Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Population:  Country:  Source of dataset : 
Region:  Ethnic Origin:     Type of study :  Sort by: 
Sample Size:      Sample Year:     Loci Tested: 
Displaying 1 to 100 (from 799) records   Pages: 1 2 3 4 5 6 7 8 of 8  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*33-B*14:01-C*08:02  Pakistan Karachi Parsi 4.400091
 2  B*14:01-C*08:02  Tunisia 3.5000100
 3  A*03-B*14:01-DRB1*01-DQB1*05  Mexico Morelos Rural 3.333330
 4  A*33:01-B*14:01  Tunisia 3.0000100
 5  A*02:05-B*14:01  South Africa Natal Zulu 2.5000100
 6  A*30:01-B*14:01  India West Coast Parsi 2.400050
 7  A*23:01-B*14:01  Zambia Lusaka 2.300044
 8  A*23:01-B*14:01-C*02:02  Zambia Lusaka 2.300044
 9  B*14:01-C*02:02  Zambia Lusaka 2.300044
 10  B*14:01-C*08:02  Ireland Northern 2.10001,000
 11  A*68:02:01-B*14:01:01-C*08:02:01  South African Mixed ancestry 2.000050
 12  B*14:01-C*08:02-DRB1*07:01-DQB1*02:02  Ireland South 2.0000250
 13  A*30:04-B*14:01-C*08:02  South Korea pop 3 1.9000485
 14  A*26:01-B*14:01-DRB1*07:01  Azores Central Islands 1.800059
 15  A*33-B*14:01-DRB1*07-DQB1*02  Mexico Veracruz, Coatzacoalcos 1.785755
 16  A*26-B*14:01-DRB1*13-DQB1*06  Mexico San Luis Potosi Rural 1.724187
 17  A*24:02:01-B*14:01-DRB1*07:01:01  Madeira 1.6000185
 18  B*14:01-C*08:02  Uganda Kampala 1.6000161
 19  A*33:01-B*14:01-DRB1*01:01-DQB1*05:01  Iran Tabriz Azeris 1.546497
 20  A*26-B*14:01-DRB1*07-DQB1*02  Mexico Mexico City West 1.470633
 21  A*32:01-B*14:01-DRB1*15:01  Azores Oriental Islands 1.300043
 22  B*14:01-C*08:02-DRB1*04:04  South Korea pop 3 1.3000485
 23  B*14:01-DRB1*04:04-DQB1*04:02  South Korea pop 3 1.3000485
 24  A*26-B*14:01-DRB1*01:03-DQB1*05  Mexico Guanajuato, Leon 1.282178
 25  A*32-B*14:01-DRB1*08-DQB1*03:01  Ecuador Amazonia Mixed Ancestry 1.282139
 26  A*68-B*14:01-DRB1*13-DQB1*03:01  Mexico Jalisco, Tlaquepaque 1.282139
 27  A*26:01-B*14:01-DRB1*13:03  Gaza 1.282042
 28  A*02-B*14:01-DRB1*04-DQB1*03:02  Mexico Morelos, Cuernavaca 1.219582
 29  A*26-B*14:01-DRB1*07-DQB1*02  Mexico Tabasco, Villahermosa 1.219582
 30  A*30:04-B*14:01-C*08:02-DRB1*04:04-DQB1*04:02  South Korea pop 3 1.2000485
 31  A*30:04-B*14:01-DRB1*04:04  South Korea pop 3 1.2000485
 32  A*32:01-B*14:01-C*08:02  Ireland South 1.2000250
 33  A*32:01-B*14:01-C*08:02-DRB1*07:01-DQB1*02:02  Ireland South 1.2000250
 34  B*14:01-C*08:02  Mali Bandiagara 1.2000138
 35  A*01:01-B*14:01-DRB1*01:02-DQB1*05:01  Mexico Chihuahua Chihuahua City Pop 2 1.136488
 36  A*11-B*14:01-DRB1*04-DQB1*03:02  Mexico Queretaro, Queretaro city 1.111145
