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 8,334) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 84  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 901  A*26:01:01-B*55:01:01-C*03:03:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.006523,595
 902  A*26:01:01-B*55:01:01-C*03:03:01-DRB1*11:01:01-DQB1*03:02:01  Poland BMR 0.006423,595
 903  A*26:01:01-B*55:01:01-C*03:03:01-DRB1*11:03:01-DQB1*02:01:01  Poland BMR 0.002123,595
 904  A*26:01:01-B*55:01:01-C*03:03:01-DRB1*11:03:01-DQB1*02:02:01  Poland BMR 0.004323,595
 905  A*26:01:01-B*55:01:01-C*03:03:01-DRB1*11:03:01-DQB1*03:01:01  Poland BMR 0.100023,595
 906  A*26:01:01-B*55:01:01-C*03:03:01-DRB1*11:03:01-DQB1*06:03:01  Poland BMR 0.006423,595
 907  A*26:01:01-B*55:01:01-C*03:03:01-DRB1*11:04:01-DQB1*03:01:01  Poland BMR 0.004623,595
 908  A*26:01:01-B*55:01:01-C*03:03:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.019023,595
 909  A*26:01:01-B*55:01:01-C*03:03:01-DRB1*13:03:01-DQB1*05:02:01  Poland BMR 0.002123,595
 910  A*26:01:01-B*55:01:01-C*03:03:01-DRB1*14:54:01-DQB1*05:03:01  Poland BMR 0.012423,595
 911  A*26:01:01-B*55:01:01-C*03:03:01-DRB1*14:54-DQB1*05:03:01  Russia Nizhny Novgorod, Russians 0.06571,510
 912  A*26:01:01-B*55:01:01-C*03:03:01-DRB1*15:01:01-DQA1*02:01-DQB1*02:02-DPA1*01:03:01-DPB1*04:02  Russia Belgorod region 0.3268153
 913  A*26:01:01-B*55:01:01-C*03:03:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.005723,595
 914  A*26:01:01-B*55:01:01-C*03:03:01-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.03371,510
 915  A*26:01:01-B*55:01:01-C*03:03:01-DRB1*15:01:01-DQB1*06:03:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 916  A*26:01:01-B*55:01:01-C*03:03:01-DRB1*16:01:01-DQB1*05:02  Russia Nizhny Novgorod, Russians 0.03311,510
 917  A*26:01:01-B*55:01:01-C*03:03:01-DRB1*16:01:01-DQB1*05:02:01  Poland BMR 0.037323,595
 918  A*26:01:01-B*55:01:01-C*03:03:01-DRB1*16:01:01-DQB1*05:02:01-DPA1*02:01:01-DPB1*14:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 919  A*26:01:01-B*55:01:01-C*15:02:01  South African Indian population 1.000050
 920  A*26:01:01-B*55:02:01-C*01:02:01-DRB1*12:02:01-DQB1*03:01:01  China Zhejiang Han 0.02881,734
 921  A*26:01:01-B*55:02:01-C*01:02:01-DRB1*14:05:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00575,266
 922  A*26:01:01-B*55:02:01-C*01:02:01-DRB1*14:54:01-DPB1*04:02:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00645,266
 923  A*26:01:01-B*55:02:01-C*01:02:01-DRB1*14:54:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00535,266
 924  A*26:01:01-B*55:02:01-C*01:02:01-DRB1*15:01:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00905,266
 925  A*26:01:01-B*55:02:01-C*12:03:01-DRB1*14:05:01-DQB1*05:03:01  China Zhejiang Han 0.02881,734
 926  A*26:01:01-B*55:02:01-C*15:02:01-DRB1*11:01:01-DPB1*14:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00915,266
 927  A*26:01:01-B*55:02:01-C*15:02:01-DRB1*13:12:01-DPB1*13:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00955,266
 928  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*01:01:01-DQB1*02:02:01  Poland BMR 0.002823,595
 929  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*01:01:01-DQB1*04:02:01  Poland BMR 0.002023,595
 930  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.013023,595
 931  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*01:01:01-DQB1*06:02:01  Poland BMR 0.000938623,595
 932  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*04:01:01-DQB1*03:01:01  Poland BMR 0.001723,595
 933  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*04:01:01-DQB1*03:02:01  Poland BMR 0.002123,595
 934  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*04:04:01-DQB1*03:02  Russia Nizhny Novgorod, Russians 0.06621,510
 935  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.014723,595
 936  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.037323,595
 937  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*07:01:01-DQB1*03:01:01  Poland BMR 0.002123,595
 938  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*07:01:01-DQB1*05:02:01  Poland BMR 0.002123,595
 939  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*08:01:01-DQB1*03:01:01  Poland BMR 0.005023,595
 940  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.093623,595
 941  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*08:01:01-DQB1*04:02:01  Russia Nizhny Novgorod, Russians 0.06621,510
 942  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*08:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 943  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.006623,595
 944  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*11:04:01-DQB1*03:01:01  Poland BMR 0.006423,595
 945  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.012423,595
 946  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*13:03:01-DQB1*03:01:01  Poland BMR 0.001723,595
 947  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*14:54:01-DQB1*05:03:01  Poland BMR 0.006323,595
 948  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.015123,595
 949  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*15:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 950  A*26:01:01-B*56:01:01-C*01:02:01-DRB1*16:01:01-DQB1*05:02:01  Poland BMR 0.025623,595
