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 : 
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Sample Size:      Sample Year:     Loci Tested: 
Displaying 201 to 300 (from 7,533) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 76  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 201  A*31:01:02-B*15:01:01-C*12:02:02-DRB1*11:01:01-DQB1*03:01:01  China Zhejiang Han 0.02881,734
 202  A*31:01:02-B*15:01-DRB1*04:03-DQB1*03:02  USA South Dakota Lakota Sioux 2.2000302
 203  A*31:01:02-B*15:01-DRB1*08:02-DQB1*04:02  Peru Titikaka Lake Uros 0.4800105
 204  A*31:01:02-B*15:01-DRB1*09:01-DQB1*03:03  Peru Titikaka Lake Uros 0.9300105
 205  A*31:01:02-B*15:02:01-C*08:01:01-DRB1*04:04:01-DQB1*03:02:01  China Zhejiang Han 0.02881,734
 206  A*31:01:02-B*15:02:01-C*08:01:01-DRB1*11:01:01-DPB1*03:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00655,266
 207  A*31:01:02-B*15:02:01-C*08:01:01-DRB1*12:02:01-DPB1*21:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.04845,266
 208  A*31:01:02-B*15:02:01-C*08:01:01-DRB1*15:01:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00825,266
 209  A*31:01:02-B*15:03:01-C*12:02:02-DRB1*15:02:01-DQB1*06:02:01-DPA1*02:01:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 210  A*31:01:02-B*15:04:01-C*03:03:01-DRB1*14:02:01-DQB1*04:02:01-DPA1*01:03:01-DPB1*04:02:01  Brazil Barra Mansa Rio State Black 2.381073
 211  A*31:01:02-B*15:04:01-C*03:03:01-DRB1*15:03:01-DQB1*06:02:01-DPA1*01:03:01-DPB1*416:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 212  A*31:01:02-B*15:05:01-C*03:03:01-DRB1*14:04:01-DQB1*05:03:01  India Andhra Pradesh Telugu Speaking 0.2688186
 213  A*31:01:02-B*15:05:01-C*07:01:01-DRB1*15:02:01-DQB1*05:03:01  India Karnataka Kannada Speaking 0.2870174
 214  A*31:01:02-B*15:05:01-C*15:02:01-DRB1*15:02:01-DQB1*03:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 215  A*31:01:02-B*15:07:01-C*03:03:01-DRB1*04:03:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00655,266
 216  A*31:01:02-B*15:07:01-C*03:03:01-DRB1*08:03:02-DQB1*06:01:01  China Zhejiang Han 0.02881,734
 217  A*31:01:02-B*15:08:01-C*01:02:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.002123,595
 218  A*31:01:02-B*15:08:01-C*01:02:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.002223,595
 219  A*31:01:02-B*15:08:01-C*01:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.004223,595
 220  A*31:01:02-B*15:08:01-C*01:02:01-DRB1*08:02:01-DQB1*04:02:01  Poland BMR 0.002123,595
 221  A*31:01:02-B*15:08:01-C*01:02:01-DRB1*09:01:02-DQB1*03:02:01  Poland BMR 0.002123,595
 222  A*31:01:02-B*15:08:01-C*01:02:01-DRB1*13:01:01-DQB1*03:02:01  Poland BMR 0.002123,595
 223  A*31:01:02-B*15:08:01-C*01:02:01-DRB1*13:03:01-DQB1*03:02:01  Poland BMR 0.002123,595
 224  A*31:01:02-B*15:08:01-C*01:02:01-DRB1*15:07:01-DQB1*03:02:01  Poland BMR 0.002123,595
 225  A*31:01:02-B*15:08-C*01:02:01-DRB1*13:01:01-DQB1*06:03:01-DPB1*03:01:01  Saudi Arabia pop 6 (G) 0.314128,927
 226  A*31:01:02-B*15:09-C*04:01:01-DRB1*08:02:01-DQB1*04:02:01  Costa Rica Central Valley Mestizo (G) 0.2262221
 227  A*31:01:02-B*15:10:01-C*03:04:02-DRB1*13:02:01-DQB1*06:04:01  Poland BMR 0.001423,595
 228  A*31:01:02-B*15:11:01-C*03:03:01-DRB1*09:01:02-DQB1*03:03:02  China Zhejiang Han 0.04941,734
 229  A*31:01:02-B*15:11:01-C*03:03:01-DRB1*12:01:01-DPB1*02:01:02  Hong Kong Chinese HKBMDR HLA 11 loci 0.00905,266
 230  A*31:01:02-B*15:11:01-C*03:03:01-DRB1*15:01:01-DPB1*02:01:02  Hong Kong Chinese HKBMDR HLA 11 loci 0.00865,266
 231  A*31:01:02-B*15:11:01-C*07:04:01-DRB1*09:01:02-DQB1*03:03:02  China Zhejiang Han 0.02881,734
