Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Displaying 301 to 400 (from 573) records   Pages: 1 2 3 4 5 6 of 6  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 301  A*11:01-B*08:01-C*12:03-DRB1*03:01-DQB1*02:01  USA Hispanic pop 2 0.04701,999
 302  A*11:03-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  India East UCBB 0.02082,403
 303  A*11:202-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.00855,849
 304  A*23:01:01-B*08:01:01-C*05:01:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.002123,595
 305  A*23:01:01-B*08:01:01-C*07:01:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.080523,595
 306  A*23:01:01-B*08:01:02-C*07:01:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.000327723,595
 307  A*23:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 308  A*23:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01  USA Hispanic pop 2 0.09401,999
 309  A*23:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*04:01  Germany DKMS - German donors 0.01613,456,066
 310  A*23:01-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  India Tamil Nadu 0.02012,492
 311  A*24:02:01:01-B*08:01:01-C*07:02:01:01-DRB1*03:01:01-DQB1*02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 312  A*24:02:01-B*08:01:01-C*03:03:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.002123,595
 313  A*24:02:01-B*08:01:01-C*05:01:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.008523,595
 314  A*24:02:01-B*08:01:01-C*07:01:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.182823,595
 315  A*24:02:01-B*08:01:01-C*07:01:01-DRB1*03:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Barra Mansa Rio State Caucasian 0.3125405
 316  A*24:02:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  China Zhejiang Han 0.05731,734
 317  A*24:02:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  India Karnataka Kannada Speaking 0.5750174
 318  A*24:02:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.033123,595
 319  A*24:02:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.667228,927
 320  A*24:02:01-B*08:01:01-C*07:02:01-DRB1*03:01-DQB1*02:01  Costa Rica Central Valley Mestizo (G) 0.2262221
 321  A*24:02-B*08:01-C*02:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.06005,829
 322  A*24:02-B*08:01-C*02:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.08314,204
 323  A*24:02-B*08:01-C*02:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.06155,849
 324  A*24:02-B*08:01-C*04:01-DRB1*03:01-DQB1*02:01  India West UCBB 0.00865,829
 325  A*24:02-B*08:01-C*04:01-DRB1*03:01-DQB1*02:01-DPB1*04:01  Panama 0.1900462
 326  A*24:02-B*08:01-C*05:01-DRB1*03:01-DQB1*02:01  India Central UCBB 0.01194,204
 327  A*24:02-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.03731,463
 328  A*24:02-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.05804,856
 329  A*24:02-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01  Germany DKMS - Italy minority 0.05601,159
 330  A*24:02-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.17104,335
 331  A*24:02-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01  Tunisia 3.0000100
 332  A*24:02-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01  USA Hispanic pop 2 0.18701,999
 333  A*24:02-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01  USA Asian pop 2 0.01101,772
 334  A*24:02-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01  USA NMDP American Indian South or Central America 0.26685,926
 335  A*24:02-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*01:01  Germany DKMS - German donors 0.06163,456,066
 336  A*24:02-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*02:01  Germany DKMS - German donors 0.01033,456,066
 337  A*24:02-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*03:01  Germany DKMS - German donors 0.01293,456,066
 338  A*24:02-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*04:01  Germany DKMS - German donors 0.05803,456,066
 339  A*24:02-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*04:01  Russia Karelia 0.11531,075
 340  A*24:02-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*04:02  Germany DKMS - German donors 0.01743,456,066
 341  A*24:02-B*08:01-C*07:02-DRB1*03:01-DQA1*05:01-DQB1*02:01-DPB1*02:01  Sri Lanka Colombo 0.0700714
 342  A*24:02-B*08:01-C*07:02-DRB1*03:01-DQA1*05:01-DQB1*02:01-DPB1*09:01  Sri Lanka Colombo 0.1401714
 343  A*24:02-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.55304,856
 344  A*24:02-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Italy minority 0.17301,159
 345  A*24:02-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  India Tamil Nadu 0.13542,492
 346  A*24:02-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.30965,829
 347  A*24:02-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  India East UCBB 0.31302,403
 348  A*24:02-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  India Northeast UCBB 0.3378296
 349  A*24:02-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.72445,849
 350  A*24:02-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.103411,446
