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 801 to 900 (from 1,218) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 13  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 801  A*33:03-B*44:03-C*07:01-DRB1*07:01-DQB1*02:01  Germany DKMS - Turkey minority 0.04204,856
 802  A*30-B*44-DRB1*07-DQB1*02  Mexico Jalisco, Guadalajara city 0.04191,189
 803  A*32-B*44-DRB1*07-DQB1*02  Mexico Jalisco, Guadalajara city 0.04191,189
 804  A*01:01-B*44:03-C*07:06-DRB1*07:03-DQB1*02:02  India South UCBB 0.041711,446
 805  A*02:01-B*44:03-C*04:01-DRB1*07:01-DQB1*02:01  Germany DKMS - Turkey minority 0.04104,856
 806  A*23:01-B*44:03-C*04:01-DRB1*07:01-DQB1*02:02  India East UCBB 0.04062,403
 807  A*24:02-B*44:03-C*16:01-DRB1*07:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.04041,463
 808  A*02:01-B*44:03-C*04:01-DRB1*07:01-DQB1*02:01  India Tamil Nadu 0.04012,492
 809  A*11-B*44-C*16-DRB1*07-DQB1*02-DPB1*04  Norway ethnic Norwegians 0.04004,510
 810  A*26:01:01-B*44:03:01-C*04:01:01-DRB1*07:01:01-DQB1*02:02  Russia Nizhny Novgorod, Russians 0.03891,510
 811  A*02:06-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India North UCBB 0.03825,849
 812  A*24:02-B*44:03-C*02:02-DRB1*07:01-DQB1*02:01  USA Hispanic pop 2 0.03801,999
 813  A*26:01-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India South UCBB 0.038011,446
 814  A*33:03-B*44:03-C*07:01-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Middle Eastern or North Coast of Africa 0.037370,890
 815  A*23:01-B*44:03-C*04:01-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Filipino 0.037350,614
 816  A*11:01-B*44:03-C*05:01-DRB1*07:01-DQB1*02:02  India Central UCBB 0.03724,204
 817  A*01:01-B*44:03-C*04:01-DRB1*07:01-DQB1*02:01  Germany DKMS - Turkey minority 0.03704,856
 818  A*26:01-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India North UCBB 0.03685,849
 819  A*01:01-B*44:03-C*05:01-DRB1*07:01-DQB1*02:02  India Central UCBB 0.03574,204
 820  A*24:02-B*44:03-C*04:01-DRB1*07:01-DQB1*02:01  Germany DKMS - Turkey minority 0.03504,856
 821  A*11:01-B*44:03-C*15:02-DRB1*07:01-DQB1*02:02  India South UCBB 0.034911,446
 822  A*01:01-B*44:03-C*16:01-DRB1*07:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.03491,463
 823  A*11:01-B*44:03-C*05:01-DRB1*07:01-DQB1*02:02  India West UCBB 0.03435,829
 824  A*26:01-B*44:03-C*04:01-DRB1*07:01-DQB1*02:02  India North UCBB 0.03425,849
 825  A*01:01-B*44:03-C*02:02-DRB1*07:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.03421,463
 826  A*02:01-B*44:02-C*07:04-DRB1*07:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.03421,463
 827  A*03:01-B*44:03-C*04:01-DRB1*07:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.03421,463
 828  A*23:01-B*44:02-C*05:01-DRB1*07:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.03421,463
 829  A*23:01-B*44:03-C*16:01-DRB1*07:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.03421,463
 830  A*31:01-B*44:03-C*04:01-DRB1*07:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.03421,463
 831  A*66:01-B*44:03-C*16:01-DRB1*07:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.03421,463
 832  A*68:01-B*44:02-C*02:02-DRB1*07:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.03421,463
 833  A*02:01-B*44:02-C*05:09-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 834  A*02:01-B*44:03-C*02:02-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 835  A*02:05-B*44:03-C*04:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 836  A*03:01-B*44:03-C*02:02-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 837  A*03:01-B*44:03-C*04:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 838  A*11:01-B*44:03-C*01:02-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 839  A*23:01-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 840  A*23:01-B*44:130-C*04:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 841  A*26:01-B*44:02-C*05:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 842  A*26:08-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 843  A*29:02-B*44:03-C*02:02-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 844  A*32:01-B*44:03-C*02:02-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 845  A*33:03-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 846  A*68:01-B*44:02-C*05:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 847  A*68:01-B*44:03-C*05:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 848  A*68:02-B*44:03-C*16:01-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 849  A*23:01-B*44:03-C*04:01-DRB1*07:01-DQB1*02:01-DPB1*17:01  Germany DKMS - German donors 0.03333,456,066
 850  A*01:01:01:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02  Russia Nizhny Novgorod, Russians 0.03311,510
 851  A*02:01:01-B*44:03:01-C*04:01:01-DRB1*07:01:01-DQB1*02:02  Russia Nizhny Novgorod, Russians 0.03311,510
