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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Displaying 1 to 100 (from 115) records   Pages: 1 2 of 2  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*02:01:01/02:01:09-B*40:05-C*03:04-DRB1*08:02:01-DQB1*04:02-DPB1*04:02  Mexico Chihuahua Tarahumara 5.100044
 2  A*02-B*40-DRB1*08:02-DQB1*04:02  Bolivia Quechua 5.070069
 3  A*24:02:01-B*40:02-C*03:04-DRB1*08:02:01-DQB1*04:02-DPB1*04:02  Mexico Chihuahua Tarahumara 3.400044
 4  A*24:02:01-B*40:02:01-C*03:05-DRB1*08:02:01-DQB1*04:02:01  Costa Rica Central Valley Mestizo (G) 2.0362221
 5  A*68-B*40-DRB1*08:02-DQB1*04:02  Mexico San Vicente Tancuayalab Teenek/Huastecos 1.890053
 6  A*24-B*40-DRB1*08:02-DQB1*04:02  Bolivia La Paz Aymaras 1.724087
 7  A*24-B*40-DRB1*08:02-DQB1*04:02  Mexico Sinaloa Capomos Mayo Yoremes 1.666760
 8  B*40:02-C*03:04-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 1.0490143
 9  A*24:02-B*40:02-C*01:06-DRB1*08:02-DQB1*04:02  Colombia North Wiwa El Encanto 0.961552
 10  A*31:12-B*40:02-C*01:02-DRB1*08:02-DQB1*04:02  Colombia North Wiwa El Encanto 0.961552
 11  A*31-B*40-DRB1*08:02-DQB1*04:02  Mexico San Vicente Tancuayalab Teenek/Huastecos 0.940053
 12  A*68:01-B*40:09-DRB1*08:02-DQB1*04:02  Chile Mapuche 0.770066
 13  A*31:01-B*40:02-C*03:04-DRB1*08:02-DQA1*04:01-DQB1*04:02  Mexico Tixcacaltuyub Maya 0.746367
 14  A*02:01-B*40:02-C*03:04-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.6993143
 15  B*40:11-C*03:04-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.6993143
 16  A*02:01:01-B*40:02:01-C*03:02:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 17  A*24:02:01-B*40:02:01-C*08:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 18  A*31:01:02-B*40:02:01-C*03:02:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 19  A*02:01-B*40:02-C*03:04-DRB1*08:02-DQA1*04:01-DQB1*04:02  Brazil Puyanawa 0.6667150
 20  A*02:01-B*40:02-DRB1*08:02-DQB1*04:02  Mexico Veracruz Xalapa 0.595284
 21  A*69-B*40-DRB1*08:02-DQB1*04:02  Bolivia La Paz Aymaras 0.575087
 22  A*02:01-B*40:02-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 23  A*26:01-B*40:02-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 24  A*31:01-B*40:01-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 25  A*68:01:02-B*40:03-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uros 0.4800105
 26  A*02:01-B*40:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 0.4545330
 27  B*40:02-C*03:04-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.4300234
 28  A*02:06-B*40:02-C*03:04-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.4274234
 29  A*02:06-B*40:02-C*03:05-DRB1*08:02-DQB1*04:02-DPB1*14:01  Panama 0.3800462
 30  A*24:02-B*40:02-C*03:04-DRB1*08:02-DQB1*04:02-DPB1*04:02  Panama 0.3800462
 31  A*02:22-B*40:02-C*03:04-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.37511,463
 32  A*01:01-B*40:11-C*03:04-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 33  A*02:02-B*40:02-C*03:04-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 34  A*68:01-B*40:11-C*03:04-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 35  A*24:02-B*40:02-C*03:05-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.25631,463
 36  A*02:06-B*40:02-C*03:06-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.23401,999
 37  A*02:01-B*40:11-C*03:04-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218
 38  A*02:06-B*40:02-C*15:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:01  Mexico Chiapas Lacandon Mayans 0.2294218
 39  A*02:06-B*40:02-C*15:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218
 40  A*24:02-B*40:11-C*03:04-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218
 41  A*31:01-B*40:02-C*03:05-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218
 42  A*68:01-B*40:08-C*03:04-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218
 43  A*02:01:01-B*40:02:01-C*03:05-DRB1*08:02:01-DQB1*04:02:01  Costa Rica Central Valley Mestizo (G) 0.2262221
 44  A*02:06:01-B*40:02:01-C*03:05-DRB1*08:02:01-DQB1*04:02:01  Costa Rica Central Valley Mestizo (G) 0.2262221
 45  A*33:01:01-B*40:02:01-C*03:05-DRB1*08:02:01-DQB1*04:02:01  Costa Rica Central Valley Mestizo (G) 0.2262221
 46  A*68:01:02-B*40:02:01-C*03:05-DRB1*08:02:01-DQB1*04:02:01  Costa Rica Central Valley Mestizo (G) 0.2262221
 47  A*02:06-B*40:27-C*03:04-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPB1*04:02  Nicaragua Managua 0.2165339
 48  A*68:03-B*40:02-C*03:05-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPB1*02:01  Nicaragua Managua 0.2165339
 49  A*24:02-B*40:02-C*03:04-DRB1*08:02-DQB1*04:02-DPB1*03:01  Panama 0.1900462
 50  A*68:01-B*40:02-C*03:04-DRB1*08:02-DQB1*04:02-DPB1*14:01  Panama 0.1900462
 51  A*24:02-B*40:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 0.1515330
