Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

Please specify your search by selecting options from boxes. Then, click "Search" to find HLA Haplotype frequencies that match your criteria. Remember at least one option must be selected.
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 801 to 900 (from 15,562) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 156  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 801  A*01-B*07-DRB1*04-DQB1*03:01  Mexico Veracruz, Orizaba 0.833360
 802  A*01-B*39-DRB1*14:06-DQB1*03:01  Mexico Sinaloa Capomos Mayo Yoremes 0.833360
 803  A*01-B*52-DRB1*15-DQB1*06  Mexico Tlaxcala, Tlaxcala city 0.8287181
 804  A*01:01-B*57:01-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*03:03  USA NMDP European Caucasian 0.82801,242,890
 805  A*01-B*37-DRB1*10-DQB1*05  Mexico Chiapas Rural 0.8264121
 806  A*01:01:01-B*44:03:02-C*07:06-DRB1*07:01:01-DQB1*02:02:01  India Andhra Pradesh Telugu Speaking 0.8213186
 807  A*01:01-B*52:01-DRB1*12:01  Israel Bukhara Jews 0.82002,317
 808  A*01-B*07-DRB1*13-DQB1*03:01  Mexico Colima, Colima city 0.819761
 809  A*01-B*08-DRB1*07-DQB1*02  Mexico Colima, Colima city 0.819761
 810  A*01-B*35-DRB1*08-DQB1*04  Mexico Colima, Colima city 0.819761
 811  A*01-B*35-DRB1*13-DQB1*06  Mexico Colima, Colima city 0.819761
 812  A*01-B*38-DRB1*11-DQB1*06  Mexico Colima, Colima city 0.819761
 813  A*01-B*52-DRB1*15-DQB1*06  Mexico Sinaloa Rural 0.8197183
 814  A*01-B*57-DRB1*03:01-DQB1*02  Mexico Colima, Colima city 0.819761
 815  A*01:01-B*58:01-DRB1*07:01  Israel Ashkenazi Jews pop 3 0.81304,625
 816  A*01:02-B*49:01:01-C*07:01:01-DRB1*04:06:01  Costa Rica Amerindians (G) 0.8065125
 817  A*01:01-B*08:01-C*12:03-DRB1*13:01-DQA1*01:03-DQB1*06:03  Kosovo 0.8060124
 818  A*01:01-B*35:01-C*12:03-DRB1*14:54-DQA1*01:01-DQB1*05:03  Kosovo 0.8060124
 819  A*01:01-B*35:02-C*04:01-DRB1*04:03-DQA1*03:01-DQB1*03:02  Kosovo 0.8060124
 820  A*01:01-B*57:01-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*03:03  USA NMDP Vietnamese 0.804843,540
 821  A*01-B*08-DRB1*03  Iraq Erbil 0.8000372
 822  A*01-B*08-DRB1*03:01  Colombia Barranquilla 0.8000188
 823  A*01-B*35-DRB1*04  Iraq Erbil 0.8000372
 824  A*01-B*35-DRB1*11  Germany pop 7 0.800013,386
 825  A*01-B*35-DRB1*11  Iraq Erbil 0.8000372
 826  A*01-B*35-DRB1*13  Iraq Erbil 0.8000372
 827  A*01-B*41-DRB1*10  Iraq Erbil 0.8000372
 828  A*01:01-B*45:01-C*06:02-DRB1*13:02-DQB1*06:04-DPB1*03:01  Tanzania Maasai 0.7987336
 829  A*01:01-G*01:01  Ecuador Amerindians 0.793763
 830  A*01:01-G*01:03  Ecuador Amerindians 0.793763
 831  A*01-B*15:03-DRB1*03:02-DQB1*04  Mexico Tamaulipas Rural 0.7937125
 832  A*01-B*35-DRB1*11-DQB1*06  Mexico Tamaulipas Rural 0.7937125
 833  A*01-B*49-DRB1*04-DQB1*03:02  Mexico Tamaulipas Rural 0.7937125
 834  A*01-B*57-DRB1*01-DQB1*05  Mexico Tamaulipas Rural 0.7937125
 835  A*01-B*08-DRB1*03:01-DQB1*02  Ecuador Andes Mixed Ancestry 0.7888824
 836  A*01:01-B*57:01-C*06:02-DRB1*07:01-DQB1*03:03  Germany DKMS - Italy minority 0.78801,159
 837  A*01:01-B*57:01-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*03:03  USA NMDP North American Amerindian 0.782335,791
 838  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Nayarit Rural 0.781264
 839  A*01-B*15:01-DRB1*13-DQB1*06  Mexico Nayarit Rural 0.781264
 840  A*01-B*44-C*02-DRB1*01  Macedonia MBMDR - Albanian 0.7812128
 841  A*01-B*44-C*05-DRB1*11  Macedonia MBMDR - Albanian 0.7812128
 842  A*01-B*51-C*12-DRB1*11  Macedonia MBMDR - Albanian 0.7812128
 843  A*01-B*57-DRB1*07-DQB1*03:03  Mexico Nayarit Rural 0.781264
 844  A*01:01-B*44:03-C*04:01-DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*04:01  USA San Diego 0.7810496
 845  A*01-B*07-C*01-DRB1*14  Myanmar Mon 0.781064
 846  A*01:01-B*07:02-C*07:08-DRB1*14:01-DQB1*03:04  Iran Gorgan 0.780064
 847  A*01:01-B*37:01-C*03:02-DRB1*10:01-DQB1*05:02  Iran Gorgan 0.780064
 848  A*01:02-B*07:02-C*07:03-DRB1*15:01-DQB1*04:01  Iran Gorgan 0.780064
 849  A*01:02-B*13:01-C*15:02-DRB1*07:01-DQB1*02:01  Iran Gorgan 0.780064