 232  A*31:01:02-B*15:15-C*01:02:01-DRB1*08:02:01  Nicaragua Mestizo (G) 0.3226155
 233  A*31:01:02-B*15:15-C*01:02:01-DRB1*16:02:01  Nicaragua Mestizo (G) 0.3226155
 234  A*31:01:02-B*15:17:01-C*07:01:01-DRB1*13:02:01-DQB1*06:04:01  India Kerala Malayalam speaking 0.1400356
 235  A*31:01:02-B*15:17:01-C*07:01:02-DRB1*04:02:01-DQB1*02:01:01  Poland BMR 0.002123,595
 236  A*31:01:02-B*15:17:01-C*07:01:02-DRB1*11:04:01-DQB1*03:01:01  Poland BMR 0.002123,595
 237  A*31:01:02-B*15:17:01-C*07:01:02-DRB1*13:02:01-DQB1*06:04:01  Poland BMR 0.002623,595
 238  A*31:01:02-B*15:18:01-C*07:02:01-DRB1*04:05:01-DQB1*04:01:01  China Zhejiang Han 0.02881,734
 239  A*31:01:02-B*15:18:01-C*07:04:01-DRB1*04:01:01-DQB1*03:01:01  China Zhejiang Han 0.02881,734
 240  A*31:01:02-B*15:18:01-C*07:04:01-DRB1*09:01:02-DQB1*03:03:02  China Zhejiang Han 0.02881,734
 241  A*31:01:02-B*15:18:01-C*07:04:01-DRB1*14:05:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00575,266
 242  A*31:01:02-B*15:18:01-C*08:01:01-DRB1*04:04:01-DQB1*03:02:01  China Zhejiang Han 0.02881,734
 243  A*31:01:02-B*15:18:01-C*08:01:01-DRB1*08:02:01-DQB1*04:02:01  China Zhejiang Han 0.02881,734
 244  A*31:01:02-B*15:18:01-C*08:01:01-DRB1*09:01:02-DPB1*02:01:02  Hong Kong Chinese HKBMDR HLA 11 loci 0.00475,266
 245  A*31:01:02-B*15:18:01-C*08:41-DRB1*15:01:01-DQB1*06:02:01  China Zhejiang Han 0.02881,734
 246  A*31:01:02-B*15:27:01-C*04:01:01-DRB1*04:05:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00935,266
 247  A*31:01:02-B*15:27:01-C*04:01:01-DRB1*04:06:01-DQB1*03:02:01  China Zhejiang Han 0.08651,734
 248  A*31:01:02-B*18:01:01-C*02:02:02-DRB1*13:01:01-DQB1*03:02:01-DPA1*01:03:01-DPB1*11:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 249  A*31:01:02-B*18:01:01-C*05:01:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.002123,595
 250  A*31:01:02-B*18:01:01-C*05:01:01-DRB1*15:03:01-DQB1*06:02:01-DPA1*01:03:01-DPB1*105:01:01  Brazil Rio de Janeiro Black 1.470668
 251  A*31:01:02-B*18:01:01-C*07:01:01  England Blood Donors of Mixed Ethnicity 0.0963519
 252  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*01:01:01-DQB1*04:02:01  Poland BMR 0.000975023,595
 253  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*01:01:01-DQB1*05:04  Poland BMR 0.002123,595
 254  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*01:01:01-DQB1*06:02:01  Poland BMR 0.002123,595
 255  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.005823,595
 256  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*04:03:01-DQB1*03:02:01  India Kerala Malayalam speaking 0.1400356
 257  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*04:03:01-DQB1*03:02:01  India Karnataka Kannada Speaking 0.2870174
 258  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*04:07:01-DQB1*03:01:01  Poland BMR 0.002423,595
 259  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*04:07:01-DQB1*05:02:01  Poland BMR 0.002123,595
 260  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.008523,595
 261  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*07:01:01-DQB1*05:02:01  Poland BMR 0.002023,595
 262  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.005223,595
 263  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*08:01:01-DQB1*04:02:01  Spain, Canary Islands, Gran canaria island 0.2300215
 264  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*10:01:01-DQB1*02:02:01  Poland BMR 0.002123,595
 265  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*10:01:01-DQB1*05:01:01  Poland BMR 0.005823,595
 266  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.008023,595
 267  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*11:03:01-DQB1*03:01:01  Poland BMR 0.000187723,595
