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 101 to 200 (from 4,370) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 44  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 101  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  India Andhra Pradesh Telugu Speaking 3.1035186
 102  DQA1*02:01-DQB1*03:03  Belgium pop 2 3.1000715
 103  DRB1*09-DQA1*03:01-DQB1*03:03  Russia Arkhangelsk 3.100081
 104  A*01:01-B*57:01-C*06:02-DRB1*07:01-DQB1*03:03  Ireland South 3.0000250
 105  A*02-B*39-DRB1*09:01:02-DQB1*03:03  Peru Lamas City Lama 3.000083
 106  A*03-B*35-DRB1*07-DQB1*03:03  Mexico Baja California Rural 3.000050
 107  A*11-B*35-DRB1*07:01-DQB1*03:03  Russia Chuvash 3.000082
 108  DQA1*02:01-DQB1*03:03:02  India Bombay 3.000059
 109  DRB1*04:03-DQA1*03:01-DQB1*03:03  Iran Azeri 3.0000100
 110  DRB1*09:01-DQA1*03:01-DQB1*03:03  Mongolia Tarialan Khoton 3.000085
 111  A*01-B*15:01-DRB1*09-DQB1*03:03  Mexico Campeche, Campeche city 2.941234
 112  DRB1*07-DQA1*02:01-DQB1*03:03  Belarus Brest Region 2.9000105
 113  DRB1*09:01:02-DQA1*03:01/03:02/03:03-DQB1*03:03:02  Russia Siberia Lower Yenisey Ket 2.900017
 114  DRB1*09:01-DQA1*03:02-DQB1*03:03-DPB1*02:01  South Korea pop 1 2.9000324
 115  DRB1*09:01-DQB1*03:03-DPB1*02:01  Mongolia Tarialan Khoton 2.900085
 116  DRB1*15:01-DQA1*01:01-DQB1*03:03:02  Russia Siberia Polygus Evenk 2.900035
 117  A*02:07:01-B*46:01:01-C*01:02:01-DRB1*09:01:02-DQB1*03:03:02  Vietnam Kinh 2.8540101
 118  DRB1*07:01-DQB1*03:03  Sweden Southern Sami 2.8000130
 119  DRB1*07-DQA1*02:01-DQB1*03:03  Russia Kostroma Region 2.8000126
 120  DRB1*09:01-DQB1*03:03-DPB1*02:01  South Korea pop 1 2.8000324
 121  A*68-B*40:02-DRB1*16-DQB1*03:03  Mexico Coahuila, Saltillo 2.739772
 122  DRB1*09:01:02-DQB1*03:03:02-DPB1*05:01  China Yunnan Province Bai 2.7000128
 123  DRB1*13-DQA1*03:01-DQB1*03:03  Gabon Haut-Ogooue Dienga 2.7000167
 124  DRB1*07-DQA1*02:01-DQB1*03:03  Croatia Gorski Kotar Region 2.600063
 125  DRB1*09:01:02-DQB1*03:03  Malaysia 2.600074
 126  DRB1*09:01:02-DQB1*03:03:02-DPB1*05:01  China Lijiang Naxi 2.6000100
 127  A*02-B*35-DRB1*09-DQB1*03:03  Ecuador Amazonia Mixed Ancestry 2.564139
 128  A*02-B*51-DRB1*09-DQB1*03:03  Ecuador Amazonia Mixed Ancestry 2.564139
 129  A*24-B*40:02-DRB1*09-DQB1*03:03  Ecuador Amazonia Mixed Ancestry 2.564139
 130  A*02:01-B*46:01-C*01:02-DRB1*09:01-DQB1*03:03  Malaysia Peninsular Chinese 2.5440194
 131  DRB1*07:01-DQA1*02:01-DQB1*03:03  Russia Northwest Slavic 2.5000200
 132  DRB1*07:01-DQB1*03:03  Vietnam Hanoi Kinh 2.5000103
 133  DRB1*07-DQA1*02:01-DQB1*03:03  Ukraine Khmelnytskyi 2.5000138
 134  DRB1*07-DQA1*02:01-DQB1*03:03  Belarus Vitebsk Region 2.500070
