Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

Please specify your search by selecting options from boxes. Then, click "Search" to find HLA Haplotype frequencies that match your criteria. Remember at least one option must be selected.
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 201 to 300 (from 5,642) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 57  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 201  A*03-B*52-DRB1*08-DQB1*04  Mexico Queretaro, Queretaro city 1.111145
 202  A*24-B*52-DRB1*04-DQB1*03:02  Mexico Veracruz, Poza Rica 1.111145
 203  A*24-B*52-DRB1*04-DQB1*05  Mexico Veracruz, Poza Rica 1.111145
 204  A*24-B*52-DRB1*14-DQB1*03:01  Mexico Veracruz, Poza Rica 1.111145
 205  A*24:02:01-B*52:01:01-C*12:02-DRB1*04:03:01  South Africa Caucasians 1.1100102
 206  A*24:02-B*52:01-C*12:02-DRB1*04:03-DQB1*03:02  Malaysia Peninsular Indian 1.1070271
 207  A*01-B*52-DRB1*04  Jordan 1.100015,141
 208  A*11-B*52-DRB1*15  Jordan 1.100015,141
 209  A*11:01-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  India East UCBB 1.09952,403
 210  A*02-B*52-DRB1*15-DQB1*06  Mexico Sinaloa Rural 1.0929183
 211  A*02-B*52-DRB1*04-DQB1*03:02  Mexico Durango Rural 1.0703326
 212  A*11:01-B*52:01-DRB1*15:02  Israel USSR Jews 1.070045,681
 213  A*24:02-B*52:01-C*03:04-DRB1*04:11-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 214  A*68:01-B*52:01-C*03:03-DRB1*04:11-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 215  A*02-B*52-DRB1*14-DQB1*03:01  Mexico Campeche Rural 1.063847
 216  A*02-B*52-DRB1*04-DQB1*03:02  Mexico Tabasco Rural 1.0563142
 217  A*11:01-B*52:01-DRB1*15:02  Israel Ashkenazi Jews pop 3 1.05004,625
 218  A*24-B*52-DRB1*14-DQB1*03:01  Mexico Sonora, Ciudad Obregón 1.0490143
 219  A*24:02-B*52:01  USA Asian pop 2 1.04301,772
 220  A*02-B*52-C*12-DRB1*14  Myanmar Rakhine 1.042048
 221  A*11-B*52-C*12-DRB1*11  Myanmar Rakhine 1.042048
 222  A*24:02:01-B*52:01:01-DRB1*14:04  China Jingpo Minority 1.0420105
 223  A*24-B*52-C*07-DRB1*14  Myanmar Rakhine 1.042048
 224  A*26-B*52-C*12-DRB1*08  Myanmar Rakhine 1.042048
 225  A*33:03:01-B*52:01:01-DRB1*12:02:01  China Jingpo Minority 1.0420105
 226  A*33-B*52-C*04-DRB1*12  Myanmar Rakhine 1.042048
 227  A*33-B*52-C*07-DRB1*04  Myanmar Rakhine 1.042048
 228  B*52:01:01-C*07:02:01-DRB1*14:04  China Jingpo Minority 1.0420105
 229  B*52:01:01-C*07:02:01-DRB1*15:02:02  China Jingpo Minority 1.0420105
 230  B*52:01:01-DRB1*14:04  China Jingpo Minority 1.0420105
 231  B*52:01:01-DRB1*15:02:02  China Jingpo Minority 1.0420105
 232  A*02-B*52-DRB1*04-DQB1*03:02  Mexico Quintana Roo, Cancun 1.041748
 233  A*24:02-B*52:01-C*15:39-DRB1*08:02  Brazil Vale do Ribeira Quilombos 1.0417144
 234  A*01:01-B*52:01-DRB1*15:02  Mexico Oaxaca Jamiltepec Mixtec 1.040096
 235  A*01:02-B*52:01-DRB1*15:01-DQB1*06:01  Iran Tabriz Azeris 1.030997
 236  A*02:01-B*52:01-DRB1*04:01-DQB1*06:01  Iran Tabriz Azeris 1.030997
 237  A*02-B*52-DRB1*15-DQB1*06  Mexico Nayarit, Tepic 1.030997
 238  A*11:01-B*52:01-DRB1*04:01-DQB1*03:01  Iran Tabriz Azeris 1.030997
 239  A*33:01-B*52:01-DRB1*15:01-DQB1*06:01  Iran Tabriz Azeris 1.030997
 240  A*02:01-B*52:01-DRB1*15:02  Israel Poland Jews 1.030013,871
 241  A*02-B*52-DRB1*04-DQB1*03:02  Mexico Veracruz Rural 1.0166539
 242  A*11:01-B*52:01-C*07:02-DRB1*14:04-DQB1*05:03  India Northeast UCBB 1.0135296
 243  A*02-B*52-DRB1*15-DQB1*06  Mexico Sonora, Hermosillo 1.010199
 244  A*03-B*52-DRB1*11-DQB1*06  Iraq Arabs 1.0100149
 245  A*11:01-B*52:01-DRB1*15:02  Israel USA Jews 1.01006,058
 246  A*01:01-B*52:01-C*12:02-DRB1*15:02:01-DQB1*06:01  England North West 1.0000298
 247  A*01:01-B*52:01-DRB1*15:02  Armenia combined Regions 1.0000100
 248  A*02-B*52-DRB1*03:01-DQB1*02  Mexico Baja California Rural 1.000050
 249  A*02-B*52-DRB1*04-DQB1*03:02  Mexico Quintana Roo Rural 1.000050