 850  A*01:02-B*15:17-C*07:01-DRB1*01:01-DQB1*05:01  Iran Gorgan 0.780064
 851  A*01:02-B*35:01-C*14:02-DRB1*13:02-DQB1*03:07  Iran Gorgan 0.780064
 852  A*01:02-B*37:01-C*04:01-DRB1*03:01-DQB1*02:01  Iran Gorgan 0.780064
 853  A*01:02-B*57:01-C*12:03-DRB1*03:03-DQB1*03:02  Iran Gorgan 0.780064
 854  A*01-B*07-C*07:02-DRB1*11-DQB1*03  Russia North Ossetian 0.7800127
 855  A*01-B*08-C*07  Brazil Parana Japanese 0.7800192
 856  A*01-B*15-C*07:01-DRB1*07-DQB1*02  Russia North Ossetian 0.7800127
 857  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Puebla Rural 0.7794833
 858  A*01:01-B*52:01-DRB1*15:02  Israel Iraq Jews 0.776013,270
 859  A*01:01-B*57:01-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*03:03-DPB1*13:01  Sri Lanka Colombo 0.7703714
 860  A*01-B*51-DRB1*04  Iran pop 4 0.7703855
 861  A*01:01-B*38:01-DRB1*11:04-DQB1*03:01  Chile Mapuche 0.770066
 862  A*01:01-B*39:03-DRB1*15:02-DQB1*03:01  Chile Mapuche 0.770066
 863  A*01:01-B*39:06-DRB1*04:03-DQB1*03:02  Chile Mapuche 0.770066
 864  A*01:01-B*48:01-DRB1*14:06-DQB1*03:01  Chile Mapuche 0.770066
 865  A*01:01-B*51:01-DRB1*04:02-DQB1*03:02  Chile Mapuche 0.770066
 866  A*01:01-B*51:01-DRB1*08:02-DQB1*03:01  Chile Mapuche 0.770066
 867  A*01:01-B*57:01-DRB1*07:01-DQB1*03:03  Chile Mapuche 0.770066
 868  A*01:01-B*57:03-DRB1*07:01-DQB1*03:03  Chile Mapuche 0.770066
 869  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Sonora Rural 0.7614197
 870  A*01:01-B*57:01-C*06:02-DRB1*07:01-DQB1*03:03  USA Asian pop 2 0.75501,772
 871  A*01:01-B*35:02-DRB1*11:04  Israel Bukhara Jews 0.75102,317
 872  A*01-B*52-DRB1*15-DQB1*06  Mexico Coahuila, Torreon 0.7500396
 873  A*01-B*57-DRB1*07  Russia Moscow Pop 2 0.75002,000
 874  A*01:01-B*08:01-C*07:01-DRB1*03:01-DRB3*01:01-DQB1*02:01  USA NMDP Caribean Black 0.748133,328
 875  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Yucatan Rural 0.7463132
 876  A*01-B*35-DRB1*11-DQB1*03:01  Mexico Yucatan Rural 0.7463132
 877  A*01-B*49-DRB1*11-DQB1*03:01  Mexico Yucatan Rural 0.7463132
 878  A*01-B*49-DRB1*13-DQB1*06  Mexico Yucatan Rural 0.7463132
 879  A*01:01-B*08:01-DRB1*03:01  Israel Arab pop 2 0.740012,301
 880  A*01:01-B*15:17-C*07:01-DRB1*13:02-DQB1*06:04  Italy pop 5 0.7400975
 881  A*01-B*37-DRB1*11  Albania pop 2 0.7400432
 882  A*01:01-B*57:01  USA Hispanic pop 2 0.73601,999
 883  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.731523,595
 884  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Mexico City North 0.7304751
 885  A*01-B*15-DRB1*11:01-DQB1*03:01  Bolivia Quechua 0.720069
 886  A*01-B*15-DRB1*13:01-DQB1*06:07  Bolivia Quechua 0.720069
 887  A*01-B*35-DRB1*08:02-DQB1*04:02  Bolivia Quechua 0.720069
 888  A*01-B*37-DRB1*04:07-DQB1*02:01  Bolivia Quechua 0.720069
 889  A*01-B*44-DRB1*07:01-DQB1*02:01  Bolivia Quechua 0.720069
 890  A*01-B*48-DRB1*14:06-DQB1*03:01  Bolivia Quechua 0.720069
 891  A*01:01-B*57:01-C*06:02-DRB1*07:01  Poland DKMS 0.717620,653
 892  A*01:01-B*41:01-DRB1*07:01  Israel Iran Jews 0.71208,153
 893  A*01-B*52-DRB1*15-DQB1*06  Mexico Jalisco, Guadalajara city 0.71191,189
 894  A*01-B*57-DRB1*07:01  Chile Santiago 0.7103920
 895  A*01:01-B*40:06-C*15:02-DRB1*15:02-DQB1*06:01  India West UCBB 0.70975,829
 896  A*01:01:01:01-B*57:01:01-C*06:02:01:01-DRB1*07:01:01-DQB1*03:03:02  Russia Nizhny Novgorod, Russians 0.70431,510
 897  A*01-B*08-DRB1*03:01-DQB1*02  Mexico Tabasco Rural 0.7042142
 898  A*01-B*35-DRB1*14-DQB1*05  Mexico Tabasco Rural 0.7042142
 899  A*01:01:01-B*81:01-C*18:01-DRB1*11:01:02-DQB1*03:19:01-DPB1*105:01:01  South African Black 0.7040142
 900  A*01:01-B*57:01-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*03:03-DPB1*09:01  Sri Lanka Colombo 0.7003714

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 801 to 900 (from 15,562) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 156  


   

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.

support@allelefrequencies.net

Valid XHTML 1.0 Transitional