 135  DRB1*09:01:02-DQA1*03:02-DQB1*03:03:02-DPB1*02:01  South Korea pop 2 2.5000207
 136  DRB1*09:01-DQA1*03:01-DQB1*03:03-DPB1*02:01  China Canton Han 2.5000264
 137  DRB1*09-DQA1*03:01-DQB1*03:03  Russia Vologda 2.5000121
 138  DRB1*04:01-DQA1*03-DQB1*03:03:02  Russia Siberia Gvaysugi Udege 2.400025
 139  DRB1*09:01:02-DQA1*02:01-DQB1*03:03  China Urumqi Kazak 2.400042
 140  A*66:01:01-B*58:02:01-C*06:02:01-DRB1*08:07-DQB1*03:03:02-DPA1*01:03:01-DPB1*04:02:01  Brazil Barra Mansa Rio State Black 2.381073
 141  DRB1*07:01:01-DQB1*03:03:02  India Mumbai Maratha 2.320091
 142  A*33:01-B*14:02-DRB1*07:01-DQB1*03:03  Chile Mapuche 2.310066
 143  A*02:06-B*40:02-DRB1*09:01-DQB1*03:03  USA Alaska Yupik 2.3000252
 144  DRB1*07:01-DQA1*02:01-DQB1*03:03  England pop 6 2.3000177
 145  DRB1*09:01:02-DQA1*03-DQB1*03:03  Russia Tuva pop3 2.300044
 146  DRB1*09:01:02-DQA1*03-DQB1*03:03:02  Russia Siberia Sulamai Ket 2.300022
 147  B*40:06-DRB1*09:01-DQB1*03:03  South Korea pop 3 2.2000485
 148  DRB1*04:01-DQA1*03-DQB1*03:03:02  Russia Siberia North East Kamchatka Koryak 2.200092
 149  DRB1*07:01-DQA1*02:01-DQB1*03:03  Italy Sardinia Sorgono 2.200093
 150  DQB1*03:03-DPB1*04:02:01  China Inner Mongolia Autonomous Region Northeast 2.1960496
 151  A*01:01-B*57:01-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*03:03  USA NMDP South Asian Indian 2.1760185,391
 152  A*24-B*35-DRB1*07-DQB1*03:03  Mexico Tamaulipas, Ciudad Victoria 2.173923
 153  A*01:01-B*57:01-C*06:02-DRB1*07:01-DQB1*03:03  India West UCBB 2.16055,829
 154  A*32-B*41-DRB1*07-DQB1*03:03  Mexico Campeche Rural 2.127747
 155  DQA1*03-DQB1*03:03  China, Xinjiang Uyghur Autonomous Region Uyghur 2.110071
 156  A*01:01-B*57:01-C*06:02-DRB1*07:01-DQB1*03:03  Vietnam Hanoi Kinh pop 2 2.1000170
 157  A*02-B*48-DRB1*09:01-DQB1*03:03  Bolivia Quechua 2.100069
 158  A*68-B*35-DRB1*09:01-DQB1*03:03  Bolivia Quechua 2.100069
 159  DQA1*02:01-DQB1*03:03:02  Russia Tuva pop 2 2.1000169
 160  DRB1*09:01-DQA1*03:01-DQB1*03:03-DPB1*02:02  China Canton Han 2.1000264
 161  A*11:01:01-B*46:01:01-C*01:02:01-DRB1*09:01:02-DQB1*03:03:02  Vietnam Kinh 2.0960101
 162  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  India Kerala Malayalam speaking 2.0680356
 163  A*24-B*35-DRB1*09:01-DQB1*03:03  Bolivia La Paz Aymaras 2.038087
 164  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  India Karnataka Kannada Speaking 2.0110174
 165  A*02:07-B*46:01-C*01:02-DRB1*09:01-DQB1*03:03  Vietnam Hanoi Kinh pop 2 2.0000170
 166  DRB1*07:01:01-DQB1*03:03:02  China Shandong Province Han 2.000098
 167  DRB1*07:01-DQA1*02:01-DQB1*03:03  Greece pop3 2.0000246
 168  DRB1*07:01-DQA1*02:01-DQB1*03:03  Tunisia 2.0000100