 37  A*24-B*14:01-DRB1*15-DQB1*06  Mexico Veracruz, Poza Rica 1.111145
 38  A*26-B*14:01-DRB1*07-DQB1*02  Mexico Veracruz, Poza Rica 1.111145
 39  A*68-B*14:01-DRB1*09-DQB1*02  Mexico Veracruz, Poza Rica 1.111145
 40  B*14:01-C*08:02  USA Hispanic 1.1000234
 41  A*02-B*14:01-DRB1*07-DQB1*02  Mexico Campeche Rural 1.063847
 42  A*11-B*14:01-DRB1*04-DQB1*02  Mexico Campeche Rural 1.063847
 43  B*14:01-C*08:02  Mexico Mexico City Mestizo population 1.0490143
 44  A*02-B*14:01-DRB1*07-DQB1*02  Mexico Quintana Roo Rural 1.000050
 45  A*24:02:01-B*14:01-DRB1*10:01  Portugal South 1.000049
 46  A*32:01-B*14:01  South Africa Natal Zulu 1.0000100
 47  A*33:01-B*14:01-DRB1*01:02:01  Portugal South 1.000049
 48  A*68:02:01-B*14:01:01-C*04:01:01  South African Indian population 1.000050
 49  B*14:01-C*08:02  Mexico Oaxaca Mixtec 1.0000103
 50  A*24-B*14:01-DRB1*01-DQB1*05  Mexico Sinaloa, Culiacán 0.9709103
 51  A*68-B*14:01-DRB1*07-DQB1*02  Mexico Sinaloa, Culiacán 0.9709103
 52  A*03:01-B*14:01-C*08:02-DRB1*04:05-DQB1*03:02  Colombia North Wiwa El Encanto 0.961552
 53  A*33:18-B*14:01-C*07:02-DRB1*01:01-DQB1*06:02  Colombia North Wiwa El Encanto 0.961552
 54  A*23-B*14:01-DRB1*08-DQB1*03:01  Mexico Veracruz, Cordoba 0.892956
 55  A*24-B*14:01-DRB1*15-DQB1*06  Mexico Veracruz, Coatzacoalcos 0.892955
 56  A*32:01-B*14:01-C*08:02-E*01:01:01-F*01:01:01-G*01:01-DRB1*07:01-DQA1*02:01-DQB1*02:02  Portugal Azores Terceira Island 0.8772130
 57  B*14:01-C*08:02  Mexico Mexico City Mestizo pop 2 0.8500234
 58  A*01:01-B*14:01-DRB1*04:01-DQB1*03:02  Iran Saqqez-Baneh Kurds 0.833360
 59  B*14:01-C*08:02  USA Hispanic pop 2 0.82801,999
 60  A*02-B*14:01-DRB1*13-DQB1*06  Mexico Colima, Colima city 0.819761
 61  A*26-B*14:01-DRB1*07-DQB1*02  Mexico Sinaloa Rural 0.8197183
 62  A*03-B*14:01-DRB1*15-DQB1*06  Mexico Nayarit Rural 0.781264
 63  A*32:03-B*14:01-C*08:01-DRB1*04:01-DQB1*05:01  Iran Gorgan 0.780064
 64  A*33:01-B*14:01-DRB1*07:01-DQB1*02:01  Chile Mapuche 0.770066
 65  A*24:02-B*14:01-C*08:02-DRB1*13:03-DQA1*02:01-DQB1*02:02  Mexico Tixcacaltuyub Maya 0.746367
 66  A*30:04-B*14:01-C*08:02-DRB1*04:04-DRB4*01:01-DQB1*04:02  USA NMDP Korean 0.718777,584
 67  B*14:01-C*08:02  USA African American pop 4 0.70602,411
 68  A*26:01:01-B*14:01:01-C*08:02:01-DRB1*07:01:01-DQB1*02:02:01  Spain, Canary Islands, Gran canaria island 0.7000215
 69  A*32-B*14:01-DRB1*07-DQB1*02  Mexico Sonora, Ciudad Obregón 0.6993143
 70  A*33-B*14:01-DRB1*07-DQB1*02  Mexico Sonora, Ciudad Obregón 0.6993143
