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 701 to 800 (from 13,576) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 136  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 701  A*30:02-B*51:01-DRB1*03:01  Israel Druze 0.92205,914
 702  A*02-B*51-DRB1*13  Brazil Para Cord Blood Unit 0.9206841
 703  A*02:01-B*51:01  USA Asian pop 2 0.91301,772
 704  A*02-B*51-DRB1*14-DQB1*03:01  Ecuador Andes Mixed Ancestry 0.9102824
 705  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*11:01  Costa Rica Guanacaste Mestizo (G) 0.9091110
 706  A*68:05-B*51:01:01-C*08:01:01-DRB1*04:07  Costa Rica Guanacaste Mestizo (G) 0.9091110
 707  A*02-B*51-C*01-DRB1*12  Myanmar Chin 0.909055
 708  A*11-B*51-C*15-DRB1*04  Myanmar Kayah 0.909055
 709  A*11-B*51-C*15-DRB1*07  Myanmar Chin 0.909055
 710  A*24-B*51-C*14-DRB1*15  Myanmar Chin 0.909055
 711  A*31-B*51-C*15-DRB1*04  Myanmar Chin 0.909055
 712  A*02-B*51-C*15-DRB1*03  Iran pop 4 0.9000855
 713  A*23-B*51-C*15-DRB1*14  Iran pop 4 0.9000855
 714  A*68-B*51-C*14-DRB1*11  Iran pop 4 0.9000855
 715  A*02:01-B*51:02-DRB1*08:01-DQB1*03:01  Iran Yazd 0.892956
 716  A*02:01-B*51:08-DRB1*03:01-DQB1*06:02  Iran Yazd 0.892956
 717  A*02-B*51-DRB1*04-DQB1*03:02  Mexico Jalisco, Zapopan 0.8929168
 718  A*02-B*51-DRB1*07-DQB1*02  Mexico Veracruz, Cordoba 0.892956
 719  A*02-B*51-DRB1*08-DQB1*04  Mexico Veracruz, Cordoba 0.892956
 720  A*02-B*51-DRB1*08-DQB1*04  Mexico Jalisco, Zapopan 0.8929168
 721  A*02-B*51-DRB1*11-DQB1*03:01  Mexico Jalisco, Zapopan 0.8929168
 722  A*03:01-B*51:01-DRB1*08:01-DQB1*04:01  Iran Yazd 0.892956
 723  A*03:01-B*51:01-DRB1*10:01-DQB1*05:01  Iran Yazd 0.892956
 724  A*03:01-B*51:01-DRB1*15:01-DQB1*03:03  Iran Yazd 0.892956
 725  A*23:01-B*51:06-DRB1*11:01-DQB1*02:01  Iran Yazd 0.892956
 726  A*24:02-B*51:01-DRB1*08:01-DQB1*04:01  Iran Yazd 0.892956
 727  A*24-B*51-DRB1*16-DQB1*03:01  Mexico Veracruz, Coatzacoalcos 0.892955
 728  A*26:08-B*51:01-DRB1*11:01-DQB1*03:01  Iran Yazd 0.892956
 729  A*29:01-B*51:06-DRB1*11:01-DQB1*02:01  Iran Yazd 0.892956
 730  A*31:01-B*51:06-DRB1*04:01-DQB1*06:01  Iran Yazd 0.892956
 731  A*68:01-B*51:01-DRB1*04:01-DQB1*03:02  Iran Yazd 0.892956
 732  A*68:01-B*51:06-DRB1*13:01-DQB1*06:02  Iran Yazd 0.892956
 733  A*68-B*51-DRB1*10-DQA1*01:01-DQB1*05:01  Russia, South Ural, Chelyabinsk region, Nagaybaks 0.8900112
 734  A*32:01-B*51:01-DRB1*11:04  Israel Druze 0.88705,914
 735  B*51:01-C*15:02  USA Asian pop 2 0.88701,772
 736  A*02-B*51-DRB1*08-DQB1*04  Mexico Nuevo Leon, Monterrey city 0.8850226