 250  A*11:01:01-B*52:01:01-C*07:02:01  South African Indian population 1.000050
 251  A*11:03-B*52:01:01-C*07:02:01  South African Indian population 1.000050
 252  A*11-B*52-C*07  Italy East Sicily 1.000050
 253  A*11-B*52-C*12-DRB1*15-DQB1*06  Iraq Kurdistan Region 1.0000209
 254  A*11-B*52-DRB1*15-DQB1*06  Mexico Quintana Roo Rural 1.000050
 255  A*11-B*52-DRB1*15-DQB1*06  Mexico Baja California Rural 1.000050
 256  A*23:01:01-B*52:01:01-C*12:02:02  South African Mixed ancestry 1.000050
 257  A*24:07-B*52:01:01-C*03:04:01  South African Mixed ancestry 1.000050
 258  A*24-B*52-DRB1*08-DQB1*04  Mexico Baja California Rural 1.000050
 259  A*30-B*52-C*04  Italy East Sicily 1.000050
 260  A*31:01:02-B*52:01:01-DRB1*15:02:01  Portugal Center 1.000050
 261  A*32-B*52-DRB1*15-DQB1*06  Mexico Baja Californa, Mexicali 1.0000100
 262  A*33:03:01-B*52:01:01-C*14:02:01  South African Indian population 1.000050
 263  A*34-B*52-DRB1*04  Philippines National Capital Region 1.000051
 264  A*68:01:02-B*52:01:01-C*12:02:02  South African Indian population 1.000050
 265  A*68-B*52-C*04  Italy East Sicily 1.000050
 266  A*80-B*52-C*16  Italy East Sicily 1.000050
 267  A*02-B*52-DRB1*14-DQB1*03:01  Mexico Oaxaca, Oaxaca city 0.9934151
 268  A*02:06:01-B*52:01:01  China Jingpo Minority 0.9900105
 269  A*11:01-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  India West UCBB 0.98925,829
 270  A*24-B*52-DRB1*14-DQB1*03:01  Mexico Mexico City Metropolitan Area Rural 0.9868150
 271  A*11-B*52-DRB1*15  Iran pop 4 0.9804855
 272  A*24:02-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  USA Asian pop 2 0.97701,772
 273  A*32-B*52-DRB1*15-DQB1*06  Mexico Sinaloa, Culiacán 0.9709103
 274  A*02-B*52-DRB1*14-DQB1*03:01  Mexico Durango, Durango city 0.9677153
 275  A*01-B*52-DRB1*15-DQB1*06  Mexico Mexico City South 0.961552
 276  A*23-B*52-DRB1*07-DQB1*02  Mexico Mexico City South 0.961552
 277  A*32:01-B*52:01-C*12:02-DRB1*15:01-DQA1*01:02-DQB1*06:01  United Arab Emirates Abu Dhabi 0.960052
 278  A*02-B*52-DRB1*04:04-DQB1*03:02  Mexico San Vicente Tancuayalab Teenek/Huastecos 0.940053
 279  A*02-B*52-DRB1*14:06-DQB1*03:04  Mexico San Vicente Tancuayalab Teenek/Huastecos 0.940053
 280  A*24-B*52-DRB1*04:07-DQB1*03:02  Mexico San Vicente Tancuayalab Teenek/Huastecos 0.940053
 281  A*24-B*52-DRB1*08:02-DQB1*04:02  Mexico San Vicente Tancuayalab Teenek/Huastecos 0.940053
 282  A*31-B*52-DRB1*04:04-DQB1*03:02  Mexico San Vicente Tancuayalab Teenek/Huastecos 0.940053
 283  A*68-B*52-DRB1*04:08-DQB1*03:02  Mexico San Vicente Tancuayalab Teenek/Huastecos 0.940053
 284  A*68-B*52-DRB1*14:02-DQB1*03:02  Mexico San Vicente Tancuayalab Teenek/Huastecos 0.940053
 285  A*02:01-B*52:01-DRB1*15:02  Israel Argentina Jews 0.93604,307
 286  A*02:01-B*52:01-DRB1*15:02  Israel USA Jews 0.93406,058
 287  A*01-B*52-C*12-DRB1*14  Myanmar Shan 0.926054
 288  A*11:01-B*52:01-DRB1*15:02  Israel YemenJews 0.926015,542
 289  A*11-B*52-C*07-DRB1*14  Myanmar Shan 0.926054
 290  A*02-B*52-DRB1*14-DQB1*03:01  Mexico Chihuahua, Ciudad Juarez 0.9259106
 291  A*11:01-B*52:01-DRB1*15:02  Israel Arab pop 2 0.910012,301
 292  A*02:01-B*52:01-DRB1*15:02  Israel Ashkenazi Jews pop 3 0.90904,625
 293  A*02-B*52-C*07-DRB1*14  Myanmar Chin 0.909055
 294  A*02-B*52-C*12-DRB1*12  Myanmar Chin 0.909055
 295  A*02-B*52-C*12-DRB1*12  Myanmar Kayah 0.909055
 296  A*11-B*52-C*07-DRB1*09  Myanmar Kayah 0.909055
 297  A*11-B*52-C*07-DRB1*14  Myanmar Kayah 0.909055
 298  A*11-B*52-C*12-DRB1*14  Myanmar Chin 0.909055
 299  A*11-B*52-C*12-DRB1*15  Myanmar Chin 0.909055
 300  A*24-B*52-C*07-DRB1*04  Myanmar Kayah 0.909055

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 201 to 300 (from 5,642) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 57  


   

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.

support@allelefrequencies.net


Valid XHTML 1.0 Transitional