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 6,317) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 64  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  DRB1*08:02-DQB1*04:02  Mexico Oaxaca Mixe 28.000055
 2  DRB1*08:02:01-DQB1*04:02-DPB1*04:02  Mexico Chihuahua Tarahumara 27.900044
 3  DRB1*08:02-DQA1*04:01-DQB1*04:02  Brazil Central Plateau Xavante 23.000074
 4  DRB1*08:02-DQB1*04:02  Mexico Oaxaca Mixtec 21.6000103
 5  DRB1*08:02-DQB1*04:02  Mexico Oaxaca Zapotec 21.500090
 6  DRB1*08:01-DQB1*04:02  Sweden Northern Sami 20.7000154
 7  DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo pop 2 19.0200234
 8  DRB1*08:02-DQA1*04:01-DQB1*04:02  Argentina Gran Chaco Eastern Toba 18.9000135
 9  DRB1*08:02-DQB1*04:02  Mexico Mexico City Mestizo population 18.1818143
 10  DQA1*03-DQB1*04:01  Japan Fukuoka 16.300086
 11  DQA1*04:01-DQB1*04:02  Ecuador Cayapa 15.1000183
 12  DRB1*08:02-DQA1*04:01-DQB1*04:02  Mexico Guanajuato and Jalisco Mestizo 14.9000101
 13  DRB1*04:05-DQA1*03:01-DQB1*04:01  Japan pop 2 14.7000916
 14  DRB1*08:02-DQA1*04:01-DQB1*04:02  Mexico Highlands Mestizos 13.8000160
 15  A*02:01-B*35:05-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uro 13.5000105
 16  A*02:01-B*35:05-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uros 13.4500105
 17  DRB1*08:02-DQB1*04:02  USA Alaska Yupik 13.3000252
 18  DRB1*08:01-DQA1*04:01-DQB1*04:02  Russia Siberia Lower Yenisey Ket 11.800017
 19  DQA1*03-DQB1*04:01  Papua New Guinea Highland pop2 11.500028
 20  DRB1*04:05-DQB1*04:01  Japan Central 11.3000371
 21  DRB1*08:02-DQB1*04:02  Mexico Nahua/Aztec Santo Domingo Ocotitlan 10.958973
 22  DRB1*04:05-DQB1*04:01  Papua New Guinea Highland 10.900094
 23  DRB1*08:02-DQA1*04:01-DQB1*04:02  Argentina Gran Chaco Western Toba Pilaga 10.500019
 24  A*02-B*35-DRB1*08:02-DQB1*04:02  Bolivia La Paz Aymaras 10.448087
 25  A*02-B*35-DRB1*08:02-DQB1*04:02  Bolivia Quechua 10.050069
 26  DRB1*08:02-DQB1*04:02  Japan Hokkaido Ainu 10.000050
 27  A*02-B*35-DRB1*08-DQB1*04  Mexico Morelos, Cuernavaca 9.756182
 28  A*02-B*35-DRB1*08-DQB1*04  Mexico San Luis Potosi Rural 9.195487
 29  DRB1*04:05-DQA1*03:03-DQB1*04:01  South Korea pop 5 8.8000467
 30  A*68-B*39-DRB1*08-DQB1*04  Mexico Tamaulipas, Ciudad Victoria 8.695723
 31  DQA1*04:01-DQB1*04:02  Ecuador African 8.600058
 32  DQA1*04:01-DQB1*04:02  Uganda Baganda 8.500047
 33  A*02-B*35-DRB1*08:02-DQB1*04:02  Guatemala Mayan 8.4000132
 34  DRB1*04:05-DQB1*04:01  Japan Hokkaido Ainu 8.000050
