Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Population:  Country:  Source of dataset : 
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Sample Size:      Sample Year:     Loci Tested: 
Displaying 301 to 400 (from 4,214) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 43  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 301  A*02:01:01-B*51:01:01-C*14:02:01-DRB1*10:01:01-DQB1*03:01:01-DPA1*02:01:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 302  A*03:01:01-B*53:01:01-C*03:03:01-DRB1*10:01:01-DQB1*05:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 303  A*11:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 304  A*23:01:01-B*07:20-C*07:02:01-DRB1*10:01:01-DQB1*05:01:01-DPA1*02:01:01-DPB1*17:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 305  A*32:01:01-B*18:01:01-C*05:01:01-DRB1*10:01:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*104:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 306  A*68:01:01-B*27:05:02-C*02:02:02-DRB1*10:01:01-DQB1*05:01:01-DPA1*02:01:02-DPB1*01:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 307  A*03-B*35-DRB1*10:01-DQA1*01:01-DQB1*05:01  Brazil Paraná Caucasian 0.3120641
 308  A*24-B*45-DRB1*10:01-DQA1*01:01-DQB1*05:01  Brazil Paraná Caucasian 0.3120641
 309  A*29:01:01-B*07:05:01-C*15:05:02-DRB1*10:01:01-DPB1*04:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.31035,266
 310  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Chinese 0.310399,672
 311  DRB1*10:01:01-DPB1*04:01:01  China Inner Mongolia Autonomous Region Northeast 0.3080496
 312  A*68:01-B*39:01-DRB1*10:01-DQB1*05:01  Mexico Mexico City Tlalpan 0.3030330
 313  A*01:01-B*15:03-C*04:01-DRB1*10:01-DQA1*01:01-DQB1*05:01-DPB1*02:01  South Africa Worcester 0.3000159
 314  A*01:01-B*37:01-C*06:02-DRB1*10:01  Italy pop 5 0.3000975
 315  A*02:01-B*27:05-C*02:02-DRB1*10:01  Italy pop 5 0.3000975
 316  A*02:01-B*40:01-C*02:10-DRB1*10:01-DQA1*02:01-DQB1*05:08-DPB1*01:01  South Africa Worcester 0.3000159
 317  A*03:01-B*07:02-C*07:02-DRB1*10:01  Italy pop 5 0.3000975
 318  A*24:07-B*52:01-C*12:02-DRB1*10:01-DQA1*01:01-DQB1*05:01-DPB1*02:01  South Africa Worcester 0.3000159
 319  A*29:02-B*15:03-C*04:01-DRB1*10:01-DQA1*05:01-DQB1*05:01-DPB1*18:01  South Africa Worcester 0.3000159
 320  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Germany DKMS - Turkey minority 0.29404,856
 321  A*68:02-B*49:01-DRB1*10:01  Israel Ethiopia Jews 0.28805,928
 322  A*01:01:01-B*37:04:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  India Karnataka Kannada Speaking 0.2870174
 323  A*02:11:01-B*40:06:01-C*15:02:01-DRB1*10:01:01-DQB1*05:03:01  India Karnataka Kannada Speaking 0.2870174
 324  A*29:01:01-B*07:02:01-C*15:05:01-DRB1*10:01:01-DQB1*05:02:04  India Karnataka Kannada Speaking 0.2870174
 325  A*29:01:01-B*35:01:01-C*15:05:01-DRB1*10:01:01-DQB1*05:01:01  India Karnataka Kannada Speaking 0.2870174
 326  A*29:01:01-B*51:06:01-C*14:02:01-DRB1*10:01:01-DQB1*05:01:01  India Karnataka Kannada Speaking 0.2870174
 327  A*32:01:01-B*35:01:01-C*04:01:01-DRB1*10:01:01-DQB1*05:01:01  India Karnataka Kannada Speaking 0.2870174
 328  A*68:01:02-B*52:01:01-C*14:02:01-DRB1*10:01:01-DQB1*06:01:01  India Karnataka Kannada Speaking 0.2870174
 329  A*29:02-B*07:05-DRB1*10:01  Israel Tunisia Jews 0.28409,070
 330  DRB1*10:01:01-DQB1*05:01-DPB1*05:01:01  China Inner Mongolia Autonomous Region Northeast 0.2840496
 331  A*01:01-B*35:08-DRB1*10:01  Israel Poland Jews 0.283013,871
 332  DRB1*10:01:01-DPB1*05:01:01  China Inner Mongolia Autonomous Region Northeast 0.2830496
 333  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 0.2810356
 334  A*03:01:01-B*15:01:01-C*03:03:01-DRB1*10:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 0.2810356
