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 201 to 300 (from 1,273) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 13  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 201  DRB1*04-DQA1*03:01-DQB1*03:01  Russia Kostroma Region 1.6000126
 202  DRB1*04-DQA1*03:01-DQB1*03:04  Russia Smolensk 1.6000156
 203  DRB1*09:01-DQA1*03:01-DQB1*03:03  USA San Francisco Caucasian 1.6000220
 204  DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*02:01  Hong Kong Chinese HKBMDR. DQ and DP 1.58011,064
 205  A*02-B*15-DRB1*04:01-DRB4*01:03-DQA1*03:01-DQB1*03:02  Spain Murcia 1.5000173
 206  DRB1*04:02-DQA1*03:01-DQB1*03:02  Mexico Guanajuato and Jalisco Mestizo 1.5000101
 207  DRB1*04:03-DQA1*03:01-DQB1*03:02  Mexico Guanajuato and Jalisco Mestizo 1.5000101
 208  DRB1*04:03-DQA1*03:01-DQB1*03:02  Morocco Souss Region 1.500098
 209  DRB1*04:04-DQA1*03:01-DQB1*03:02  Australia New South Wales Aborigine 1.5000177
 210  DRB1*04:05-DQA1*03:01-DQB1*03:02  Mexico Guanajuato and Jalisco Mestizo 1.5000101
 211  DRB1*04:06-DQA1*03:01/03:02-DQB1*04:02  Ethiopia Amhara 1.500098
 212  DRB1*04-DQA1*03:01-DQB1*03:01  Belarus Vitebsk Region 1.500070
 213  DRB1*09:01-DQA1*03:01-DQB1*03:01  India Northeast Mech 1.500063
 214  DRB1*12:01-DQA1*03:01-DQB1*03:02  Japan pop 2 1.5000916
 215  A*02:01-B*35:12-C*04:01-DRB1*04:07-DQA1*03:01-DQB1*03:02  Mexico Tixcacaltuyub Maya 1.492567
 216  A*02:06-B*35:01-C*07:02-DRB1*04:07-DQA1*03:01-DQB1*03:02  Mexico Tixcacaltuyub Maya 1.492567
 217  A*24:02-B*35:12-C*04:01-DRB1*04:07-DQA1*03:01-DQB1*03:02  Mexico Tixcacaltuyub Maya 1.492567
 218  A*24:02-B*35:20-C*03:04-DRB1*04:07-DQA1*03:01-DQB1*03:02  Mexico Tixcacaltuyub Maya 1.492567
 219  A*24:02-B*40:02-C*03:05-DRB1*04:07-DQA1*03:01-DQB1*03:02  Mexico Tixcacaltuyub Maya 1.492567
 220  A*31:01-B*35:01-C*07:02-DRB1*04:03-DQA1*03:01-DQB1*03:02  Mexico Tixcacaltuyub Maya 1.492567
 221  A*68:03-B*35:01-C*07:02-DRB1*04:07-DQA1*03:01-DQB1*03:02  Mexico Tixcacaltuyub Maya 1.492567
 222  A*68:03-B*35:43-C*01:02-DRB1*04:03-DQA1*03:01-DQB1*03:02  Mexico Tixcacaltuyub Maya 1.492567
 223  DRB1*04:01-DQA1*03:01-DQB1*03:01  Slovenia pop 2 1.4000140
 224  DRB1*04:02-DQA1*03:01-DQB1*03:02  USA San Francisco Caucasian 1.4000220
 225  DRB1*04:04-DQA1*03:01-DQB1*03:02  Slovenia pop 2 1.4000140
 226  DRB1*04:06-DQA1*03:01-DQB1*03:02-DPB1*05:01  China Canton Han 1.4000264
 227  DRB1*04:07-DQA1*03:01-DQB1*03:01  Slovenia pop 2 1.4000140
 228  DRB1*09:01:02-DQA1*03:01/03:02-DQB1*03:03  England pop 6 1.4000177
 229  DRB1*09:01-DRB4*01:01-DQA1*03:01-DQB1*03:03-DPB1*04:01  USA San Francisco Caucasian 1.4000220
 230  DRB1*09:01-DRB4*01:01-DQA1*03:01-DQB1*03:03-DPB1*04:01  USA San Francisco Caucasian 1.4000220
 231  A*02:06-B*35:01-C*07:02-DRB1*04:07-DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 1.3761218
 232  A*02:06-B*40:02-C*03:04-DRB1*04:11-DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*02:01  Mexico Chiapas Lacandon Mayans 1.3761218
 233  DRB1*04:06-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*05:01  China Zhejiang Han pop 2 1.3584833
 234  DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*05:01  China Zhejiang Han pop 2 1.3522833
