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 1 to 100 (from 40,342) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 404  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*02:01-G*01:01  Ecuador Amerindians 25.396863
 2  A*02:06-B*55:02-DRB1*12:01  New Zealand Maori with Full Ancestry 22.800046
 3  A*02:01-C*08:01  Philippines Ivatan 20.200050
 4  A*02:04-B*39:05-C*07:02-DRB1*04:11-DQA1*03:01:01-DQB1*03:02-DPA1*01-DPB1*04:02  Venezuela Sierra de Perija Yucpa 19.800073
 5  A*02:01-B*15:02  Philippines Ivatan 18.800050
 6  A*02:06-B*55:02-DRB1*12:01  New Zealand Maori with Admixed History 17.1429105
 7  A*02-B*35-DRB1*04:07-DQB1*03:02  Mexico Huasteca Region Teenek 15.500055
 8  A*02:07-B*46:01-C*01:02  China Southwest Dai 15.2000124
 9  A*02:01-B*35:12-DRB1*08:02  Mexico Oaxaca Mixe 15.000055
 10  A*02-B*35-DRB1*04:07-DQB1*03:02  Mexico San Vicente Tancuayalab Teenek/Huastecos 13.920053
 11  A*02:01-B*35:05-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uro 13.5000105
 12  A*02:01-B*35:05-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uros 13.4500105
 13  A*02-B*15:01-DRB1*07-DQB1*02  Mexico Tamaulipas, Ciudad Victoria 13.043523
 14  A*02:01-B*15:13-DRB1*12:02  Malaysia Kedah Kensiu 11.900021
 15  A*02:01-C*01:02  Taiwan Taroko 11.700055
 16  A*02:01-B*15:02-DRB1*12:02  Malaysia Mandailing 11.111127
 17  A*02-B*39-DRB1*04:07-DQA1*03-DQB1*03:02  Mexico Mazatecan 10.800089
 18  A*02:01-B*55:02  Taiwan Taroko 10.700055
 19  A*02-B*35-DRB1*04:07-DQB1*03:02  Guatemala Mayan 10.6000132
 20  A*02:07-B*46:01-C*01:02-DRB1*09:01  China Yunnan Province Han 10.5000101
 21  A*02-B*35-DRB1*08:02-DQB1*04:02  Bolivia La Paz Aymaras 10.448087
 22  A*02-B*35-DRB1*08:02-DQB1*04:02  Bolivia Quechua 10.050069
 23  A*02-B*35-DRB1*08-DQB1*04  Mexico Morelos, Cuernavaca 9.756182
 24  A*02-B*35-DRB1*04:07-DQA1*03-DQB1*03:02  Colombia Jaidukama 9.600039
 25  A*02:07-B*46:01  Hong Kong Chinese 9.4000569
 26  A*02:07-B*46:01  Taiwan Minnan pop 1 9.3000102
 27  A*02:03-B*07:05-DRB1*15:01  Malaysia Pahang Semai 9.210038
 28  A*02:07-C*01:02  Taiwan Minnan pop 1 9.2000102
 29  A*02-B*35-DRB1*08-DQB1*04  Mexico San Luis Potosi Rural 9.195487
 30  A*02-B*13-C*04-DRB1*12  Myanmar Kayin 9.091044
 31  A*02:06-B*39:02-DRB1*04:07  Mexico Oaxaca Mixe 9.000055
 32  A*02-B*39-DRB1*04-DQB1*03:02  Mexico Campeche, Campeche city 8.823534
 33  A*02-B*35-DRB1*04-DQB1*03:02  Mexico Tabasco Rural 8.8028142
 34  A*02-B*35-DRB1*04-DQB1*03:02  Mexico Mexico City South 8.653852
 35  A*02-C*07  Macedonia 8.5664286
 36  A*02-B*35-DRB1*08:02-DQB1*04:02  Guatemala Mayan 8.4000132
 37  A*02:01-B*44:02-C*05:01  Ireland Northern 8.30001,000
 38  A*02-B*39-DRB1*04-DQB1*03:02  Mexico Veracruz, Cordoba 8.035756
 39  A*02:01:01/02:01:09-B*40:05-C*03:04  Mexico Chihuahua Tarahumara 8.000044
 40  A*02:01-B*44:02  Ireland Northern 8.00001,000
 41  A*02-C*07  Venezuela Caracas Mestizo 8.000050
 42  A*02-B*35-C*12:03  Pakistan Kalash 7.900069
 43  A*02-B*35-DRB1*13  Pakistan Kalash 7.900069
 44  A*02:06-B*27:05  USA Alaska Yupik 7.8000252
 45  A*02-B*48-DRB1*04:03-DQB1*03:02  Peru Lamas City Lama 7.800083
 46  A*02-B*48-DRB1*08:04-DQB1*04:02  Peru Lamas City Lama 7.800083
 47  A*02-B*39-DRB1*04-DQB1*03:02  Mexico Queretaro, Queretaro city 7.777845
 48  A*02:07-B*46:01-C*01:02-DRB1*14:01  China Yunnan Hani 7.7000150
