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 901 to 1,000 (from 4,695) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 47  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 901  A*03:01-B*35:03-C*12:03-DRB1*14:04-DQB1*05:03  India Tamil Nadu 0.08032,492
 902  A*11:01-B*35:03-C*12:03-DRB1*14:04-DQB1*05:03  India North UCBB 0.08015,849
 903  A*02:11-B*52:01-C*12:02-DRB1*14:04-DQB1*05:03  India South UCBB 0.079911,446
 904  A*02:01:01-B*07:02:01-C*07:02:01-DRB1*14:54:01-DQB1*05:03:01  Poland BMR 0.079923,595
 905  A*02:01-B*27:05-C*02:02-DRB1*14:01-DQB1*05:03-DPB1*03:01  Russia Karelia 0.07841,075
 906  A*24:02-B*35:03-C*12:03-DRB1*14:54-DQB1*05:03  India Central UCBB 0.07844,204
 907  A*01-B*13-DRB1*14:02-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 908  A*01-B*57-DRB1*14:01-DQA1*01:01-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 909  A*02-B*13-DRB1*14:01-DQA1*01:01-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 910  A*02-B*13-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 911  A*02-B*35-DRB1*04:11-DQA1*01:02-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 912  A*02-B*44-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 913  A*02-B*45-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 914  A*02-B*51-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 915  A*02-B*53-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 916  A*03-B*15-DRB1*13:08-DQA1*01:01-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 917  A*03-B*18-DRB1*14:01-DQA1*01:01-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 918  A*03-B*18-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 919  A*03-B*35-DRB1*14:01-DQA1*01:01-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 920  A*03-B*41-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 921  A*03-B*45-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 922  A*03-B*51-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 923  A*11-B*18-DRB1*14:01-DQA1*01:01-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 924  A*11-B*39-DRB1*11:13-DQA1*01:01-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 925  A*24:02-B*51:01-C*14:02-DRB1*14:04-DQB1*05:03  India South UCBB 0.078011,446
 926  A*24-B*15-DRB1*14:01-DQA1*01:01-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 927  A*24-B*35-DRB1*14:01-DQA1*01:01-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 928  A*24-B*44-DRB1*14:01-DQA1*01:01-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 929  A*26-B*08-DRB1*01:01-DQA1*01:01-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 930  A*26-B*14-DRB1*14:01-DQA1*01:01-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 931  A*29-B*15-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 932  A*29-B*38-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 933  A*30-B*13-DRB1*14:01-DQA1*03:01-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 934  A*30-B*52-DRB1*14:01-DQA1*01:01-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 935  A*31:01-B*39:01-C*12:03-DRB1*14:01-DQB1*05:03  Germany DKMS - Italy minority 0.07801,159
 936  A*32-B*50-DRB1*13:01-DQA1*01:03-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 937  A*68-B*07-DRB1*14:01-DQA1*01:01-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 938  A*68-B*39-DRB1*14:01-DQA1*01:01-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 939  A*02:11-B*18:01-C*07:01-DRB1*14:04-DQB1*05:03  India Tamil Nadu 0.07742,492
 940  A*24:02:01-B*51:01:01-C*15:02:01-DRB1*14:05:01-DQB1*05:03:01  China Zhejiang Han 0.07741,734
 941  A*24:02-B*52:01-C*12:02-DRB1*14:04-DQB1*05:03  India South UCBB 0.077411,446
 942  A*01:01-B*37:01-C*06:02-DRB1*14:04-DQB1*05:03  India Central UCBB 0.07724,204
 943  A*24:02-B*15:05-C*03:03-DRB1*15:02-DQB1*05:03  India West UCBB 0.07695,829
 944  A*26:01-B*55:01-C*03:03-DRB1*14:54-DQB1*05:03  India North UCBB 0.07695,849
 945  A*68:01-B*52:01-C*12:02-DRB1*14:04-DQB1*05:03  India Central UCBB 0.07654,204
 946  A*24:02-B*40:06-C*12:04-DRB1*14:04-DQB1*05:03  India Tamil Nadu 0.07502,492
 947  A*01:01-B*37:01-C*06:02-DRB1*14:04-DQB1*05:03  India North UCBB 0.07485,849
 948  A*24:02-B*35:03-C*12:03-DRB1*14:54-DQB1*05:03  India North UCBB 0.07485,849
 949  A*03:01-B*40:06-C*15:02-DRB1*14:04-DQB1*05:03  India South UCBB 0.074711,446
 950  A*11:01-B*35:01-C*04:01-DRB1*14:01-DQB1*05:03-DPB1*04:01  Germany DKMS - German donors 0.07453,456,066
 951  A*24:02-B*15:01-C*03:03-DRB1*14:04-DQB1*05:03  India West UCBB 0.07445,829
 952  A*24:02-B*40:01-C*12:03-DRB1*14:04-DQB1*05:03  India South UCBB 0.073811,446
 953  A*24:02-B*35:03-C*12:03-DRB1*14:01-DQB1*05:03  India Tamil Nadu 0.07372,492
 954  A*33:03-B*35:03-C*04:01-DRB1*14:04-DQB1*05:03  India East UCBB 0.07362,403
 955  A*02:11-B*35:03-C*04:01-DRB1*14:04-DQB1*05:03  India West UCBB 0.07355,829
 956  A*11:01-B*07:06-C*07:02-DRB1*14:04-DQB1*05:03  India West UCBB 0.07335,829