 169  DRB1*09:01:02-DQA1*03-DQB1*03:03  Russia Siberia Kushun Buryat 2.000025
 170  DRB1*09:01-DQA1*03:01-DQB1*03:03  Russia Northwest Slavic 2.0000200
 171  A*01:01-B*57:01-C*06:02-DRB1*07:01-DQB1*03:03  India East UCBB 1.96422,403
 172  DRB1*09:01-DQA1*03:02-DQB1*03:03-DPA1*01:03-DPB1*02:01  China Zhejiang Han pop 2 1.9200833
 173  DRB1*09-DQA1*03:01-DQB1*03:03  Belarus Brest Region 1.9000105
 174  DRB1*14:02-DQA1*04:01-DQB1*03:03:02  Russia Siberia Chukotka Peninsula Eskimo 1.900080
 175  DRB1*07:01:01:01-DQB1*03:03  China Inner Mongolia Autonomous Region Northeast 1.8150496
 176  A*01:01-B*57:01:01-C*06:02-DRB1*07:01:01-DQB1*03:03:02  England North West 1.8000298
 177  A*11:01-B*46:01-C*01:02-DRB1*09:01-DQB1*03:03  Vietnam Hanoi Kinh pop 2 1.8000170
 178  A*24-B*15-DRB1*09:01:02-DQB1*03:03  Peru Lamas City Lama 1.800083
 179  DRB1*04:05:01-DQB1*03:03:02  China Yunnan Province Lahu 1.800070
 180  DRB1*07:01-DQA1*02:01-DQB1*03:03  India Northeast Shia 1.8000190
 181  DRB1*07:01-DQA1*02:01-DQB1*03:03  USA San Francisco Caucasian 1.8000220
 182  DRB1*07:01-DQB1*03:03  Tunisia Jerba Berber 1.800055
 183  DRB1*07:01-DQB1*03:03-DPB1*13:01  Ireland South 1.8000250
 184  A*29-B*44-DRB1*07-DQB1*03:03  Mexico Veracruz, Cordoba 1.785756
 185  DRB1*07:01-DQA1*02:01-DQB1*03:03  Spain Las Alpujarras 1.760085
 186  A*02-B*35-DRB1*09-DQB1*03:03  Ecuador Andes Mixed Ancestry 1.7597824
 187  DRB1*07:01-DQB1*03:03  USA Asian pop 2 1.72101,772
 188  DRB1*07:01-DQB1*03:03  Italy pop 5 1.7100975
 189  A*02-B*35-DRB1*09-DQB1*03:03  Ecuador Mixed Ancestry 1.70501,173
 190  A*11:01:01-B*51-C*14:02:01-DRB1*09:01:02-DQB1*03:03:02-DPB1*04:01:01  China Yunnan Province Lisu 1.7000111
 191  DRB1*07:01-DQB1*03:03  Samoa 1.700029
 192  DRB1*09:01-DQA1*03:01-DQB1*03:03-DPB1*13:01  China Canton Han 1.7000264
 193  DRB1*09-DQA1*03:02-DQB1*03:03  Croatia Gorski Kotar Region 1.700063
 194  DRB1*12:01-DQB1*03:03  Samoa 1.700029
 195  A*02-B*15-DRB1*09:01-DQB1*03:03  Bolivia La Paz Aymaras 1.689087
 196  A*02-B*48-DRB1*09:01-DQB1*03:03  Bolivia La Paz Aymaras 1.688087
 197  A*68-B*08-DRB1*09-DQB1*03:03  Mexico San Luis Potosi, San Luis Potosi city 1.666730
 198  DRB1*09:01:02-DQB1*03:03-DPB1*04:02:01  China Inner Mongolia Autonomous Region Northeast 1.6270496
 199  DRB1*07:01-DQA1*02:01-DQB1*03:03  Italy Sardinia Oristano 1.600091
 200  DRB1*09:01-DQA1*03:01-DQB1*03:03  USA San Francisco Caucasian 1.6000220

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 101 to 200 (from 4,370) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 44  


   

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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