 52  A*26:01-B*40:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 0.1515330
 53  A*29:01-B*40:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 0.1515330
 54  A*31:01-B*40:02-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 0.1515330
 55  A*68:01-B*40:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 0.1515330
 56  A*02:13-B*40:02-C*03:04-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.14651,463
 57  A*24:02-B*40:02-C*03:06-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.14001,999
 58  A*24:14-B*40:02-C*03:04-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.12501,463
 59  A*02:01-B*40:02-C*04:01-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.10221,463
 60  A*02:06-B*40:02-C*15:02-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.09401,999
 61  A*24:02-B*40:02-C*03:04-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.09401,999
 62  A*02:06-B*40:02-C*03:04-DRB1*08:02-DQB1*04:02  USA Asian pop 2 0.08901,772
 63  A*24:02-B*40:02-C*03:04-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.08011,463
 64  A*11:01-B*40:06-C*07:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPB1*20:01  Sri Lanka Colombo 0.0700714
 65  A*24:02-B*40:01-C*03:04-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.07003,078
 66  A*24:02-B*40:02-C*01:02-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.06891,463
 67  A*02:22-B*40:02-C*03:05-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.06841,463
 68  A*68:01-B*40:02-C*03:04-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.06841,463
 69  A*68:01-B*40:02-C*03:05-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.05791,463
 70  A*32:01-B*40:02-C*03:04-DRB1*08:02-DQB1*04:02-DPB1*04:02  Russia Karelia 0.05651,075
 71  A*26:01-B*40:02-C*03:04-DRB1*08:02-DQB1*04:02-DPB1*04:02  Russia Karelia 0.05651,075
 72  A*31:01-B*40:02-C*03:04-DRB1*08:02-DQB1*04:02-DPB1*04:02  Russia Karelia 0.05561,075
 73  A*02:22-B*40:02-C*01:10-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.05131,463
 74  A*02:01-B*40:08-C*03:04-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.04701,999
 75  A*24:02-B*40:05-C*03:04-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.04701,999
 76  A*31:01-B*40:02-C*01:10-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.04701,999
 77  A*68:01-B*40:20-C*03:04-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.04701,999
 78  A*31:01-B*40:02-C*01:10-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.04121,463
 79  A*24:02-B*40:02-C*01:10-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.03801,463
 80  A*02:01-B*40:02-C*03:06-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.03421,463
 81  A*02:11-B*40:02-C*03:05-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.03421,463
 82  A*02:11-B*40:04-C*01:02-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.03421,463
 83  A*02:13-B*40:11-C*03:04-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.03421,463
 84  A*02:22-B*40:02-C*04:01-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.03421,463
 85  A*03:01-B*40:02-C*01:10-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.03421,463
 86  A*31:01-B*40:02-C*04:01-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.03421,463
 87  A*32:01-B*40:02-C*02:02-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.03421,463
 88  A*02:22-B*40:02-C*03:04-DRB1*08:02-DQB1*04:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 89  A*02:17-B*40:02-C*03:04-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.03361,463
 90  A*02:01-B*40:02-C*03:04-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Japan pop 17 0.03003,078
 91  A*02:01-B*40:06-C*03:03-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 92  A*02:06-B*40:02-C*03:03-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 93  A*24:02-B*40:02-C*15:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*03:01  Japan pop 17 0.03003,078
 94  A*26:03-B*40:01-C*03:04-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 95  A*26:03-B*40:02-C*03:04-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 96  A*02:01:01-B*40:01:02-C*15:02:01-DRB1*08:02:01-DQB1*04:02:01  China Zhejiang Han 0.02881,734
 97  A*02:06:01-B*40:06:01-C*03:04:01-DRB1*08:02:01-DQB1*04:02:01  China Zhejiang Han 0.02881,734
 98  A*11:01:01-B*40:01:02-C*07:02:01-DRB1*08:02:01-DQB1*04:02:01  China Zhejiang Han 0.02881,734
 99  A*11:01:01-B*40:06:01-C*08:01:01-DRB1*08:02:01-DQB1*04:02:01  China Zhejiang Han 0.02881,734
 100  A*02:06-B*40:06-C*15:02-DRB1*08:02-DQB1*04:02  India Tamil Nadu 0.02012,492

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 1 to 100 (from 115) records   Pages: 1 2 of 2  


   

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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