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 : 
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Sample Size:      Sample Year:     Loci Tested: 
Displaying 1 to 74 (from 74) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*68-B*14:02-DRB1*13-DQB1*03:01  Mexico Jalisco, Tlajomulco 1.666730
 2  A*30-B*14:02-DRB1*13-DQB1*03:01  Mexico Colima, Colima city 0.819761
 3  A*24-B*14:02-DRB1*13-DQB1*03:01  Mexico Oaxaca, Oaxaca city 0.6623151
 4  A*68-B*14:02-DRB1*13-DQB1*03:01  Mexico Morelos, Cuernavaca 0.609882
 5  A*68:02-B*14:02-C*08:02-DRB1*13:03-DQA1*05:01-DQB1*03:01-DPB1*04:01  USA San Diego 0.5210496
 6  A*02-B*14:02-DRB1*13-DQB1*03:01  Mexico Sonora, Hermosillo 0.505199
 7  A*74-B*14:02-DRB1*13-DQB1*03:01  Mexico Zacatecas, Fresnillo 0.4762103
 8  A*68:02-B*14:02-C*07:01-E*01:01:01-F*01:01:01-G*01:01-DRB1*13:03:01-DQA1*05:05-DQB1*03:01  Portugal Azores Terceira Island 0.4386130
 9  A*68:02-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01  Mexico Mexico City Mestizo population 0.3497143
 10  B*14:02-C*08:02-DRB1*13:03-DQB1*03:01  Mexico Mexico City Mestizo population 0.3497143
 11  A*11:01:01-B*14:02:01-C*08:02:01-DRB1*13:03:01-DQA1*05:05:01-DQB1*03:01-DPA1*02:01:01-DPB1*02:01:02  Russia Belgorod region 0.3268153
 12  A*68-B*14:02-DRB1*13-DQB1*03:01  Mexico Mexico City Center 0.3247152
 13  A*68:02-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01-DPB1*02:01  Russia Karelia 0.28231,075
 14  A*33-B*14:02-DRB1*13-DQB1*03:01  Mexico Coahuila Rural 0.2294216
 15  A*33-B*14:02-DRB1*13-DQB1*03:01  Ecuador Coast Mixed Ancestry 0.2101238
 16  A*68:02-B*14:02:01-C*08:02-DRB1*13:03:01-DQB1*03:01  England North West 0.2000298
 17  A*68:02:01:01-B*14:02:01-C*08:02:01-DRB1*13:03:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.19871,510
 18  A*24:02:01-B*14:02:01-C*08:02:01-DRB1*13:02:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 19  A*68:02-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01  USA NMDP American Indian South or Central America 0.18415,926
 20  A*68:02:01-B*14:02:01-C*08:02:01-DRB1*13:03:01-DQB1*03:01:01  Poland BMR 0.175823,595
 21  A*68:02-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01-DPB1*02:01  Germany DKMS - German donors 0.17433,456,066
 22  A*68-B*14:02-DRB1*13-DQB1*03:01  Mexico Durango Rural 0.1529326
 23  A*03-B*14:02-DRB1*13-DQB1*03:01  Mexico Michoacan Rural 0.1433348
 24  A*68-B*14:02-DRB1*13-DQB1*03:01  Mexico Michoacan Rural 0.1433348
 25  A*68:02-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01  Germany DKMS - Italy minority 0.12901,159
 26  A*68-B*14:02-DRB1*13-DQB1*03:01  Mexico Puebla Rural 0.1199833
 27  A*24:02-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.10304,335
 28  A*33:01-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01  USA Hispanic pop 2 0.09401,999
 29  A*02-B*14:02-DRB1*13-DQB1*03:01  Mexico Veracruz Rural 0.0924539
 30  A*68-B*14:02-DRB1*13-DQB1*03:01  Mexico Jalisco Rural 0.0853585
 31  A*68:02-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01  Colombia Bogotá Cord Blood 0.06841,463
 32  A*68:02-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01-DPB1*04:01  Germany DKMS - German donors 0.06833,456,066
 33  A*02-B*14:02-DRB1*13-DQB1*03:01  Mexico Mexico City North 0.0664751
 34  A*68-B*14:02-DRB1*13-DQB1*03:01  Mexico Mexico City North 0.0664751
 35  A*24-B*14:02-DRB1*13-DQB1*03:01  Ecuador Andes Mixed Ancestry 0.0607824
 36  A*68-B*14:02-DRB1*13-DQB1*03:01  Mexico Tlaxcala Rural 0.0602830
 37  A*24-B*14:02-DRB1*13-DQB1*03:01  Mexico Puebla Rural 0.0600833
