Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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A B C DRB1 DPA1 DPB1 DQA1 DQB1

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Displaying 1 to 100 (from 113) records   Pages: 1 2 of 2  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  B*35:01-DRB1*08:02  USA Alaska Yupik 7.7000252
 2  A*24:02-B*35:01-DRB1*08:02-DQB1*04:02  USA Alaska Yupik 6.0000252
 3  A*02:01:01/02:01:09-B*35:01/35:02/35:03-C*03:04-DRB1*08:02:01-DQB1*04:02-DPB1*04:02  Mexico Chihuahua Tarahumara 3.400044
 4  A*02:01-B*35:01-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uro 3.3000105
 5  A*02:01-B*35:01-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uros 3.2700105
 6  A*02:06-B*35:01-DRB1*08:02-DQB1*04:02  USA Alaska Yupik 3.1000252
 7  A*02:01-B*35:01-DRB1*08:02  Mexico Oaxaca Mixtec 3.0000103
 8  A*31:01:02-B*35:01:01-C*04:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 2.777872
 9  A*02:01-B*35:01-DRB1*08:02-DQB1*04:02  Mexico Veracruz Xalapa 2.381084
 10  A*02:04-B*35:01:01-C*04:01:01-DRB1*08:02:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*04:02:01  Brazil Barra Mansa Rio State Black 2.381073
 11  A*02:01-B*35:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 1.9697330
 12  B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 1.3986143
 13  A*02:01:01-B*35:01:01-C*04:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 1.388972
 14  A*68:01:01-B*35:01:01-C*04:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 1.388972
 15  A*02:01-B*35:01-C*07:02-DRB1*08:02-DQA1*04:01-DQB1*04:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 16  A*02:06-B*35:01-C*04:01-DRB1*08:02-DQA1*04:01-DQB1*04:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 17  A*24:02:01-B*35:01:01-C*04:01:01-DRB1*08:02:01-DQB1*04:02:01  Costa Rica Central Valley Mestizo (G) 0.9050221
 18  A*24:02:01-B*35:01:01-C*04:01:01-DRB1*08:02:01  Costa Rica Amerindians (G) 0.8159125
 19  A*24:02-B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.6993143
 20  A*02:01:01-B*35:01:01-C*03:02:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 21  A*02:01:01-B*35:01:01-C*08:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 22  A*24:02:01-B*35:01:01-C*04:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 23  A*68:03:01-B*35:01:01-C*04:01:01-DRB1*08:02:01-DQB1*04:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 24  B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.6400234
 25  A*24:02-B*35:01-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uros 0.6300105
 26  A*24:02-B*35:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 0.6061330
 27  A*24:02-B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  USA NMDP Alaska Native or Aleut 0.58981,376
 28  A*02:01-B*35:01-DRB1*08:02-DQB1*04:03  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 29  A*24:02-B*35:01-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 30  A*26:01-B*35:01-DRB1*08:02-DQB1*04:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 31  A*02:01-B*35:01-DRB1*08:02  Mexico Oaxaca Jamiltepec Mixtec 0.520096
 32  A*02:06:01-B*35:01:01-C*04:01:01-DRB1*08:02:01  Costa Rica Guanacaste Mestizo (G) 0.4545110
 33  A*02:01-B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 0.4274234
 34  A*68:01-B*35:01-C*04:01-DRB1*08:02-DQB1*04:02-DPB1*04:02  Panama 0.3800462
 35  A*02:01-B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 36  A*31:01-B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 37  A*68:01-B*35:01-C*04:01-DRB1*08:02-DQA1*05:01-DQB1*02:01-DPB1*04:02  USA San Diego 0.2600496
 38  A*02:01-B*35:01-C*04:01-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218
 39  A*24:02-B*35:01-C*04:01-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218
 40  A*31:01-B*35:01-C*04:01-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*35:01-C*07:02-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*35:01-C*07:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218
 43  A*02:06:01-B*35:01:01-C*07:02:01-DRB1*08:02:01-DQB1*04:02:01  Costa Rica Central Valley Mestizo (G) 0.2262221
 44  A*02:01-B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  USA NMDP American Indian South or Central America 0.22545,926
 45  A*02:01-B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.18701,999
 46  A*02:06-B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  USA NMDP Alaska Native or Aleut 0.17251,376
 47  A*24:02-B*35:01-C*03:03-DRB1*08:02-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.16003,078
 48  A*24:02-B*35:01-C*03:03-DRB1*08:02  Japan pop 16 0.156018,604
 49  A*26:01-B*35:01-C*03:03-DRB1*08:02  Japan pop 16 0.156018,604
 50  A*02:02-B*35:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 0.1515330
