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 2,115) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 22  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  DRB1*04:03/04:06-DQB1*03:02  Samoa 17.200029
 2  DRB1*04:03-DQA1*03:01/03:02/03:03-DQB1*03:02  Russia Siberia Dudinka Nganasan 12.500024
 3  DRB1*04:03-DQA1*03:01-DQB1*03:02  Canada British Columbia Athabaskan 9.600062
 4  DRB1*04:03-DQB1*03:02  Taiwan Aborigine pop 2 9.500048
 5  A*24:02-B*39:05-C*07:02-DRB1*04:03-DQA1*03:01:01-DQB1*03:02-DPA1*01-DPB1*04:02  Venezuela Sierra de Perija Yucpa 9.300073
 6  A*24-B*51-DRB1*04:03-DQB1*03:02  Colombia Wayu from Guajira Peninsula 9.220048
 7  DRB1*04:03-DQA1*03-DQB1*03:02  Russia Siberia Kushun Buryat 8.000025
 8  A*02-B*48-DRB1*04:03-DQB1*03:02  Peru Lamas City Lama 7.800083
 9  A*02:01-B*35:05-DRB1*04:03-DQB1*03:02  Peru Titikaka Lake Uros 6.3100105
 10  A*02:01-B*35:05-DRB1*04:03-DQB1*03:02  Peru Titikaka Lake Uro 6.3000105
 11  DRB1*04:03-DQA1*03-DQB1*03:02  Russia Siberia Khabarovsk Evenki 6.000025
 12  DRB1*04:03-DQA1*03-DQB1*03:02  Russia Siberia Negidal 5.700035
 13  DRB1*04:03/04:06-DQB1*03:02  Philippines 5.200034
 14  DRB1*04:03-DQB1*03:02  Mexico Oaxaca Zapotec 5.200090
 15  DRB1*04:03/04:04/04:06/04:07/04:08-DQA1*03:01/03:02-DQB1*03:02  England pop 6 5.1000177
 16  DRB1*04:03-DQA1*03-DQB1*03:02  Russia Siberia North East Kamchatka Koryak 4.900092
 17  DRB1*04:03-DQA1*03-DQB1*03:02  Russia Tuva pop3 4.500044
 18  A*68-B*15-DRB1*04:03-DQB1*03:02  Colombia Wayu from Guajira Peninsula 4.170048
 19  DRB1*04:03-DQB1*03:02  Mexico Oaxaca Mixe 3.900055
 20  DRB1*04:03-DQB1*03:02  Mexico Oaxaca Mixtec 3.9000103
 21  A*68:01-B*51:01-DRB1*04:03-DQB1*03:02  Chile Mapuche 3.850066
 22  DRB1*04:03-DQA1*03:01-DQB1*03:02  Italy Sardinia Sorgono 3.800093
 23  DRB1*04:03-DQB1*03:02  Japan Central 3.8000371
 24  DRB1*04:03-DQA1*03:01-DQB1*03:02  Tunisia 3.5000100
 25  DRB1*04:03:01-DQB1*03:02/03:07-DPB1*04:02  Mexico Chihuahua Tarahumara 3.400044
 26  DRB1*04:03-DQA1*03-DQB1*03:02  Turkey pop 1 3.4000250
 27  A*02-B*44-DRB1*04:03-DQB1*03:02  Spain Pas Valley 3.300088
 28  DRB1*04:03-DQA1*03:01:01-DQB1*03:02  South Korea pop 5 3.3000467
 29  DRB1*04:03-DQA1*03:01-DQB1*03:02  Italy Sardinia Sassari 3.300091
 30  DRB1*04:03-DQA1*03-DQB1*03:02  Algeria pop 2 3.3000106
 31  DRB1*04:03-DQB1*03:02  USA Asian pop 2 3.22201,772
 32  A*68:01:02-B*35:05-DRB1*04:03-DQB1*03:02  Peru Titikaka Lake Uro 3.2000105
 33  A*68:01:02-B*35:05-DRB1*04:03-DQB1*03:02  Peru Titikaka Lake Uros 3.1800105
 34  A*24-B*35-DRB1*04:03-DQB1*03:02  Colombia Wayu from Guajira Peninsula 3.130048