 951  A*26:01:01-B*56:01:01-C*03:03:01-DRB1*07:01:01-DQB1*02:01:01  China Zhejiang Han 0.02881,734
 952  A*26:01:01-B*57:01:01-C*04:01:01-DRB1*13:01:01-DQB1*06:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 953  A*26:01:01-B*57:01:01-C*04:01:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.002123,595
 954  A*26:01:01-B*57:01:01-C*06:02:01  England Blood Donors of Mixed Ethnicity 0.1927519
 955  A*26:01:01-B*57:01:01-C*06:02:01:01-DRB1*13:03:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.03011,510
 956  A*26:01:01-B*57:01:01-C*06:02:01-DRB1*01:01:01-DQB1*02:01:01  Poland BMR 0.002123,595
 957  A*26:01:01-B*57:01:01-C*06:02:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.004823,595
 958  A*26:01:01-B*57:01:01-C*06:02:01-DRB1*01:01:01-DQB1*06:02:01  Poland BMR 0.002023,595
 959  A*26:01:01-B*57:01:01-C*06:02:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.004423,595
 960  A*26:01:01-B*57:01:01-C*06:02:01-DRB1*04:05:01-DQB1*03:02:01  Poland BMR 0.001823,595
 961  A*26:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.008523,595
 962  A*26:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  India Karnataka Kannada Speaking 0.2870174
 963  A*26:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.072323,595
 964  A*26:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  Russia Nizhny Novgorod, Russians 0.06621,510
 965  A*26:01:01-B*57:01:01-C*06:02:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.000116823,595
 966  A*26:01:01-B*57:01:01-C*06:02:01-DRB1*12:01:01-DQB1*03:01:01  Poland BMR 0.001923,595
 967  A*26:01:01-B*57:01:01-C*06:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.002423,595
 968  A*26:01:01-B*57:01:01-C*06:02:01-DRB1*13:02:01-DQB1*06:04:01  Poland BMR 0.002123,595
 969  A*26:01:01-B*57:01:01-C*06:02:01-DRB1*15:01:01-DQB1*02:02:01  Poland BMR 0.002123,595
 970  A*26:01:01-B*57:01:01-C*06:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.007223,595
 971  A*26:01:01-B*57:01:01-C*06:02:01-DRB1*15:01:01-DQB1*06:03:01  Poland BMR 0.002423,595
 972  A*26:01:01-B*57:01:01-C*06:02:01-DRB1*15:02:01-DQB1*05:03:01  India Andhra Pradesh Telugu Speaking 0.2688186
 973  A*26:01:01-B*57:01:01-C*06:02:01-DRB1*16:01:01-DQB1*05:02:01  Poland BMR 0.006423,595
 974  A*26:01:01-B*57:01:01-C*07:01:01-DRB1*07:01:01-DQB1*02:02:01  India Kerala Malayalam speaking 0.1400356
 975  A*26:01:01-B*57:01:01-C*07:01:01-DRB1*07:01:01-DQB1*03:01:04-DPA1*01:03:01-DPB1*10:01:01  Brazil Rio de Janeiro Parda 0.5882170
 976  A*26:01:01-B*58:01:01-C*03:02:02-DRB1*01:01:01-DQB1*02:02:01  Poland BMR 0.004223,595
 977  A*26:01:01-B*58:01:01-C*03:02:02-DRB1*01:01:01-DQB1*03:01:01  Poland BMR 0.004223,595
 978  A*26:01:01-B*58:01:01-C*03:02:02-DRB1*01:01:01-DQB1*03:03:02  Poland BMR 0.002123,595
 979  A*26:01:01-B*58:01:01-C*03:02:02-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.007623,595
 980  A*26:01:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DPB1*04:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.01295,266
 981  A*26:01:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00955,266
 982  A*26:01:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DPB1*13:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00725,266
 983  A*26:01:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQA1*05:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*04:01  Russian Federation Vologda Region 0.4202119
 984  A*26:01:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.006423,595
 985  A*26:01:01-B*58:01:01-C*03:02:02-DRB1*04:01:01-DQB1*03:02:01  Poland BMR 0.004023,595
 986  A*26:01:01-B*58:01:01-C*03:02:02-DRB1*04:05:01-DQB1*03:02:01-DPA1*01:03:01-DPB1*01:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 987  A*26:01:01-B*58:01:01-C*03:02:02-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.000812323,595
 988  A*26:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:04:01  Poland BMR 0.002123,595
 989  A*26:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  China Zhejiang Han 0.02881,734
 990  A*26:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  India Kerala Malayalam speaking 0.1400356
 991  A*26:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  Poland BMR 0.006723,595
 992  A*26:01:01-B*58:01:01-C*03:02:02-DRB1*14:54:01-DQB1*05:03:01  Poland BMR 0.002123,595
 993  A*26:01:01-B*58:01:01-C*03:02:02-DRB1*16:01:01-DQB1*05:02:01  Poland BMR 0.002123,595
 994  A*26:01:01-B*58:01:01-C*03:04:01-DRB1*04:11:01  Nicaragua Mestizo (G) 0.3226155
 995  A*26:01:01-B*58:01:01-C*04:01:01-DRB1*13:02:01-DQB1*06:09:01  Russia Nizhny Novgorod, Russians 0.03311,510
 996  A*26:01:01-B*58:01:01-C*05:01:01-DRB1*01:02:01-DQB1*02:01:01  Poland BMR 0.002123,595
 997  A*26:01:01-B*58:01:01-C*12:03:01-DRB1*07:01:01-DQB1*03:01:01-DPA1*02:01:01-DPB1*03:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 998  A*26:01:01-B*58:02:01-C*06:02:01-DRB1*13:01:01-DQB1*06:04:01-DPB1*14:01:01  South African Black 0.3520142
 999  A*26:01:01-B*59:01:01-C*01:02:01-DRB1*12:02:01-DQB1*03:01:01  China Zhejiang Han 0.02881,734
 1,000  A*26:01:01-B*67:01:01-C*07:02:01-DRB1*16:02:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00615,266

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 8,334) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 84  


   

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