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 301 to 400 (from 424) records   Pages: 1 2 3 4 5 of 5  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 301  A*02:01:01-B*48:01:01-C*08:03:01-DRB1*04:03:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00575,266
 302  A*02:06-B*48:01-C*08:03-DRB1*09:01  Hong Kong Chinese BMDR 0.00567,595
 303  B*48:01-C*08:03  China Hubei Han 0.00523,732
 304  A*11:01-B*48:01-C*08:03-DRB1*11:01  Hong Kong Chinese BMDR 0.00517,595
 305  A*02:01-B*15:01-C*08:03-DRB1*11:01  Japan pop 16 0.005018,604
 306  A*02:01-B*15:01-C*08:03-DRB1*14:06  Japan pop 16 0.005018,604
 307  A*02:01-B*15:01-C*08:03-DRB1*15:01  Japan pop 16 0.005018,604
 308  A*02:01-B*48:01-C*08:03-DRB1*04:10  Japan pop 16 0.005018,604
 309  A*02:01-B*48:01-C*08:03-DRB1*08:03  Japan pop 16 0.005018,604
 310  A*02:01-B*48:01-C*08:03-DRB1*11:01  Japan pop 16 0.005018,604
 311  A*02:01-B*48:01-C*08:03-DRB1*12:01  Japan pop 16 0.005018,604
 312  A*02:01-B*48:01-C*08:03-DRB1*14:05  Japan pop 16 0.005018,604
 313  A*02:01-B*48:01-C*08:03-DRB1*14:54  Japan pop 16 0.005018,604
 314  A*02:01-B*48:01-C*08:03-DRB1*15:02  Japan pop 16 0.005018,604
 315  A*02:01-B*54:01-C*08:03-DRB1*04:05  Japan pop 16 0.005018,604
 316  A*02:06-B*15:01-C*08:03-DRB1*14:54  Japan pop 16 0.005018,604
 317  A*02:06-B*48:01-C*08:03-DRB1*08:03  Japan pop 16 0.005018,604
 318  A*02:06-B*48:01-C*08:03-DRB1*12:02  Japan pop 16 0.005018,604
 319  A*02:06-B*48:01-C*08:03-DRB1*14:05  Japan pop 16 0.005018,604
 320  A*02:06-B*55:02-C*08:03-DRB1*15:01  Japan pop 16 0.005018,604
 321  A*11:01:01-B*48:01:01-C*08:03:01-DRB1*04:03:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00505,266
 322  A*11:01-B*15:01-C*08:03-DRB1*09:01  Japan pop 16 0.005018,604
 323  A*11:01-B*15:01-C*08:03-DRB1*11:01  Japan pop 16 0.005018,604
 324  A*11:01-B*48:01-C*08:03-DRB1*04:05  Japan pop 16 0.005018,604
 325  A*11:01-B*48:01-C*08:03-DRB1*04:07  Japan pop 16 0.005018,604
 326  A*11:01-B*48:01-C*08:03-DRB1*04:10  Japan pop 16 0.005018,604
 327  A*11:01-B*48:01-C*08:03-DRB1*08:03  Japan pop 16 0.005018,604
 328  A*11:01-B*48:01-C*08:03-DRB1*09:01  Japan pop 16 0.005018,604
 329  A*11:01-B*48:01-C*08:03-DRB1*12:01  Japan pop 16 0.005018,604
 330  A*11:01-B*48:01-C*08:03-DRB1*14:06  Japan pop 16 0.005018,604
 331  A*11:02-B*48:01-C*08:03-DRB1*09:01  Japan pop 16 0.005018,604
 332  A*24:02-B*15:01-C*08:03-DRB1*14:06  Japan pop 16 0.005018,604
 333  A*24:02-B*40:01-C*08:03-DRB1*15:02  Japan pop 16 0.005018,604