 35  DRB1*04:03-DQA1*03:01/03:02-DQB1*03:02  Ethiopia Oromo 3.000083
 36  DRB1*04:03-DQA1*03:01-DQB1*03:02  Russia Northwest Slavic 3.0000200
 37  DRB1*04:03-DQB1*03:02  USA Alaska Yupik 3.0000252
 38  DRB1*04:03-DQB1*03:02  Japan Hokkaido Ainu 3.000050
 39  A*02-B*35-DRB1*04:03-DQB1*03:02  Bolivia Quechua 2.900069
 40  DRB1*04:03-DQA1*03:01-DQB1*03:02  Italy Sardinia Cagliari 2.900087
 41  DRB1*04:03-DQA1*03:01-DQB1*03:02  Japan pop 2 2.9000916
 42  DRB1*04:03-DQA1*03-DQB1*03:02  Russia Siberia Polygus Evenk 2.900035
 43  DRB1*04:03-DQB1*03:02  Mexico Nahua/Aztec Santo Domingo Ocotitlan 2.739773
 44  DRB1*04:03-DQB1*03:02-DMB*01:03  Ecuadorean Amerindians 2.556175
 45  DRB1*04:03-DQB1*03:02  Vietnam Hanoi Kinh 2.5000103
 46  DRB1*04:03-DQB1*03:02  Tunisia Matmata Berber 2.500081
 47  A*69-B*49-DRB1*04:03-DQB1*03:02  Gaza Palestinians 2.4000165
 48  A*68:01-B*35:01-DRB1*04:03-DQB1*03:02  Chile Mapuche 2.310066
 49  A*68:01-B*39:01-DRB1*04:03-DQB1*03:02  Chile Mapuche 2.310066
 50  DRB1*04:03-DQA1*03:01-DQB1*03:02  South Korea pop 1 2.3000324
 51  A*24:02-B*48:01-DRB1*04:03-DQB1*03:02  Peru Titikaka Lake Uros 2.2300105
 52  A*02-B*44-DRB1*04:03-DQB1*03:02  Spain North Cabuerniga 2.200095
 53  A*24:02-B*48:01-DRB1*04:03-DQB1*03:02  Peru Titikaka Lake Uro 2.2000105
 54  A*31:01:02-B*15:01-DRB1*04:03-DQB1*03:02  USA South Dakota Lakota Sioux 2.2000302
 55  DRB1*04:03-DQA1*03:01-DQB1*03:02  Italy Sardinia Carbonia 2.200091
 56  DRB1*04:03-DQA1*03:01-DQB1*03:02  India Northeast Mathur 2.2000155
 57  DRB1*04:03-DQA1*03:01-DQB1*03:02-DPB1*02:01  China Canton Han 2.2000264
 58  DRB1*04:03-DQA1*03-DQB1*03:02  Russia Siberia Khanty Mansi 2.200068
 59  DRB1*04:03-DQB1*03:02  Mexico Mexico City Mestizo pop 2 2.1400234
 60  DRB1*04:03-DQB1*03:02  Georgia Caucasus Tbilisi 2.1008119
 61  A*68:01-B*40:02-DRB1*04:03-DQB1*03:02  USA Alaska Yupik 2.1000252
 62  A*02-B*15-DRB1*04:03-DQB1*03:02  Colombia Wayu from Guajira Peninsula 2.080048
 63  A*02-B*51-DRB1*04:03-DQB1*03:02  Colombia Wayu from Guajira Peninsula 2.080048
 64  A*24-B*40-DRB1*04:03-DQB1*03:02  Colombia Wayu from Guajira Peninsula 2.080048
 65  A*31-B*39-DRB1*04:03-DQB1*03:02  Colombia Wayu from Guajira Peninsula 2.080048
 66  DRB1*04:03/04:06-DQB1*03:02  Malaysia 2.000074
 67  DRB1*04:03-DQA1*03:01/03:02-DQB1*03:02  Ethiopia Amhara 2.000098
 68  DRB1*04:03-DQA1*03:01-DQB1*03:02  Greece pop3 2.0000246
 69  DRB1*04:03-DQA1*03:01-DQB1*03:02  India Uttar Pradesh 2.0000202
 70  A*24:02-B*35:05-DRB1*04:03-DQB1*03:02  Peru Titikaka Lake Uros 1.9600105
 71  A*24-B*35-DRB1*04:03-DQB1*03:02  Mexico San Vicente Tancuayalab Teenek/Huastecos 1.890053