 49  A*02:01-B*48:01  Taiwan Taroko 7.500055
 50  A*02:03-B*15:13-DRB1*15:02  Malaysia Mandailing 7.407427
 51  A*02-B*35-DRB1*08-DQB1*04  Mexico Hidalgo Rural 7.407481
 52  A*02:01-C*08:01  Taiwan Taroko 7.400055
 53  A*02-B*35-DRB1*04:07-DQB1*03:02  Mexico Sinaloa Capomos Mayo Yoremes 7.323260
 54  A*02-B*18-C*07-DRB1*11-DQB1*03  Albanian Kosovo 7.3200120
 55  A*02:06-B*48:01  Taiwan Atayal 7.3000106
 56  A*02:07-B*46:01  Taiwan Hakka 7.300055
 57  A*02:07-C*01:02  Taiwan Hakka 7.300055
 58  A*02:01-B*44:02-C*05:01  Ireland South 7.2000250
 59  A*02:06-C*08:01  Taiwan Atayal 7.2000106
 60  A*02-B*51-C*14  Pakistan Kalash 7.200069
 61  A*02-B*51-DRB1*04  Pakistan Kalash 7.200069
 62  A*02:01-B*18:01-DRB1*09:01  Malaysia Kedah Kensiu 7.140021
 63  A*02:01-B*18:01-DRB1*15:01  Malaysia Kedah Kensiu 7.140021
 64  A*02:07-B*46:01  Singapore Chinese 7.1000149
 65  A*02:01-B*27:05-DRB1*08:01  Sweden Northern Sami 7.0000154
 66  A*02-DRB1*11  Macedonia 6.9930286
 67  A*02:06-B*55:02  Taiwan Bunun 6.9000101
 68  A*02:06-C*01:02  Taiwan Bunun 6.9000101
 69  A*02-B*18-C*07-DRB1*11  Macedonia MBMDR - Macedonian Muslims 6.819976
 70  A*02-B*39-DRB1*04-DQB1*03:02  Mexico Guanajuato, Guanajuato city 6.818222
 71  A*02:01-B*35:17-DRB1*08:02  Mexico Oaxaca Jamiltepec Mixtec 6.770096
 72  A*02:01-B*55:02  Taiwan Thao 6.700030
 73  A*02:01-C*01:02  Taiwan Thao 6.700030
 74  A*02:03:01-B*52:01:01-C*07:02:01-DRB1*14:04-DQB1*05:03:01-DPB1*04:02  China Yunnan Province Lisu 6.7000111
 75  A*02-B*13-DRB1*07  Russia South Ural Bashkir 6.7000146
 76  A*02-B*18-DRB1*11  Albania pop 2 6.6900432
 77  A*02-B*35-DRB1*04-DQB1*03:02  Guatemala, Guatemala City Mixed Ancestry 6.6900127
 78  A*02-B*35-DRB1*08-DQB1*04  Mexico Jalisco, Tlajomulco 6.666730
 79  A*02-B*39-DRB1*04-DQB1*03:02  Mexico Morelos Rural 6.666730
 80  A*02:01:01-B*44:02:01-C*05:01:01  England Blood Donors of Mixed Ethnicity 6.6142519
 81  A*02:07-B*46:01-C*01:02  China Canton Han 6.5000264
 82  A*02-B*40  Pakistan Mixed Sindhi 6.5000101
 83  A*02-B*35-DRB1*08-DQB1*04  Mexico Jalisco, Tlaquepaque 6.410339
 84  A*02:07-B*46:01-DRB1*14:01  China Yunnan Province Jinuo 6.4000109
 85  A*02:01-B*35:05-DRB1*04:03-DQB1*03:02  Peru Titikaka Lake Uros 6.3100105
 86  A*02:01-B*35:05-DRB1*04:03-DQB1*03:02  Peru Titikaka Lake Uro 6.3000105
 87  A*02:01-B*44-C*05:01  Spain Catalonia Girona 6.300088
 88  A*02-DRB1*16  Macedonia 6.2937286
 89  A*02-B*15-DRB1*16:02-DQB1*03:01  Colombia Wayu from Guajira Peninsula 6.250048
 90  A*02-B*35-DRB1*08-DQB1*04  Mexico Quintana Roo, Cancun 6.250048
 91  A*02-B*39-DRB1*04-DQB1*03:02  Mexico Veracruz, Coatzacoalcos 6.250055
 92  A*02-B*39-DRB1*04-DQB1*03:02  Mexico Mexico City North 6.2417751
 93  A*02-B*07-DRB1*15  Germany pop 7 6.200013,386
 94  A*02-B*51  Pakistan Mixed Pathan 6.2000100
 95  A*02-B*51  Pakistan Brahui 6.2000104
 96  A*02:01-B*35:12  Mexico Mestizo 6.100041
 97  A*02:01-B*35:17-DRB1*08:02  Mexico Mixtec 6.100097
 98  A*02-B*39-DRB1*04-DQB1*03:02  Mexico Oaxaca Rural 6.0575485
 99  A*02:01-B*35:12-DRB1*08:02  Mexico Oaxaca Mixtec 6.0000103
 100  A*02:01-B*39:02-DRB1*16:02  Mexico Oaxaca Mixtec 6.0000103

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 40,342) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 404  


   

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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