 334  A*24:02-B*40:02-C*08:03-DRB1*14:54  Japan pop 16 0.005018,604
 335  A*24:02-B*40:06-C*08:03-DRB1*08:02  Japan pop 16 0.005018,604
 336  A*24:02-B*40:06-C*08:03-DRB1*09:01  Japan pop 16 0.005018,604
 337  A*24:02-B*48:01-C*08:03-DRB1*04:03  Japan pop 16 0.005018,604
 338  A*24:02-B*48:01-C*08:03-DRB1*11:01  Japan pop 16 0.005018,604
 339  A*24:02-B*48:01-C*08:03-DRB1*12:01  Japan pop 16 0.005018,604
 340  A*24:02-B*48:01-C*08:03-DRB1*14:05  Japan pop 16 0.005018,604
 341  A*24:02-B*48:01-C*08:03-DRB1*14:07  Japan pop 16 0.005018,604
 342  A*24:02-B*54:01-C*08:03-DRB1*01:01  Japan pop 16 0.005018,604
 343  A*24:02-B*54:01-C*08:03-DRB1*12:01  Japan pop 16 0.005018,604
 344  A*24:02-B*54:21-C*08:03-DRB1*08:03  Japan pop 16 0.005018,604
 345  A*26:01-B*15:01-C*08:03-DRB1*04:05  Japan pop 16 0.005018,604
 346  A*26:01-B*40:01-C*08:03-DRB1*14:06  Japan pop 16 0.005018,604
 347  A*26:01-B*48:01-C*08:03-DRB1*04:04  Japan pop 16 0.005018,604
 348  A*26:01-B*48:01-C*08:03-DRB1*08:03  Japan pop 16 0.005018,604
 349  A*26:01-B*48:01-C*08:03-DRB1*09:01  Japan pop 16 0.005018,604
 350  A*26:01-B*48:01-C*08:03-DRB1*11:01  Japan pop 16 0.005018,604
 351  A*26:01-B*48:01-C*08:03-DRB1*12:01  Japan pop 16 0.005018,604
 352  A*26:01-B*48:01-C*08:03-DRB1*13:02  Japan pop 16 0.005018,604
 353  A*26:01-B*48:01-C*08:03-DRB1*15:02  Japan pop 16 0.005018,604
 354  A*26:01-B*54:01-C*08:03-DRB1*04:05  Japan pop 16 0.005018,604
 355  A*26:02-B*48:01-C*08:03-DRB1*15:01  Japan pop 16 0.005018,604
 356  A*26:03-B*15:01-C*08:03-DRB1*04:05  Japan pop 16 0.005018,604
 357  A*26:03-B*15:01-C*08:03-DRB1*09:01  Japan pop 16 0.005018,604
 358  A*26:03-B*35:01-C*08:03-DRB1*12:01  Japan pop 16 0.005018,604
 359  A*26:03-B*48:01-C*08:03-DRB1*09:01  Japan pop 16 0.005018,604
 360  A*26:05-B*48:01-C*08:03-DRB1*15:01  Japan pop 16 0.005018,604
 361  A*31:01-B*48:01-C*08:03-DRB1*04:04  Japan pop 16 0.005018,604
 362  A*31:01-B*48:01-C*08:03-DRB1*04:05  Japan pop 16 0.005018,604
 363  A*31:01-B*54:01-C*08:03-DRB1*04:05  Japan pop 16 0.005018,604
 364  A*33:03-B*48:01-C*08:03-DRB1*09:01  Japan pop 16 0.005018,604
 365  A*33:03-B*54:01-C*08:03-DRB1*04:05  Japan pop 16 0.005018,604
 366  A*68:01-B*48:01-C*08:03-DRB1*09:01  Japan pop 16 0.005018,604
 367  A*24:02-B*48:01-C*08:03-DRB1*14:05  Poland DKMS 0.004820,653
 368  A*26:01-B*48:01-C*08:03-DRB1*12:01  Poland DKMS 0.004820,653
 369  A*02:01-B*48:01-C*08:03-DRB1*13:02  Poland DKMS 0.004720,653
 370  A*02:11-B*48:01-C*08:03-DRB1*07:01-DQB1*02:02  India South UCBB 0.004511,446