 51  A*23:01-B*35:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 0.1515330
 52  A*31:01-B*35:01-DRB1*08:02-DQB1*04:02  Mexico Mexico City Tlalpan 0.1515330
 53  A*68:01-B*35:01-DRB1*08:02-DQB1*03:01  Mexico Mexico City Tlalpan 0.1515330
 54  A*68:01-B*35:01-C*03:04-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.13671,463
 55  A*31:01-B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.09961,463
 56  A*02:01-B*35:01-C*03:03-DRB1*08:02  Japan pop 16 0.094018,604
 57  A*24:02-B*35:01-C*03:04-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.09401,999
 58  A*26:03-B*35:01-C*03:03-DRB1*08:02  Japan pop 16 0.083018,604
 59  A*31:01-B*35:01-C*03:03-DRB1*08:02  Japan pop 16 0.073018,604
 60  A*02:01-B*35:01-C*03:04-DRB1*08:02-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.07003,078
 61  A*26:01-B*35:01-C*03:03-DRB1*08:02-DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.07003,078
 62  A*26:01-B*35:01-C*03:03-DRB1*08:02-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.07003,078
 63  A*31:01-B*35:01-C*03:03-DRB1*08:02-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.07003,078
 64  A*33:03-B*35:01-C*03:03-DRB1*08:02-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.07003,078
 65  A*24:14-B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.06841,463
 66  A*02:03-B*35:01-C*04:01-DRB1*08:02-DQB1*05:03  Malaysia Peninsular Malay 0.0526951
 67  A*02:01-B*35:01-C*03:04-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.04701,999
 68  A*02:06-B*35:01-C*04:01-DRB1*08:02-DQB1*03:01  USA Hispanic pop 2 0.04701,999
 69  A*25:01-B*35:01-C*03:04-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.04701,999
 70  A*68:01-B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 0.04701,999
 71  A*26:01-B*35:01-C*03:03-DRB1*08:02-DQB1*03:02  USA Asian pop 2 0.04401,772
 72  A*02:01-B*35:01-C*08:01-DRB1*08:02  Japan pop 16 0.037018,604
 73  A*02:06-B*35:01-C*03:03-DRB1*08:02  Japan pop 16 0.037018,604
 74  A*03:01-B*35:01-C*04:01-DRB1*08:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.03421,463
 75  A*02:01-B*35:01-C*03:03-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 76  A*02:01-B*35:01-C*08:01-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Japan pop 17 0.03003,078
 77  A*02:01-B*35:01-C*08:01-DRB1*08:02-DQA1*06:01-DQB1*04:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 78  A*02:06-B*35:01-C*03:03-DRB1*08:02-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 79  A*02:06-B*35:01-C*03:03-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 80  A*11:01-B*35:01-C*03:03-DRB1*08:02-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 81  A*24:02-B*35:01-C*03:03-DRB1*08:02-DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 82  A*24:02-B*35:01-C*03:03-DRB1*08:02-DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*03:01  Japan pop 17 0.03003,078
 83  A*24:02-B*35:01-C*03:03-DRB1*08:02-DQA1*04:01-DQB1*03:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 84  A*26:01-B*35:01-C*03:03-DRB1*08:02-DQA1*03:01-DQB1*03:02-DPA1*02:01-DPB1*05:01  Japan pop 17 0.03003,078
 85  A*26:01-B*35:01-C*03:03-DRB1*08:02-DQA1*03:01-DQB1*03:02-DPA1*02:01-DPB1*09:01  Japan pop 17 0.03003,078
 86  A*26:02-B*35:01-C*03:03-DRB1*08:02-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 87  A*26:03-B*35:01-C*03:03-DRB1*08:02-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 88  A*26:03-B*35:01-C*03:03-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*02:01-DPB1*13:01  Japan pop 17 0.03003,078
 89  A*31:01-B*35:01-C*03:03-DRB1*08:02-DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*04:02  Japan pop 17 0.03003,078
 90  A*31:01:02-B*35:01:01-C*04:01:01-DRB1*08:02:01-DPB1*02:01:02  Hong Kong Chinese HKBMDR HLA 11 loci 0.02855,266
 91  A*24:02:01-B*35:01:01-C*14:02:01-DRB1*08:02:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.01905,266
 92  A*11:01-B*35:01-C*03:03-DRB1*08:02  Japan pop 16 0.016018,604
 93  A*24:02-B*35:01-C*04:01-DRB1*08:02  Japan pop 16 0.016018,604
 94  A*24:02-B*35:01-C*08:01-DRB1*08:02  Japan pop 16 0.016018,604
 95  A*24:02-B*35:01-C*14:02-DRB1*08:02  Hong Kong Chinese BMDR 0.01327,595
 96  A*02:01-B*35:01-C*03:03-DRB1*08:02-DQB1*04:02  USA Asian pop 2 0.01101,772
 97  A*26:01-B*35:01-C*03:03-DRB1*08:02-DQB1*04:02  USA Asian pop 2 0.01101,772
 98  A*26:02-B*35:01-C*03:03-DRB1*08:02  Japan pop 16 0.010018,604
 99  A*33:03-B*35:01-C*03:03-DRB1*08:02  Japan pop 16 0.010018,604
 100  A*02:11-B*35:01-DRB1*08:02  Israel USA Jews 0.00836,058

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 113) 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.
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