 737  A*01:01-B*51:01-C*14:02-E*01:01:01-F*01:01:01-G*01:01-DRB1*07:01-DQA1*02:01-DQB1*02:02  Portugal Azores Terceira Island 0.8772130
 738  A*02:01-B*51:01-C*06:02-E*01:01:01-F*01:01:01-G*01:01-DRB1*13:01-DQA1*02:01-DQB1*06:03  Portugal Azores Terceira Island 0.8772130
 739  A*02-B*51-DRB1*13  Macedonia 0.8741286
 740  A*02-B*51-DRB1*14  Macedonia 0.8741286
 741  A*03-B*51  Macedonia 0.8741286
 742  A*11-B*51-C*15  Macedonia 0.8741286
 743  A*24-B*51-C*01  Macedonia 0.8741286
 744  A*31-B*51-C*15  Macedonia 0.8741286
 745  A*68-B*51  Macedonia 0.8741286
 746  A*24-B*51-DRB1*14-DQB1*03:01  Mexico Veracruz, Veracruz city 0.8721171
 747  A*24-B*51-DRB1*16-DQB1*03:01  Mexico Veracruz, Veracruz city 0.8721171
 748  A*31-B*51-DRB1*04-DQB1*03:02  Mexico Veracruz, Veracruz city 0.8721171
 749  A*02:02-B*51:06-DRB1*04:02  Israel YemenJews 0.871015,542
 750  A*02:11:01-B*51:01:01-C*14:02:01-DRB1*14:04:01-DQB1*05:03:01  India Karnataka Kannada Speaking 0.8620174
 751  A*24:02:01-B*51:01:01-C*14:02:01-DRB1*13:01:01-DQB1*06:03:01  India Karnataka Kannada Speaking 0.8620174
 752  A*02-B*51-DRB1*13-DQA1*01:03-DQB1*06:03  Russia, South Ural, Chelyabinsk region, Nagaybaks 0.8600112
 753  B*51:01-C*15:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.8600234
 754  A*02-B*51-DRB1*04-DQB1*03:02  Mexico Michoacan Rural 0.8596348
 755  A*24-B*51-DRB1*08:02-DQB1*04:02  Bolivia La Paz Aymaras 0.858087
 756  A*02-B*51-C*14  Brazil Parana Japanese 0.8500192
 757  A*24:02-B*51:01-C*15:02  Italy pop 5 0.8500975
 758  A*02-B*51-DRB1*08-DQB1*04  Mexico Chihuahua Chihuahua City 0.8403119
 759  A*11-B*51-DRB1*11-DQB1*03:01  Mexico Chihuahua Chihuahua City 0.8403119
 760  A*11-B*51-DRB1*15-DQB1*06  Mexico Chihuahua Chihuahua City 0.8403119
 761  A*31-B*51-DRB1*04-DQB1*03:01  Mexico Chihuahua Chihuahua City 0.8403119
 762  A*31-B*51-DRB1*04-DQB1*03:02  Mexico Chihuahua Chihuahua City 0.8403119
 763  A*31-B*51-DRB1*04-DQB1*04  Mexico Chihuahua Chihuahua City 0.8403119
 764  A*02-B*51-DRB1*04  Albania pop 2 0.8400432
 765  A*03-B*51-C*01-DRB1*11  Macedonia MBMDR - Albanian 0.8363128
 766  A*02:01:01-B*51:01:01-C*01:02:01-DRB1*07:01-DQB1*02:02  Russia Bashkortostan, Bashkirs 0.8333120
 767  A*02:01-B*51:01-DRB1*04:01-DQB1*03:02  Iran Saqqez-Baneh Kurds 0.833360
 768  A*02:01-B*51:01-DRB1*10:01-DQB1*06:03  Iran Saqqez-Baneh Kurds 0.833360
 769  A*02:48-B*51:06-DRB1*04:01-DQB1*03:05  Iran Saqqez-Baneh Kurds 0.833360
 770  A*02:50-B*51:01-DRB1*03:01-DQB1*05:01  Iran Saqqez-Baneh Kurds 0.833360
 771  A*02:50-B*51:01-DRB1*13:01-DQB1*06:02  Iran Saqqez-Baneh Kurds 0.833360