 852  A*03:01:01:01-B*44:03:01-C*07:01:01-DRB1*07:01:01-DQB1*02:02  Russia Nizhny Novgorod, Russians 0.03311,510
 853  A*11:01:01:01-B*44:02:01:01-C*05:01:01:02-DRB1*07:01:01-DQB1*02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 854  A*26:01-B*44:05:01-C*01:02:01-DRB1*07:01:01-DQB1*02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 855  A*31:01:02:01-B*44:03:02-C*12:03:01:01-DRB1*07:01:01-DQB1*02:02  Russia Nizhny Novgorod, Russians 0.03311,510
 856  A*01-B*44-C*03-DRB1*07-DQA1*02-DQB1*02  Spain, Castilla y Leon, Northwest, 0.03281,743
 857  A*01-B*44-C*15-DRB1*07-DQA1*02-DQB1*02  Spain, Castilla y Leon, Northwest, 0.03281,743
 858  A*01-B*44-C*16-DRB1*07-DQA1*01-DQB1*02  Spain, Castilla y Leon, Northwest, 0.03281,743
 859  A*02-B*44-C*04-DRB1*07-DQA1*01-DQB1*02  Spain, Castilla y Leon, Northwest, 0.03281,743
 860  A*02-B*44-C*15-DRB1*07-DQA1*02-DQB1*02  Spain, Castilla y Leon, Northwest, 0.03281,743
 861  A*23-B*44-C*04-DRB1*07-DQA1*01-DQB1*02  Spain, Castilla y Leon, Northwest, 0.03281,743
 862  A*31-B*44-C*04-DRB1*07-DQA1*02-DQB1*02  Spain, Castilla y Leon, Northwest, 0.03281,743
 863  A*31-B*44-C*16-DRB1*07-DQA1*05-DQB1*02  Spain, Castilla y Leon, Northwest, 0.03281,743
 864  A*68-B*44-C*07-DRB1*07-DQA1*02-DQB1*02  Spain, Castilla y Leon, Northwest, 0.03281,743
 865  A*02:01-B*44:03-C*04:01-DRB1*07:01-DQB1*02:01-DPB1*14:01  Germany DKMS - German donors 0.03283,456,066
 866  A*68:01-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India South UCBB 0.032511,446
 867  A*24:07-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India Central UCBB 0.03214,204
 868  A*03:01-B*44:02-C*07:04-DRB1*07:01-DQB1*02:01  Germany DKMS - Turkey minority 0.03104,856
 869  A*02-B*44-C*04-DRB1*07-DQB1*02-DPB1*01  Norway ethnic Norwegians 0.03004,510
 870  A*25-B*44-C*16-DRB1*07-DQB1*02-DPB1*01  Norway ethnic Norwegians 0.03004,510
 871  A*31-B*44-C*04-DRB1*07-DQB1*02-DPB1*02  Norway ethnic Norwegians 0.03004,510
 872  A*33:03-B*44:03-C*07:01-DRB1*07:01-DQA1*02:01-DQB1*02:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 873  A*68-B*44-C*16-DRB1*07-DQB1*02-DPB1*11  Norway ethnic Norwegians 0.03004,510
 874  A*23:01:01-B*44:03:01-C*04:01:01-DRB1*07:01:01-DQB1*02:02:01  China Zhejiang Han 0.02881,734
 875  A*26:01:01-B*44:03:01-C*01:02:01-DRB1*07:01:01-DQB1*02:02:01  China Zhejiang Han 0.02881,734
 876  A*31:01-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India Central UCBB 0.02864,204
 877  A*11:01:01-B*44:03:01-C*04:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.028223,595
 878  A*23:01-B*44:03-C*04:01-DRB1*07:01-DQB1*02:01-DPB1*03:01  Germany DKMS - German donors 0.02803,456,066
 879  A*01:01:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.028023,595
 880  A*24:02-B*44:03-C*04:01-DRB1*07:01-DQB1*02:02  India South UCBB 0.027611,446
 881  A*23:01-B*44:03-C*04:01-DRB1*07:01-DQB1*02:01-DPB1*13:01  Germany DKMS - German donors 0.02673,456,066
 882  A*32:01-B*44:02-C*05:01-DRB1*07:01-DQB1*02:02  India North UCBB 0.02635,849
 883  A*32:01-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India Central UCBB 0.02624,204
 884  A*11:01-B*44:03-C*07:01-DRB1*07:01-DQB1*02:01  Germany DKMS - Turkey minority 0.02604,856
 885  A*11:01-B*44:03-C*15:02-DRB1*07:01-DQB1*02:02  India West UCBB 0.02575,829
 886  A*11:01-B*44:03-C*14:02-DRB1*07:01-DQB1*02:02  India North UCBB 0.02565,849
 887  A*01-B*44-DRB1*07-DQB1*02  Mexico Puebla, Puebla city 0.02511,994
 888  A*66-B*44-DRB1*07-DQB1*02  Mexico Puebla, Puebla city 0.02511,994
 889  A*68-B*44-DRB1*07-DQB1*02  Mexico Puebla, Puebla city 0.02511,994
 890  A*01:01-B*44:03-C*04:01-DRB1*07:01-DQB1*02:02  India Central UCBB 0.02504,204
 891  A*24:03-B*44:03-C*07:01-DRB1*07:01-DQB1*02:01  India Tamil Nadu 0.02482,492
 892  A*01:01-B*44:03-C*07:01-DRB1*07:01-DQB1*02:01  Germany DKMS - Turkey minority 0.02404,856
 893  A*01:01-B*44:03-C*06:02-DRB1*07:01-DQB1*02:02  India Central UCBB 0.02384,204
 894  A*02:11-B*44:03-C*05:01-DRB1*07:01-DQB1*02:02  India Central UCBB 0.02384,204
 895  A*11:01-B*44:03-C*07:06-DRB1*07:01-DQB1*02:110  India Central UCBB 0.02384,204
 896  A*31:01:02-B*44:03:01-C*04:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.023723,595
 897  A*31:01-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India East UCBB 0.02362,403
 898  A*02:01-B*44:03-C*16:01-DRB1*07:01-DQB1*02:01-DPB1*01:01  Germany DKMS - German donors 0.02353,456,066
 899  A*24:02:01-B*44:03:01-C*16:01:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.023423,595
 900  A*02:01-B*44:03-C*07:06-DRB1*07:01-DQB1*02:02  India West UCBB 0.02325,829

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 1,218) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 13  


   

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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