 957  DRB1*13:04-DQB1*05:03-DPB1*414:01  Gambia pop 3 0.0726939
 958  A*26:01-B*55:01-C*01:02-DRB1*14:04-DQB1*05:03  India Tamil Nadu 0.07242,492
 959  A*24:02-B*35:01-C*04:01-DRB1*14:04-DQB1*05:03  India West UCBB 0.07245,829
 960  A*68:01-B*35:03-C*04:01-DRB1*14:04-DQB1*05:03  India Central UCBB 0.07214,204
 961  A*68:01-B*35:03-C*04:01-DRB1*14:04-DQB1*05:03  India Tamil Nadu 0.07212,492
 962  DRB1*14:07-DQA1*01:04-DQB1*05:03-DPA1*02:02-DPB1*05:01  China Zhejiang Han pop 2 0.0720833
 963  A*24:02-B*15:05-C*03:03-DRB1*15:02-DQB1*05:03  India Central UCBB 0.07134,204
 964  A*33:03-B*52:01-C*12:02-DRB1*14:04-DQB1*05:03  India East UCBB 0.07092,403
 965  A*11:01-B*35:03-C*12:03-DRB1*14:54-DQB1*05:03  India West UCBB 0.07055,829
 966  A*68:01-B*51:01-C*14:02-DRB1*14:04-DQB1*05:03  India South UCBB 0.070511,446
 967  A*01:01-B*13:01-C*04:03-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*04:01  Sri Lanka Colombo 0.0700714
 968  A*01:01-B*15:17-C*07:01-DRB1*13:02-DQA1*01:02-DQB1*05:03-DPB1*14:01  Sri Lanka Colombo 0.0700714
 969  A*01:01-B*15:18-C*07:04-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*02:01  Sri Lanka Colombo 0.0700714
 970  A*01:01-B*37:01-C*06:02-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*02:01  Sri Lanka Colombo 0.0700714
 971  A*01:01-B*37:01-C*06:02-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*04:01  Sri Lanka Colombo 0.0700714
 972  A*01:01-B*40:02-C*14:02-DRB1*04:03-DQA1*01:01-DQB1*05:03-DPB1*14:01  Sri Lanka Colombo 0.0700714
 973  A*01:01-B*57:01-C*06:02-DRB1*04:08-DQA1*01:01-DQB1*05:03-DPB1*02:01  Sri Lanka Colombo 0.0700714
 974  A*02:01-B*35:03-C*04:01-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*09:01  Sri Lanka Colombo 0.0700714
 975  A*02:01-B*35:03-C*12:03-DRB1*14:01-DQA1*01:01-DQB1*05:03-DPB1*26:01  Sri Lanka Colombo 0.0700714
 976  A*02:01-B*51:01-C*07:02-DRB1*14:01-DQA1*01:01-DQB1*05:03-DPB1*04:01  Sri Lanka Colombo 0.0700714
 977  A*02:03-B*35:01-C*04:01-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*04:02  Sri Lanka Colombo 0.0700714
 978  A*02:03-B*39:01-C*03:03-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*04:01  Sri Lanka Colombo 0.0700714
 979  A*02:05-B*40:02-C*04:01-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*04:01  Sri Lanka Colombo 0.0700714
 980  A*02:05-B*50:01-C*06:02-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*01:01  Sri Lanka Colombo 0.0700714
 981  A*02:06-B*15:01-C*03:03-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*02:01  Sri Lanka Colombo 0.0700714
 982  A*02:06-B*35:03-C*04:01-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*02:01  Sri Lanka Colombo 0.0700714
 983  A*02:06-B*40:06-C*01:02-DRB1*14:01-DQA1*01:01-DQB1*05:03-DPB1*14:01  Sri Lanka Colombo 0.0700714
 984  A*02:11-B*15:05-C*03:03-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*04:01  Sri Lanka Colombo 0.0700714
 985  A*02:11-B*18:01-C*07:01-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*13:01  Sri Lanka Colombo 0.0700714
 986  A*02:11-B*35:03-C*04:01-DRB1*14:01-DQA1*01:01-DQB1*05:03-DPB1*04:01  Sri Lanka Colombo 0.0700714
 987  A*02:11-B*40:06-C*12:02-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*03:01  Sri Lanka Colombo 0.0700714
 988  A*02:11-B*40:06-C*15:02-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*83:01  Sri Lanka Colombo 0.0700714
 989  A*02:11-B*52:01-C*12:02-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*04:01  Sri Lanka Colombo 0.0700714
 990  A*02:16-B*15:38-C*02:08-DRB1*08:02-DQA1*04:01-DQB1*05:03-DPB1*04:01  Sri Lanka Colombo 0.0700714
 991  A*02:16-B*18:01-C*07:01-DRB1*14:10-DQA1*01:01-DQB1*05:03-DPB1*04:01  Sri Lanka Colombo 0.0700714
 992  A*02:16-B*35:03-C*12:03-DRB1*14:01-DQA1*01:01-DQB1*05:03-DPB1*15:01  Sri Lanka Colombo 0.0700714
 993  A*03:01-B*07:02-C*07:01-DRB1*14:01-DQA1*01:01-DQB1*05:03-DPB1*13:01  Sri Lanka Colombo 0.0700714
 994  A*03:01-B*15:01-C*03:03-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*04:01  Sri Lanka Colombo 0.0700714
 995  A*03:01-B*40:02-C*15:02-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*02:01  Sri Lanka Colombo 0.0700714
 996  A*11:01-B*07:02-C*03:04-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*02:01  Sri Lanka Colombo 0.0700714
 997  A*11:01-B*15:01-C*01:02-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*02:01  Sri Lanka Colombo 0.0700714
 998  A*11:01-B*15:02-C*08:01-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*03:01  Sri Lanka Colombo 0.0700714
 999  A*11:01-B*35:01-C*07:04-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*16:01  Sri Lanka Colombo 0.0700714
 1,000  A*11:01-B*40:06-C*15:02-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*26:01  Sri Lanka Colombo 0.0700714

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 901 to 1,000 (from 4,695) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 47  


   

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