 38  A*68:02-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01-DPB1*09:01  Russia Karelia 0.05651,075
 39  A*68:02-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01-DPB1*05:01  Russia Karelia 0.05651,075
 40  A*02:01-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01-DPB1*02:01  Russia Karelia 0.05641,075
 41  A*33:01-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01-DPB1*14:01  Russia Karelia 0.05571,075
 42  A*02:01-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01  USA Hispanic pop 2 0.04701,999
 43  A*03:01:01-B*14:02:01-C*08:02:01-DRB1*13:03:01-DQB1*03:01:01  Poland BMR 0.043123,595
 44  A*24-B*14:02-DRB1*13-DQB1*03:01  Ecuador Mixed Ancestry 0.04261,173
 45  A*33-B*14:02-DRB1*13-DQB1*03:01  Ecuador Mixed Ancestry 0.04261,173
 46  A*01-B*14:02-DRB1*13-DQB1*03:01  Mexico Jalisco, Guadalajara city 0.04191,189
 47  A*33-B*14:02-DRB1*13-DQB1*03:01  Mexico Jalisco, Guadalajara city 0.04191,189
 48  A*68-B*14:02-DRB1*13-DQB1*03:01  Mexico Jalisco, Guadalajara city 0.04191,189
 49  A*02:05-B*14:02-C*07:04-DRB1*13:02-DQB1*03:01  Colombia Bogotá Cord Blood 0.03421,463
 50  A*24:02-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01  Colombia Bogotá Cord Blood 0.03421,463
 51  A*02:01-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 52  A*32:01-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 53  A*33:01-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 54  A*68:02-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 55  A*02:01:01:01-B*14:02:01-C*08:02:01-DRB1*13:03:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 56  A*03:01:01-B*14:02:01-C*08:02:01-DRB1*13:03:01-DQB1*03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 57  A*68:02-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01  Germany DKMS - Turkey minority 0.03104,856
 58  A*24-B*14:02-DRB1*13-DQB1*03:01  Mexico Puebla, Puebla city 0.02511,994
 59  A*24:02-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01  USA Hispanic pop 2 0.02301,999
 60  A*03:01-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01-DPB1*02:01  Germany DKMS - German donors 0.01243,456,066
 61  A*02:01-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01-DPB1*02:01  Germany DKMS - German donors 0.01143,456,066
 62  A*02:01:01-B*14:02:01-C*08:02:01-DRB1*13:03:01-DQB1*03:01:01  Poland BMR 0.011323,595
 63  A*68:02-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01-DPB1*03:01  Germany DKMS - German donors 0.01103,456,066
 64  A*03:01-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01  Germany DKMS - Turkey minority 0.01004,856
 65  A*32:01:01-B*14:02:01-C*08:02:01-DRB1*13:03:01-DQB1*03:01:01  Poland BMR 0.008523,595
 66  A*24:02:01-B*14:02:01-C*08:02:01-DRB1*13:03:01-DQB1*03:01:01  Poland BMR 0.004523,595
 67  A*01:01:01-B*14:02:01-C*08:02:01-DRB1*13:03:01-DQB1*03:01:01  Poland BMR 0.004523,595
 68  A*68:02-B*14:02-C*08:02-DRB1*13:03-DQB1*03:01  India South UCBB 0.004411,446
 69  A*29:02:01-B*14:02:01-C*08:02:01-DRB1*13:03:01-DQB1*03:01:01  Poland BMR 0.004223,595
 70  A*26:01:01-B*14:02:01-C*08:02:01-DRB1*13:03:01-DQB1*03:01:01  Poland BMR 0.002123,595
 71  A*30:01:01-B*14:02:01-C*05:01:01-DRB1*13:03:01-DQB1*03:01:01  Poland BMR 0.002123,595
 72  A*33:01:01-B*14:02:01-C*08:02:01-DRB1*13:02:01-DQB1*03:01:01  Poland BMR 0.002123,595
 73  A*68:02:01-B*14:02:01-C*08:02:01-DRB1*13:02:01-DQB1*03:01:01  Poland BMR 0.002123,595
 74  A*03:02:01-B*14:02:01-C*08:02:01-DRB1*13:03:01-DQB1*03:01:01  Poland BMR 0.002123,595

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).




   

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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