 772  A*02:52-B*51:01-DRB1*14:01-DQB1*05:02  Iran Saqqez-Baneh Kurds 0.833360
 773  A*02-B*51-DRB1*03:01-DQB1*02:01  Mexico Sinaloa Capomos Mayo Yoremes 0.833360
 774  A*02-B*51-DRB1*04:07-DQB1*03:02  Mexico Sinaloa Capomos Mayo Yoremes 0.833360
 775  A*02-B*51-DRB1*04-DQB1*03:01  Mexico Veracruz, Orizaba 0.833360
 776  A*02-B*51-DRB1*14:46-DQB1*03:01  Mexico Sinaloa Capomos Mayo Yoremes 0.833360
 777  A*03:01:01:01-B*51:01:01-C*16:02:01-DRB1*04:04:01-DQB1*03:02  Russia Bashkortostan, Bashkirs 0.8333120
 778  A*03:01-B*51:01-DRB1*04:15-DQB1*03:01  Iran Saqqez-Baneh Kurds 0.833360
 779  A*03:02-B*51:01-DRB1*08:01-DQB1*03:02  Iran Saqqez-Baneh Kurds 0.833360
 780  A*11:01-B*51:01-DRB1*11:01-DQB1*03:01  Iran Saqqez-Baneh Kurds 0.833360
 781  A*23-B*51-DRB1*14:03-DQB1*03:01  Mexico Sinaloa Capomos Mayo Yoremes 0.833360
 782  A*24:02-B*51:01-DRB1*11:01-DQB1*03:01  Iran Saqqez-Baneh Kurds 0.833360
 783  A*24:02-B*51:07-DRB1*15:01-DQB1*05:01  Iran Saqqez-Baneh Kurds 0.833360
 784  A*24-B*51-DRB1*04:03-DQB1*03:02  Mexico Sinaloa Capomos Mayo Yoremes 0.833360
 785  A*24-B*51-DRB1*07:01-DQB1*02:01  Mexico Sinaloa Capomos Mayo Yoremes 0.833360
 786  A*24-B*51-DRB1*13:47-DQB1*06:03  Mexico Sinaloa Capomos Mayo Yoremes 0.833360
 787  A*31-B*51-DRB1*04:07-DQB1*03:01  Mexico Sinaloa Capomos Mayo Yoremes 0.833360
 788  A*31-B*51-DRB1*08:02-DQB1*03:01  Mexico Sinaloa Capomos Mayo Yoremes 0.833360
 789  A*68:01:02:02-B*51:01:01-C*15:02:01:01-DRB1*15:01:01-DQB1*06:02  Russia Bashkortostan, Bashkirs 0.8333120
 790  A*68-B*51-DRB1*14:06-DQB1*03:01  Mexico Sinaloa Capomos Mayo Yoremes 0.833360
 791  A*24-B*51-DRB1*08-DQB1*04  Mexico Tlaxcala, Tlaxcala city 0.8287181
 792  A*68-B*51-DRB1*14-DQB1*03:01  Mexico Tlaxcala, Tlaxcala city 0.8287181
 793  A*24-B*51-DRB1*04-DQB1*03:02  Mexico Chiapas Rural 0.8264121
 794  A*68-B*51-DRB1*04-DQB1*03:02  Mexico Chiapas Rural 0.8264121
 795  A*02-B*51-DRB1*04-DQB1*03:02  Mexico Oaxaca Rural 0.8214485
 796  A*02:01-B*51:01-DRB1*13:02  Israel Georgia Jews 0.82104,471
 797  A*02-B*51-DRB1*04-DQB1*03:02  Mexico Sinaloa Rural 0.8197183
 798  A*11-B*51-DRB1*14-DQB1*05  Mexico Colima, Colima city 0.819761
 799  A*24-B*51-DRB1*14-DQB1*03:01  Mexico Colima, Colima city 0.819761
 800  A*31-B*51-DRB1*15-DQB1*06  Mexico Colima, Colima city 0.819761

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 13,576) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 136  


   

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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