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 1 to 77 (from 77) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*68:01-B*39:09-DRB1*08:02-DQB1*04:02  Chile Mapuche 6.150066
 2  A*02-B*39-DRB1*08:02-DQB1*04:02  Bolivia La Paz Aymaras 3.426087
 3  A*68:01-B*39:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 1.5152330
 4  B*39:05-C*07:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 1.3986143
 5  A*31-B*39-DRB1*08:02-DQB1*04:02  Bolivia La Paz Aymaras 1.241087
 6  A*31:01-B*39:01-DRB1*08:02-DQB1*04:02  Mexico Veracruz Xalapa 1.190584
 7  B*39:05-C*07:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 1.0700234
 8  A*68:01-B*39:05-C*03:04-DRB1*08:02-DQA1*04:01-DQB1*04:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 9  A*02-B*39-DRB1*08:02-DQB1*04:02  Bolivia Quechua 0.860069
 10  A*02:01-B*39:01-DRB1*08:02-DQB1*04:02  Chile Mapuche 0.770066
 11  A*33:01-B*39:01-DRB1*08:02-DQB1*04:02  Chile Mapuche 0.770066
 12  A*68:03-B*39:05-C*07:02-DRB1*08:02-DQA1*04:01-DQB1*04:02  Mexico Tixcacaltuyub Maya 0.746367
 13  A*01:01:01-B*39:01:01-C*07:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 14  A*02:01:01-B*39:01:01-C*07:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 15  A*24:02:01-B*39:01:01-C*07:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 16  A*24:02:01-B*39:01:01-C*08:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 17  A*31:01:02-B*39:06:01-C*07:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 18  A*68:01:01-B*39:01:01-C*07:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 19  A*68:01:01-B*39:02:01-C*07:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 20  A*68-B*39-DRB1*08:02-DQB1*04:02  Bolivia La Paz Aymaras 0.692087
 21  A*68:01-B*39:01-DRB1*08:02-DQB1*04:02  Mexico Veracruz Xalapa 0.595284
 22  A*36-B*39:01-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 23  A*24:02-B*39:05-C*07:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.4587218
 24  A*68:03-B*39:05-C*07:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.4587218
 25  A*24:02-B*39:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 0.4545330
 26  A*68:01:02-B*39:08-C*07:02:01-DRB1*08:02:01-DQB1*04:02:01  Costa Rica Central Valley Mestizo (G) 0.4525221
 27  B*39:01-C*07:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.4300234
 28  B*39:02-C*07:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.4300234
 29  A*24:02-B*39:05-C*07:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.4274234
 30  A*68:01-B*39:01-C*07:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.4274234
 31  A*01:01-B*39:05-C*07:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 32  A*02:01-B*39:05-C*07:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 33  A*02:06-B*39:05-C*07:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 34  A*24:02-B*39:06-C*07:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 35  A*68:01-B*39:01-C*07:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 36  A*68:03-B*39:05-C*07:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 37  A*68:03-B*39:08-C*07:17-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 38  B*39:01-C*07:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 39  B*39:06-C*07:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 40  B*39:08-C*07:17-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 41  A*02:01-B*39:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 0.3030330
 42  A*02:22-B*39:05-C*07:02-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.27341,463
 43  A*02:06-B*39:08-C*07:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218
 44  A*31:01-B*39:05-C*04:01-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218
 45  A*68:05-B*39:02-C*03:04-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*02:01  Mexico Chiapas Lacandon Mayans 0.2294218
 46  A*68:05-B*39:05-C*07:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218
 47  A*68:03-B*39:08-C*07:17-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPB1*03:01  Nicaragua Managua 0.2165339
 48  A*02:06-B*39:05-C*07:02-DRB1*08:02-DQB1*04:02  USA NMDP Hawaiian or other Pacific Islander 0.211111,499
 49  A*68:01-B*39:05-C*07:02-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.15691,463
 50  A*02-B*39-DRB1*08:02-DQA1*04:01-DQB1*04:02  Brazil Paraná Caucasian 0.1560641
 51  A*31-B*39-DRB1*08:02-DQA1*04:01-DQB1*04:02  Brazil Paraná Caucasian 0.1560641
 52  A*68:05-B*39:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 0.1515330
 53  A*02:01-B*39:05-C*07:02-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.10781,463
 54  A*24:02-B*39:06-C*07:02-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.09501,999
 55  A*11-B*39-DRB1*08:02-DQA1*04:01-DQB1*04:02  Brazil Paraná Caucasian 0.0780641
 56  A*24-B*39-DRB1*08:02-DQA1*04:01-DQB1*04:02  Brazil Paraná Caucasian 0.0780641
 57  A*29-B*39-DRB1*08:02-DQA1*04:01-DQB1*04:02  Brazil Paraná Caucasian 0.0780641
 58  A*02:06-B*39:01-C*07:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.07003,078
 59  A*02:06-B*39:01-C*07:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.07003,078
 60  A*31:01-B*39:03-C*07:02-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.04701,999
 61  A*24:03-B*39:05-C*07:02-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.03801,463
 62  A*02:01-B*39:11-C*07:02-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.03651,463
 63  A*24:14-B*39:08-C*07:02-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.03421,463
 64  A*03:01-B*39:05-C*07:02-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.03271,463
 65  A*02:06-B*39:01-C*07:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*03:01  Japan pop 17 0.03003,078
 66  A*02:06-B*39:01-C*07:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*06:01  Japan pop 17 0.03003,078
 67  A*02:28-B*39:01-C*07:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 68  A*26:01-B*39:01-C*07:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*02:01-DPB1*05:01  Japan pop 17 0.03003,078
 69  A*31:01-B*39:01-C*07:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 70  A*26:01:01-B*39:01:01-C*07:02:01-DRB1*08:02:01-DQB1*04:02:01  China Zhejiang Han 0.02881,734
 71  A*02:01-B*39:01-C*07:02-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.02301,999
 72  A*02:01-B*39:13-C*07:02-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.01201,999
 73  A*02:06-B*39:01-C*07:02-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.01201,999
 74  A*02:11-B*39:13-C*07:02-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.01201,999
 75  A*25:01-B*39:01-C*07:02-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.01201,999
 76  A*32:01:01-B*39:01:01-C*07:02:01-DRB1*08:02:01-DQB1*04:02:01  Poland BMR 0.006423,595
 77  A*03:01-B*39:01-C*12:03-DRB1*08:02-DQB1*04:02  India South UCBB 0.003111,446

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.

support@allelefrequencies.net

Valid XHTML 1.0 Transitional