923,595
 738  A*32:01:01-B*55:01:01-C*03:03:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.007923,595
 739  A*32:01:01-B*55:01:01-C*03:03:01-DRB1*15:01:01-DQB1*05:02:01  Poland BMR 0.000545123,595
 740  A*32:01:01-B*55:01:01-C*03:03:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.003823,595
 741  A*32:01:01-B*55:01:01-C*03:04:01-DRB1*11:01:01-DQB1*05:02:01  Poland BMR 0.002123,595
 742  A*32:01:01-B*55:01:01-C*03:04:01-DRB1*11:04:01-DQB1*03:01:01  Poland BMR 0.002123,595
 743  A*32:01:01-B*55:01:01-C*07:01:01-DRB1*01:01:01-DQB1*03:02:01  Poland BMR 0.002123,595
 744  A*32:01:01-B*55:01:01-C*12:03:01-DRB1*13:01:01-DQB1*03:01:01  India Kerala Malayalam speaking 0.1400356
 745  A*32:01:01-B*56:01:01:02-C*01:02:01-DRB1*11:28:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 746  A*32:01:01-B*56:01:01-C*01:02:01  England Blood Donors of Mixed Ethnicity 0.0963519
 747  A*32:01:01-B*56:01:01-C*01:02:01-DRB1*04:01:01-DQB1*03:01:01  Poland BMR 0.002123,595
 748  A*32:01:01-B*56:01:01-C*01:02:01-DRB1*04:07:01-DQB1*03:01:01  Poland BMR 0.001323,595
 749  A*32:01:01-B*56:01:01-C*01:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.010023,595
 750  A*32:01:01-B*56:01:01-C*01:02:01-DRB1*07:01:01-DQB1*02:02:01  Spain, Canary Islands, Gran canaria island 0.2300215
 751  A*32:01:01-B*56:01:01-C*01:02:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.002123,595
 752  A*32:01:01-B*56:01:01-C*01:02:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.005823,595
 753  A*32:01:01-B*56:01:01-C*01:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.010523,595
 754  A*32:01:01-B*56:01:01-C*01:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.002123,595
 755  A*32:01:01-B*56:01:01-C*01:02:01-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 756  A*32:01:01-B*56:01:01-C*12:03:01-DRB1*11:01:01-DQB1*02:02:01  Poland BMR 0.002123,595
 757  A*32:01:01-B*57:01:01-C*01:02:01-DRB1*01:01:01-DQB1*03:03:02  Poland BMR 0.002123,595
 758  A*32:01:01-B*57:01:01-C*02:02:02-DRB1*01:01:01-DQB1*06:03:01  Poland BMR 0.002123,595
 759  A*32:01:01-B*57:01:01-C*04:01:01-DRB1*07:01:01-DQB1*03:03:02-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Black 1.470668
 760  A*32:01:01-B*57:01:01-C*06:02:01  England Blood Donors of Mixed Ethnicity 0.1649519
 761  A*32:01:01-B*57:01:01-C*06:02:01-DRB1*01:01:01-DQB1*02:01:01  Poland BMR 0.002123,595
 762  A*32:01:01-B*57:01:01-C*06:02:01-DRB1*01:01:01-DQB1*02:02:01  Poland BMR 0.002123,595
 763  A*32:01:01-B*57:01:01-C*06:02:01-DRB1*01:01:01-DQB1*03:01:01  Poland BMR 0.002123,595
 764  A*32:01:01-B*57:01:01-C*06:02:01-DRB1*01:02:01-DQB1*06:02:01  Poland BMR 0.002123,595
 765  A*32:01:01-B*57:01:01-C*06:02:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.007223,595
 766  A*32:01:01-B*57:01:01-C*06:02:01-DRB1*04:01:01-DQB1*03:02:01  Poland BMR 0.004123,595
 767  A*32:01:01-B*57:01:01-C*06:02:01-DRB1*04:02:01-DQB1*03:02:01  Poland BMR 0.002123,595
 768  A*32:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.019923,595
 769  A*32:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  India Kerala Malayalam speaking 0.1450356
 770  A*32:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.073723,595
 771  A*32:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Russia Nizhny Novgorod, Russians 0.03311,510
 772  A*32:01:01-B*57:01:01-C*06:02:01-DRB1*09:01:02-DQB1*03:03:02  Poland BMR 0.006323,595
 773  A*32:01:01-B*57:01:01-C*06:02:01-DRB1*11:04:01-DQB1*03:01:01  Poland BMR 0.005523,595
 774  A*32:01:01-B*57:01:01-C*14:02:01  South African Indian population 1.000050
 775  A*32:01:01-B*57:03:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.002123,595
 776  A*32:01:01-B*58:01:01  China Jingpo Minority 0.4950105
 777  A*32:01:01-B*58:01:01-C*03:02:01  China Jingpo Minority 0.4950105
 778  A*32:01:01-B*58:01:01-C*03:02:02-DRB1*01:01:01-DQB1*06:02:01  Poland BMR 0.002123,595
 779  A*32:01:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DPB1*04:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.01905,266
 780  A*32:01:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00705,266
 781  A*32:01:01-B*58:01:01-C*03:02:02-DRB1*04:01:01-DQB1*03:02:01  Poland BMR 0.001623,595
 782  A*32:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DPB1*04:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00935,266
 783  A*32:01:01-B*58:01:01-C*07:18  England Blood Donors of Mixed Ethnicity 0.0963519
 784  A*32:01:01-B*58:01:01-DRB1*03:01:01  China Jingpo Minority 0.5210105
 785  A*32:01:01-B*58:02:01-C*03:03:01-DRB1*11:02:01-DQB1*02:02:01-DPA1*02:01:01-DPB1*10:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 786  A*32:01:01-C*03:02:01  China Jingpo Minority 0.4850105
 787  A*32:01:01-C*12:03:01-DRB1*11:06:01  China Jingpo Minority 0.5150105
 788  A*32:01:02-B*51:01:01-C*15:02:01-DRB1*04:05:01-DQB1*03:02:01-DPA1*01:03:01-DPB1*13:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 789  A*32:01:18-B*50:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.002123,595
 790  A*32:01-B*07:02  Cuba Caucasian 1.400070
 791  A*32:01-B*07:02  USA Asian pop 2 0.12801,772
 792  A*32:01-B*07:02  USA Hispanic pop 2 0.17001,999
 793  A*32:01-B*07:02  USA African American pop 4 0.25702,411
 794  A*32:01-B*07:02:01-DRB1*12:01:01  Cape Verde Northwestern Islands 1.600062
 795  A*32:01-B*07:02-C*02:02-DRB1*04:04  Poland DKMS 0.004820,653
 796  A*32:01-B*07:02-C*03:04-DRB1*07:01  Germany DKMS - China minority 0.03901,282
 797  A*32:01-B*07:02-C*05:01-DRB1*12:01  Poland DKMS 0.002420,653
 798  A*32:01-B*07:02-C*07:01-DRB1*04:01-DQA1*03:03-DQB1*03:02-DPB1*01:01  South Africa Worcester 0.6000159
 799  A*32:01-B*07:02-C*07:01-DRB1*11:01-DQB1*03:01  USA African American pop 4 0.01102,411
 800  A*32:01-B*07:02-C*07:01-DRB1*13:01-DQB1*06:03  USA African American pop 4 0.01102,411

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 701 to 800 (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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