 235  A*24:02-B*40:02-C*07:01-DRB1*04:04-DQA1*03:01-DQB1*03:01  Brazil Puyanawa 1.3333150
 236  A*31:01-B*39:01-C*07:02-DRB1*04:11-DQA1*03:01-DQB1*03:02  Brazil Puyanawa 1.3333150
 237  A*03-B*07-DRB1*04-DQA1*03:01-DQB1*03:02  Georgia Svaneti Region Svan 1.300080
 238  A*68:01-B*58:02-C*06:02-DRB1*07:01-DQA1*03:01-DQB1*02:02-DPB1*04:02  South Africa Worcester 1.3000159
 239  DRB1*04:01-DRB4*01:01-DQA1*03:01-DQB1*03:02-DPB1*04:01  USA San Francisco Caucasian 1.3000220
 240  DRB1*04:01-DRB4*01:01-DQA1*03:01-DQB1*03:02-DPB1*04:01  USA San Francisco Caucasian 1.3000220
 241  DRB1*04:03-DQA1*03:01-DQB1*03:02  Mexico Nuevo Leon Mestizo 1.300040
 242  DRB1*04:04-DQA1*03:01-DQB1*03:02  Mexico Nuevo Leon Mestizo 1.300040
 243  DRB1*04:07-DQA1*03:01-DQB1*03:01  Mexico Highlands Mestizos 1.3000160
 244  A*02:01-B*38:01-C*12:03-DRB1*04:02-DQA1*03:01-DQB1*03:02  Kosovo 1.2100124
 245  A*02:13-B*39:05-C*07:02-DRB1*04:11-DQA1*03:01:01-DQB1*03:02-DPA1*01-DPB1*14:01  Venezuela Sierra de Perija Yucpa 1.200073
 246  A*11:01-B*15:01-C*04:01-DRB1*04:06-DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*02:01  Japan pop 17 1.20003,078
 247  A*24:02-B*35:12-C*04:01-DRB1*04:11-DQA1*03:01:01-DQB1*03:02-DPA1*01-DPB1*04:02  Venezuela Sierra de Perija Yucpa 1.200073
 248  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
 249  A*68:01-B*40:04-C*03:02/03:04-DRB1*04:03-DQA1*03:01:01-DQB1*03:01-DPA1*02-DPB1*04:02  Venezuela Sierra de Perija Yucpa 1.200073
 250  DRB1*03:01-DQA1*03:01-DQB1*02:01  India Northeast Sunni 1.2000188
 251  DRB1*04:04-DQA1*03:01/03:02-DQB1*03:02  Ethiopia Oromo 1.200083
 252  DRB1*04:06-DQA1*03:01/03:02-DQB1*04:02  Ethiopia Oromo 1.200083
 253  DRB1*04:06-DQA1*03:01-DQB1*03:02-DPB1*05:01  South Korea pop 2 1.2000207
 254  DRB1*04:06-DQA1*03:01-DQB1*03:02-DPB1*05:01  South Korea pop 1 1.2000324
 255  DRB1*04-DQA1*03:01-DQB1*03:01  Russia Arkhangelsk 1.200081
 256  DRB1*04:01-DQA1*03:01-DQB1*03:02  Spain Las Alpujarras 1.180085
 257  DRB1*09:01-DQA1*03:01-DQB1*03:03  Spain Las Alpujarras 1.180085
 258  A*24:02-B*39:05-C*07:02-DRB1*04:07-DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 1.1468218
 259  DRB1*04:01-DQA1*03:01-DQB1*03:01  Japan pop 2 1.1000916
 260  DRB1*04:02-DQA1*03:01-DQB1*03:02  Italy Sardinia Sorgono 1.100093
 261  DRB1*04:02-DRB4*01:01-DQA1*03:01-DQB1*03:02-DPB1*04:01  USA San Francisco Caucasian 1.1000220
 262  DRB1*04:02-DRB4*01:01-DQA1*03:01-DQB1*03:02-DPB1*04:01  USA San Francisco Caucasian 1.1000220
 263  DRB1*04:03-DQA1*03:01-DQB1*03:02  Italy Sardinia Lanusei 1.100087
 264  DRB1*04:04-DQA1*03:01-DQB1*03:01  Australia New South Wales Aborigine 1.1000177
 265  DRB1*04:04-DQA1*03:01-DQB1*04:02  Australia New South Wales Aborigine 1.1000177
 266  DRB1*04:05-DQA1*03:01-DQB1*02:01  Italy Sardinia Lanusei 1.100087
 267  DRB1*04:08-DQA1*03:01-DQB1*04:01  Australia New South Wales Aborigine 1.1000177
 268  DRB1*04:08-DQA1*03:01-DQB1*04:02  Australia New South Wales Aborigine 1.1000177
 269  DRB1*09:01:02-DQA1*03:01-DQB1*03:03  Australia New South Wales Aborigine 1.1000177