 268  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*11:04:01-DQB1*03:01:01  Poland BMR 0.010823,595
 269  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*13:01:01-DQB1*06:03:01  India Andhra Pradesh Telugu Speaking 0.2688186
 270  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.000582523,595
 271  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*13:02:01-DQB1*06:04:01  Poland BMR 0.001723,595
 272  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*14:04:01-DQB1*05:03:01  India Kerala Malayalam speaking 0.1400356
 273  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*14:54:01-DQB1*05:03:01  Poland BMR 0.003723,595
 274  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*15:01:01-DQB1*06:01:01  India Karnataka Kannada Speaking 0.2870174
 275  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.035923,595
 276  A*31:01:02-B*18:01:01-C*07:01:01-DRB1*16:01:01-DQB1*05:02:01  Poland BMR 0.007223,595
 277  A*31:01:02-B*18:01:01-C*12:03:01-DRB1*11:04:01-DQB1*02:01:01  Poland BMR 0.002123,595
 278  A*31:01:02-B*18:01:01-C*12:03:01-DRB1*11:04:01-DQB1*05:02:01  Poland BMR 0.001923,595
 279  A*31:01:02-B*18:01:01-C*12:03:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.005523,595
 280  A*31:01:02-B*18:01:01-C*12:03:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.002223,595
 281  A*31:01:02-B*27:02:01-C*01:02:01-DRB1*13:03:01-DQB1*03:01:01  Poland BMR 0.001923,595
 282  A*31:01:02-B*27:02:01-C*02:02:02-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.002123,595
 283  A*31:01:02-B*27:02:01-C*02:02:02-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.002123,595
 284  A*31:01:02-B*27:02:01-C*02:02:02-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.002023,595
 285  A*31:01:02-B*27:02:01-C*02:02:02-DRB1*16:01:01-DQB1*05:02:01  Poland BMR 0.014923,595
 286  A*31:01:02-B*27:02:01-C*06:02:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.002123,595
 287  A*31:01:02-B*27:02:01-C*07:04:01-DRB1*04:07:01-DQB1*03:01:01  Poland BMR 0.002123,595
 288  A*31:01:02-B*27:04:01-C*12:02:02-DRB1*12:02:01-DQB1*03:01:01  China Zhejiang Han 0.02881,734
 289  A*31:01:02-B*27:05:02-C*01:02:01-DRB1*01:01:01-DQB1*02:01:01  Poland BMR 0.000692323,595
 290  A*31:01:02-B*27:05:02-C*01:02:01-DRB1*01:01:01-DQB1*02:02:01  Poland BMR 0.002123,595
 291  A*31:01:02-B*27:05:02-C*01:02:01-DRB1*01:01:01-DQB1*03:01:01  Poland BMR 0.002623,595
 292  A*31:01:02-B*27:05:02-C*01:02:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.011223,595
 293  A*31:01:02-B*27:05:02-C*01:02:01-DRB1*01:01:01-DQB1*06:02:01  Poland BMR 0.001323,595
 294  A*31:01:02-B*27:05:02-C*01:02:01-DRB1*03:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*03:01:01  Brazil Rio de Janeiro Black 1.470668
 295  A*31:01:02-B*27:05:02-C*01:02:01-DRB1*09:01:02-DQB1*03:03:02  Poland BMR 0.006223,595
 296  A*31:01:02-B*27:05:02-C*01:02:01-DRB1*11:04:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Black 1.470668
 297  A*31:01:02-B*27:05:02-C*01:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.000637023,595
 298  A*31:01:02-B*27:05:02-C*01:02:01-DRB1*16:01:01-DQB1*05:02:01  Poland BMR 0.002123,595
 299  A*31:01:02-B*27:05:02-C*01:127-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.002123,595
 300  A*31:01:02-B*27:05:02-C*02:02:02  England Blood Donors of Mixed Ethnicity 0.3332519

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 7,533) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 76  


   

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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