 35  A*02-B*48-DRB1*08:04-DQB1*04:02  Peru Lamas City Lama 7.800083
 36  DRB1*08-DQA1*04:01-DQB1*04:02  Croatia Gorski Kotar Region 7.700063
 37  DRB1*08-DQA1*04-DQB1*04  Mexico Tapachula, Chiapas Mestizo Population 7.638972
 38  A*02-B*35-DRB1*08-DQB1*04  Mexico Hidalgo Rural 7.407481
 39  DRB1*04:05-DQA1*03:03-DQB1*04:01  South Korea pop 1 7.4000324
 40  DRB1*08:02:01-DQB1*04:02-DPB1*04:01  Mexico Chihuahua Tarahumara 7.400044
 41  DRB1*08:01-DQA1*04:01-DQB1*04:02  Russia Siberia Irkutsk Tofalar 7.000043
 42  DRB1*04:05-DQB1*04:02  Samoa 6.900029
 43  DRB1*08:02-DQA1*05:01-DQB1*04:02  Russia Siberia Chukotka Peninsula Eskimo 6.900080
 44  A*24:02-B*35:05-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uros 6.8100105
 45  A*24:02-B*35:05-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uro 6.8000105
 46  A*02-B*35-DRB1*08-DQB1*04  Mexico Jalisco, Tlajomulco 6.666730
 47  DRB1*04:05-DQB1*04:02  Papua New Guinea East New Britain Tolai 6.500048
 48  A*02-B*35-DRB1*08-DQB1*04  Mexico Jalisco, Tlaquepaque 6.410339
 49  A*24-B*35-DRB1*08-DQB1*04  Mexico Jalisco, Tlaquepaque 6.410339
 50  DRB1*08:01-DQB1*04:02  Sweden Southern Sami 6.4000130
 51  DRB1*03:02:01-DQA1*04:01-DQB1*04:02  Cameroon Yaounde 6.300092
 52  A*02-B*35-DRB1*08-DQB1*04  Mexico Quintana Roo, Cancun 6.250048
 53  DRB1*04:05-DQA1*03:03-DQB1*04:01-DPB1*05:01  South Korea pop 2 6.2000207
 54  A*68:01-B*39:09-DRB1*08:02-DQB1*04:02  Chile Mapuche 6.150066
 55  A*24:02-B*35:01-DRB1*08:02-DQB1*04:02  USA Alaska Yupik 6.0000252
 56  DRB1*08:01-DQA1*04:01-DQB1*04:02  Russia Siberia Khabarovsk Evenki 6.000025
 57  DRB1*08:02-DQA1*04:01-DQB1*04:02  Russia Siberia Khabarovsk Evenki 6.000025
 58  A*02-B*07-DRB1*08:01-DQB1*04:02  Colombia San Basilio de Palenque 5.952042
 59  DRB1*03:02-DQB1*04:02  USA African American pop 4 5.94102,411
 60  DRB1*08:01-DQB1*04:02  Spain Tenerife Island 5.880083
 61  A*02:04-B*52:01:02-C*15:03-DRB1*08:07-DQA1*04:01-DQB1*04:02-DPA1*02-DPB1*14:01  Venezuela Sierra de Perija Yucpa 5.800073
 62  A*31-B*52:01:02-C*15:03-DRB1*08:07-DQA1*04:01-DQB1*04:02-DPA1*02-DPB1*14:01  Venezuela Sierra de Perija Yucpa 5.800073
 63  A*02-B*15:01-DRB1*08-DQB1*04  Mexico Aguascalientes state 5.789595
 64  A*02-B*35-DRB1*08-DQB1*04  Mexico Nuevo Leon, Monterrey city 5.7522226
 65  DRB1*04:05-DQB1*04:01  Taiwan pop 2 5.7000364
 66  DRB1*08:02-DQB1*04:02  USA Hispanic pop 2 5.61201,999
 67  DRB1*04:05-DQB1*04:01-DPB1*05:01  South Korea pop 1 5.6000324
 68  DRB1*08-DQA1*04:01-DQB1*04:02  Mexico Guadalajara Mestizo 5.600054