 351  A*24:02-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.51684,204
 352  A*24:02-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  Italy pop 5 0.1400975
 353  A*24:02-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 354  A*24:02-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  USA Asian pop 2 0.04401,772
 355  A*24:02-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  USA Hispanic pop 2 0.14001,999
 356  A*24:02-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01-DPB1*02:01  Germany DKMS - German donors 0.01263,456,066
 357  A*24:02-B*08:01-C*15:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.01715,849
 358  A*24:02-B*08:01-C*15:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.00865,829
 359  A*24:02-B*08:01-C*15:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.005711,446
 360  A*24:02-B*08:01-C*15:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Malay 0.0526951
 361  A*24:02-B*08:01-DRB1*03:01-DQB1*02:01  Tunisia Gabes 1.570095
 362  A*24:07:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  India Kerala Malayalam speaking 0.1400356
 363  A*24:07-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01  USA Asian pop 2 0.01101,772
 364  A*24:07-B*08:01-C*07:02-DRB1*03:01-DQA1*05:01-DQB1*02:01-DPB1*04:01  Sri Lanka Colombo 0.1401714
 365  A*24:07-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  India Tamil Nadu 0.71002,492
 366  A*24:07-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.432511,446
 367  A*24:07-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.01194,204
 368  A*24:07-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  India East UCBB 0.04222,403
 369  A*24:07-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.03105,829
 370  A*24:07-B*08:01-C*15:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.00865,829
 371  A*24-B*08:01-DRB1*03:01-DQB1*02:01  Tunisia pop 3 1.2000104
 372  A*25:01:01-B*08:01:01-C*04:01:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.004223,595
 373  A*25:01:01-B*08:01:01-C*07:01:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.110023,595
 374  A*25:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.003923,595
 375  A*25:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.10251,463
 376  A*25:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01  Germany DKMS - Italy minority 0.04301,159
 377  A*25:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.10304,335
 378  A*25:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01  USA African American pop 4 0.04402,411
 379  A*25:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*01:01  Germany DKMS - German donors 0.04413,456,066
 380  A*25:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*04:01  Germany DKMS - German donors 0.02903,456,066
 381  A*25:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01-DPB1*04:01  Russia Karelia 0.05581,075
 382  A*25:01-B*08:01-C*07:02-DRB1*03:01-DQB1*02:01  India Tamil Nadu 0.02012,492
 383  A*26:01:01-B*08:01:01-C*01:02:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.004223,595
 384  A*26:01:01-B*08:01:01-C*07:01:01-DRB1*03:01:01-DQA1*01:02:01-DQB1*02:01:01-DPA1*02:01:02-DPB1*01:01:01  Russia Belgorod region 0.3268153
 385  A*26:01:01-B*08:01:01-C*07:01:01-DRB1*03:01:01-DQB1*02:01  Russia Nizhny Novgorod, Russians 0.12311,510
 386  A*26:01:01-B*08:01:01-C*07:01:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.123623,595
 387  A*26:01:01-B*08:01:01-C*07:01:08-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.002123,595
 388  A*26:01:01-B*08:01:01-C*07:02:01:01-DRB1*03:01:01-DQB1*02:01  Russia Nizhny Novgorod, Russians 0.16561,510
 389  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  China Zhejiang Han 0.08651,734
 390  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  India Karnataka Kannada Speaking 0.2870174
 391  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  India Andhra Pradesh Telugu Speaking 0.5376186
 392  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  India Kerala Malayalam speaking 0.7020356
 393  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.015523,595
 394  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01-DPB1*02:01:02  Saudi Arabia pop 6 (G) 0.330928,927
 395  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01-DPB1*03:01:01  Saudi Arabia pop 6 (G) 0.233228,927
 396  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.593328,927
 397  A*26:01:01-B*08:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01-DPB1*17:01:01  Saudi Arabia pop 6 (G) 0.090828,927
 398  A*26:01-B*08:01-C*06:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Indian 0.1845271
 399  A*26:01-B*08:01-C*07:01-DRB1*03:01-DQA1*05:01-DQB1*02:01  Kosovo 0.8060124
 400  A*26:01-B*08:01-C*07:01-DRB1*03:01-DQB1*02:01  Germany DKMS - Italy minority 0.11701,159

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 573) records   Pages: 1 2 3 4 5 6 of 6  


   

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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