 270  A*68:03-B*35:43-C*01:02-DRB1*04:07-DQA1*03:01-DQB1*03:02-DPB1*04:02  Nicaragua Managua 1.0823339
 271  A*02:01-B*15:01-C*01:02-DRB1*04:11-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 272  A*02:01-B*35:01-C*04:01-DRB1*04:07-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 273  A*02:01-B*35:01-C*07:02-DRB1*04:07-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 274  A*02:01-B*35:17-C*04:01-DRB1*04:10-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 275  A*02:01-B*40:02-C*03:05-DRB1*04:04-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 276  A*02:06-B*35:01-C*04:01-DRB1*04:03-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 277  A*02:06-B*35:01-C*07:02-DRB1*04:07-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 278  A*02:06-B*39:05-C*07:02-DRB1*04:07-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 279  A*02:06-B*40:02-C*03:04-DRB1*04:11-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 280  A*24:02-B*15:01-C*01:02-DRB1*04:11-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 281  A*24:02-B*35:01-C*07:02-DRB1*04:07-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 282  A*24:02-B*35:17-C*03:03-DRB1*04:11-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 283  A*24:02-B*35:17-C*04:01-DRB1*04:03-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 284  A*24:02-B*39:05-C*07:02-DRB1*04:07-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 285  A*24:02-B*40:02-C*03:04-DRB1*04:03-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 286  A*24:02-B*40:08-C*03:04-DRB1*04:07-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 287  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
 288  A*31:01-B*15:01-C*01:02-DRB1*04:03-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 289  A*31:01-B*15:01-C*01:02-DRB1*04:11-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 290  A*31:01-B*35:01-C*04:01-DRB1*04:04-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 291  A*31:01-B*35:01-C*07:02-DRB1*04:07-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 292  A*31:01-B*40:02-C*03:04-DRB1*04:04-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 293  A*31:01-B*40:02-C*03:05-DRB1*04:07-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 294  A*31:01-B*40:02-C*03:05-DRB1*04:17-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 295  A*31:01-B*40:02-C*04:01-DRB1*04:03-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 296  A*31:01-B*40:02-C*15:02-DRB1*04:07-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 297  A*31:01-B*48:01-C*08:03-DRB1*04:04-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 298  A*31:01-B*48:01-C*15:02-DRB1*04:03-DQA1*03:01-DQB1*03:02  Mexico Chichen Itza Maya (prehispanic) 1.063847
 299  A*68:01-B*15:01-C*01:02-DRB1*04:04-DQA1*03:01-DQB1*03:03  Mexico Chichen Itza Maya (prehispanic) 1.063847
 300  A*68:01-B*35:01-C*04:01-DRB1*04:07-DQA1*03:01-DQB1*03:03  Mexico Chichen Itza Maya (prehispanic) 1.063847

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 1,273) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 13  


   

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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