 71  A*02:01:01-B*14:01:01-C*01:02:01-DRB1*07:01:01-DQB1*02:02  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 72  A*11-B*14:01-DRB1*04-DQB1*03:02  Mexico Guerrero state 0.6944144
 73  A*68-B*14:01-DRB1*13-DQB1*03:01  Mexico Guerrero state 0.6944144
 74  A*30:04-B*14:01-DRB1*04:04  Israel YemenJews 0.674015,542
 75  A*32:01:01-B*14:01:01-C*08:02:01  England Blood Donors of Mixed Ethnicity 0.6686519
 76  A*01-B*14:01-DRB1*07-DQB1*02  Mexico Durango, Durango city 0.6452153
 77  B*14:01-C*08:02-DRB1*07:01-DQB1*02:02  Mexico Mexico City Mestizo pop 2 0.6400234
 78  A*01-B*14:01-DRB1*03:01-DQB1*02  Mexico Tabasco, Villahermosa 0.609882
 79  A*23-B*14:01-DRB1*07-DQB1*02  Mexico Jalisco, Zapopan 0.5952168
 80  A*26:01-B*14:01-DRB1*07:01-DQB1*02:02  Mexico Veracruz Xalapa 0.595284
 81  A*26:01-B*14:01-DRB1*14:01-DQB1*03:02  Mexico Veracruz Xalapa 0.595284
 82  A*26-B*14:01-DRB1*07-DQB1*02  Mexico Zacatecas, Zacatecas city 0.595284
 83  A*68:01-B*14:01-DRB1*16:02-DQB1*03:01  Mexico Veracruz Xalapa 0.595284
 84  A*36:01-B*14:01:01-C*08:02:01-DRB1*01:01:01-DQB1*05:01:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Parda 0.5882170
 85  A*01:01-B*14:01-DRB1*03:01-DQB1*02:01  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 86  A*01:01-B*14:01-DRB1*04:07-DQB1*03:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 87  A*01:01-B*14:01-DRB1*11:04-DQB1*03:01  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 88  A*03:01-B*14:01-DRB1*13:01-DQB1*06:03  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 89  A*24:02-B*14:01-DRB1*01:01-DQB1*05:01  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 90  A*26:01-B*14:01-DRB1*04:13-DQB1*03:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 91  A*26:01-B*14:01-DRB1*10:01-DQB1*05:01  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 92  A*02-B*14:01-DRB1*07-DQB1*02  Mexico Zacatecas Rural 0.5576266
 93  A*24-B*14:01-DRB1*15-DQB1*06  Mexico Sinaloa Rural 0.5464183
 94  A*26-B*14:01-DRB1*15-DQB1*06  Mexico Sinaloa Rural 0.5464183
 95  A*02-B*14:01-DRB1*14-DQB1*05  Mexico Aguascalientes state 0.526395
 96  A*32-B*14:01-DRB1*07-DQB1*02  Mexico Aguascalientes state 0.526395
 97  A*02:01-B*14:01-DRB1*04:04  Mexico Oaxaca Jamiltepec Mixtec 0.520096
 98  A*01:02-B*14:01-DRB1*13:01-DQB1*04:01  Iran Tabriz Azeris 0.515597
 99  A*03:01-B*14:01-DRB1*13:01-DQB1*03:03  Iran Tabriz Azeris 0.515597
 100  A*31:01-B*14:01-DRB1*01:01-DQB1*05:01  Iran Tabriz Azeris 0.515597

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 799) records   Pages: 1 2 3 4 5 6 7 8 of 8  


   

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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