 371  A*01:01-B*48:01-C*08:03-DRB1*11:01-DQB1*03:01  India South UCBB 0.004411,446
 372  A*02:01-B*48:01-C*08:03-DRB1*11:11-DQB1*06:03  India South UCBB 0.004411,446
 373  A*02:09-B*48:01-C*08:03-DRB1*04:08-DQB1*03:01  India South UCBB 0.004411,446
 374  A*03:01-B*48:01-C*08:03-DRB1*09:01-DQB1*03:03  India South UCBB 0.004411,446
 375  A*11:01-B*48:01-C*08:03-DRB1*15:06-DQB1*05:02  India South UCBB 0.004411,446
 376  A*24:02-B*48:01-C*08:03-DRB1*01:01-DQB1*05:01  India South UCBB 0.004411,446
 377  A*24:02-B*48:01-C*08:03-DRB1*10:01-DQB1*05:01  India South UCBB 0.004411,446
 378  A*24:02-B*48:01-C*08:03-DRB1*11:01-DQB1*03:01  India South UCBB 0.004411,446
 379  A*24:02-B*48:01-C*08:03-DRB1*13:02-DQB1*06:04  India South UCBB 0.004411,446
 380  A*33:03-B*08:01-C*08:03-DRB1*03:01-DQB1*02:01  India South UCBB 0.004411,446
 381  A*33:03-B*48:01-C*08:03-DRB1*15:01-DQB1*06:02  India South UCBB 0.004411,446
 382  A*02:11-B*48:01-C*08:03-DRB1*07:01-DQB1*03:03  India South UCBB 0.004311,446
 383  A*02:06:01-B*48:01:01-C*08:03:01-DRB1*07:01:01-DQB1*03:03:02  Poland BMR 0.004223,595
 384  A*02:06:01-B*48:01:01-C*08:03:01-DRB1*04:03:01-DQB1*03:04:01  Poland BMR 0.004223,595
 385  A*02:06:01-B*48:01:01-C*08:03:01-DRB1*11:01:01-DQB1*03:01:01  Poland BMR 0.004223,595
 386  A*68:01-B*48:01-C*08:03-DRB1*12:02-DQB1*03:01  India South UCBB 0.004211,446
 387  A*24:02-B*48:01-C*08:03-DRB1*09:01  Hong Kong Chinese BMDR 0.00407,595
 388  A*24:02-B*48:01-C*08:03-DRB1*13:12  Hong Kong Chinese BMDR 0.00357,595
 389  A*03:01:01-B*48:01:01-C*08:03:01-DRB1*12:01:01-DQB1*03:01:01  Poland BMR 0.003323,595
 390  A*24:02-C*08:03  China Hubei Han 0.00303,732
 391  A*02:01-B*48:01-C*08:03-DRB1*08:01  Poland DKMS 0.002520,653
 392  A*02:06-B*37:01-C*08:03-DRB1*10:01  Poland DKMS 0.002420,653
 393  A*02:06-B*48:01-C*08:03-DRB1*04:01  Poland DKMS 0.002420,653
 394  A*02:06-B*48:01-C*08:03-DRB1*11:01  Poland DKMS 0.002420,653
 395  A*02:06-B*48:01-C*08:03-DRB1*12:01  Poland DKMS 0.002420,653
 396  A*03:01-B*48:01-C*08:03-DRB1*03:01  Poland DKMS 0.002420,653
 397  A*24:02-B*48:01-C*08:03-DRB1*08:02  Poland DKMS 0.002420,653
 398  A*26:01-B*48:01-C*08:03-DRB1*09:01  Poland DKMS 0.002420,653
 399  A*26:01-B*48:01-C*08:03-DRB1*13:01  Poland DKMS 0.002420,653
 400  A*02:06-B*48:01-C*08:03-DRB1*09:01  Poland DKMS 0.002320,653

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 301 to 400 (from 424) records   Pages: 1 2 3 4 5 of 5  


   

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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