 72  DRB1*04:03-DQB1*03:02  Cretan Islanders 1.8145124
 73  DRB1*04:03-DQB1*03:02  Vietnam HoaBinh Muong 1.800083
 74  DRB1*04:03-DRB4*01-DQB1*03:02  Macedonia pop 2 1.800080
 75  A*24:02-B*40:01-C*04:01-DRB1*04:03-DQB1*03:02  USA NMDP Hawaiian or other Pacific Islander 1.737511,499
 76  DRB1*04:03-DQB1*03:02  USA Hispanic pop 2 1.71601,999
 77  DRB1*04:03-DQA1*03:01-DQB1*03:02-DPB1*05:01  South Korea pop 1 1.7000324
 78  DRB1*04:03-DQA1*03-DQB1*03:02  Russia Siberia Chukotka Peninsula Chukchi 1.700059
 79  DRB1*04:03-DQA1*04:01-DQB1*03:02  Russia Siberia Chukotka Peninsula Chukchi 1.700059
 80  DRB1*04:03-DQB1*03:02-DPB1*05:01  South Korea pop 1 1.7000324
 81  A*02-B*39-DRB1*04:03-DQB1*03:02  Mexico Sinaloa Capomos Mayo Yoremes 1.666760
 82  A*02-B*35-DRB1*04:03-DQB1*03:02  Bolivia La Paz Aymaras 1.631087
 83  B*15:01-DRB1*04:03-DQB1*03:02  South Korea pop 3 1.6000485
 84  DRB1*04:03-DQA1*03:01-DQB1*03:02  Mexico Highlands Mestizos 1.6000160
 85  DRB1*04:03-DQB1*03:02  Tunisia Gabes Arab 1.600096
 86  A*02:01-B*35:04-DRB1*04:03-DQB1*03:02  Chile Mapuche 1.540066
 87  A*02:01-B*48:01-DRB1*04:03-DQB1*03:02  Peru Titikaka Lake Uros 1.5400105
 88  A*03:01-B*27:05-DRB1*04:03-DQB1*03:02  Chile Mapuche 1.540066
 89  A*68:01-B*39:09-DRB1*04:03-DQB1*03:02  Chile Mapuche 1.540066
 90  DRB1*04:03-DQA1*03:01-DQB1*03:02  Mexico Guanajuato and Jalisco Mestizo 1.5000101
 91  DRB1*04:03-DQA1*03:01-DQB1*03:02  Morocco Souss Region 1.500098
 92  A*31:01-B*35:01-C*07:02-DRB1*04:03-DQA1*03:01-DQB1*03:02  Mexico Tixcacaltuyub Maya 1.492567
 93  A*68:03-B*35:43-C*01:02-DRB1*04:03-DQA1*03:01-DQB1*03:02  Mexico Tixcacaltuyub Maya 1.492567
 94  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*04:03:01-DQB1*03:02:01  India Karnataka Kannada Speaking 1.4370174
 95  A*02:01:01-B*39:01:01-C*07:01:01-DRB1*04:03:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 1.388972
 96  A*24:02-B*35:01-DRB1*04:03-DQB1*03:02  Peru Titikaka Lake Uros 1.3700105
 97  DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*05:01  China Zhejiang Han pop 2 1.3522833
 98  DRB1*04:03-DQA1*03:01-DQB1*03:02  Mexico Nuevo Leon Mestizo 1.300040
 99  A*24-B*15-DRB1*04:03-DQB1*03:02  Colombia Wayu from Guajira Peninsula 1.200048
 100  A*68:01-B*39:09-C*07:02-DRB1*04:03-DQA1*03:01:01-DQB1*03:02-DPA1*01-DPB1*04:02  Venezuela Sierra de Perija Yucpa 1.200073

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 2,115) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 22  


   

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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