 69  A*02-B*35-DRB1*08-DQB1*04  Mexico Coahuila, Saltillo 5.479572
 70  DRB1*04:05-DQA1*03:03-DQB1*04:01-DPB1*05:01  South Korea pop 1 5.4000324
 71  A*02-B*48-DRB1*08:02-DQB1*04:02  Bolivia La Paz Aymaras 5.187087
 72  A*68-B*40:02-DRB1*08-DQB1*04  Mexico San Luis Potosi Rural 5.172487
 73  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
 74  DQA1*04:01-DQB1*04:02  Gambia 5.1000146
 75  DRB1*04:05-DQA1*03:01-DQB1*04:01  China Urumqi Han 5.100059
 76  DRB1*08:02-DQB1*04:02-DMB*01:01  Ecuadorean Amerindians 5.077575
 77  A*02-B*40-DRB1*08:02-DQB1*04:02  Bolivia Quechua 5.070069
 78  DRB1*08-DQA1*04:01-DQB1*04:01/04:02  Russia Vologda 5.0000121
 79  A*02-B*35-DRB1*08-DQB1*04  Mexico Tlaxcala Rural 4.8193830
 80  A*02-B*35-DRB1*08-DQB1*04  Mexico Mexico City South 4.807752
 81  DRB1*08:02-DQA1*04:01-DQB1*04:02  Canada British Columbia Athabaskan 4.800062
 82  A*02-B*15-DRB1*03:02-DQB1*04:02  Colombia San Basilio de Palenque 4.762042
 83  A*02-B*35-DRB1*08-DQB1*04  Mexico Jalisco, Zapopan 4.7619168
 84  DRB1*04:05-DQA1*03:01-DQB1*04:01  Mongolia Tarialan Khoton 4.700085
 85  A*02-B*35-DRB1*08-DQB1*04  Mexico Oaxaca, Oaxaca city 4.6358151
 86  A*31:01:02-B*51:02:01-C*08:01-DRB1*08:02:01-DQB1*04:02-DPB1*04:02  Mexico Chihuahua Tarahumara 4.600044
 87  DRB1*08:01-DQA1*04:01-DQB1*04:02  Iran Yazd Zoroastrian 4.600065
 88  A*02-B*35-DRB1*08-DQB1*04  Mexico Guanajuato, Guanajuato city 4.545522
 89  A*02-B*35-DRB1*08-DQB1*04  Mexico Nuevo Leon Rural 4.5455439
 90  A*24-B*40:02-DRB1*08-DQB1*04  Mexico Guanajuato, Guanajuato city 4.545522
 91  DRB1*04:05-DQB1*04:01  USA Asian pop 2 4.54501,772
 92  A*30:01-B*42:01-C*17:01-DRB1*03:02-DQA1*04:01-DQB1*04:02-DPB1*01:01  Kenya, Nyanza Province, Luo tribe 4.5000100
 93  DRB1*04:05-DQB1*04:01  Vietnam Hanoi Kinh 4.5000103
 94  DRB1*08:01-DQA1*04:01-DQB1*04:02  Russia Tuva Todja 4.500022
 95  DRB1*14:03-DQA1*05:01-DQB1*04:02  Russia Siberia Sulamai Ket 4.500022
 96  DQA1*04:01-DQB1*04:02  Russia Tuva pop 2 4.4000169
 97  DRB1*08:02-DQA1*04:01-DQB1*04:02  Russia Siberia Chukotka Peninsula Eskimo 4.400080
 98  A*02-B*35-DRB1*08-DQB1*04  Mexico Mexico City North 4.3825751
 99  A*02-B*35-DRB1*08-DQB1*04  Mexico Mexico City East 4.375079
 100  A*01-B*57-DRB1*04-DQB1*04  Mexico Tamaulipas, Ciudad Victoria 4.347823

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 6,317) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 64  


   

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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