 335  A*33:03:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 0.2810356
 336  A*33:03-B*58:01-C*03:02-DRB1*10:01-DQA1*01:01-DQB1*05:01-DPB1*04:01  Sri Lanka Colombo 0.2801714
 337  A*32:01:01-B*07:02:01-C*07:02:01-DRB1*10:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 0.2760356
 338  A*26:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  USA NMDP Caribean Indian 0.273914,339
 339  A*29:01-B*07:05-C*15:05-DRB1*10:01-DQB1*05:01  India Tamil Nadu 0.27112,492
 340  A*02-B*45-DRB1*10:01  Colombia Barranquilla 0.2700188
 341  A*26-B*50-DRB1*10:01  Colombia Barranquilla 0.2700188
 342  A*30-B*13-DRB1*10:01  Colombia Barranquilla 0.2700188
 343  A*68-B*35-DRB1*10:01  Colombia Barranquilla 0.2700188
 344  A*01:01:01-B*40:06:04-C*15:02:01-DRB1*10:01:01-DQB1*03:03:02  India Andhra Pradesh Telugu Speaking 0.2688186
 345  A*01:01:01-B*49:01:01-C*07:01:01-DRB1*10:01:01-DQB1*06:04:01  India Andhra Pradesh Telugu Speaking 0.2688186
 346  A*01:01:01-B*51:01:01-C*14:02:01-DRB1*10:01:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 347  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 348  A*01:01:01-B*57:01:01-C*12:02:01-DRB1*10:01:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 349  A*02:03:01-B*40:06:01-C*03:02:02-DRB1*10:01:01-DQB1*02:02:01  India Andhra Pradesh Telugu Speaking 0.2688186
 350  A*02:11:01-B*40:06:04-C*15:02:01-DRB1*10:01:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 351  A*02:11:01-B*52:01:01-C*07:02:01-DRB1*10:01:01-DQB1*03:02:01  India Andhra Pradesh Telugu Speaking 0.2688186
 352  A*03:01:01-B*56:01:01-C*01:02:01-DRB1*10:01:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 353  A*11:01:01-B*37:01:01-C*03:04:01-DRB1*10:01:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 354  A*11:01:01-B*44:03:02-C*07:06-DRB1*10:01:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 355  A*11:01:01-B*52:01:01-C*12:02:02-DRB1*10:01:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 356  A*24:02:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 357  A*31:01:02-B*07:02:01-C*07:02:01-DRB1*10:01:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 358  A*31:01:02-B*40:01:02-C*03:04:01-DRB1*10:01:01-DQB1*06:03:01  India Andhra Pradesh Telugu Speaking 0.2688186
 359  A*31:01:02-B*55:01:01-C*01:02:01-DRB1*10:01:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 360  A*32:01:01-B*07:02:01-C*07:02:01-DRB1*10:01:01-DQB1*05:03:01  India Andhra Pradesh Telugu Speaking 0.2688186
 361  A*33:03:01-B*15:18:01-C*07:04:01-DRB1*10:01:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 362  A*29:01-B*07:05-DRB1*10:01  Israel Georgia Jews 0.26804,471
 363  A*02:01-B*58:01-DRB1*10:01  Israel YemenJews 0.266015,542
 364  A*02:11-B*40:06-C*15:02-DRB1*10:01-DQB1*05:01  India East UCBB 0.26402,403
 365  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Malaysia Peninsular Malay 0.2629951
 366  A*29:01-B*07:05-C*15:04-DRB1*10:01-DQB1*05:01  Malaysia Peninsular Malay 0.2629951
 367  A*26:01-B*35:08-DRB1*10:01  Israel Iraq Jews 0.261013,270
 368  A*29:01-B*07:05-DRB1*10:01  Israel Poland Jews 0.261013,871
 369  A*01:01:01:01-B*49:01:01-C*07:01:01-DRB1*10:01:01-DQB1*05:01  Russia Bashkortostan, Tatars 0.2604192
 370  A*33:03:01-B*13:02:01-C*03:02:02-DRB1*10:01:01-DQB1*02:01:01  Russia Bashkortostan, Tatars 0.2604192
 371  A*68:24-B*13:02:01-C*07:04:01-DRB1*10:01:01-DQB1*05:01  Russia Bashkortostan, Tatars 0.2604192
 372  B*35:01-DRB1*10:01  Italy pop 5 0.2600975
 373  B*37:01-DRB1*10:01  Italy pop 5 0.2600975
 374  A*02:02-B*38:02-C*15:04-DRB1*10:01-DQB1*03:03  Malaysia Peninsular Chinese 0.2577194
 375  A*11:01-B*46:01-C*01:02-DRB1*10:01-DQB1*03:01  Malaysia Peninsular Chinese 0.2577194
 376  A*01:01-B*35:08-DRB1*10:01  Israel Argentina Jews 0.25104,307
 377  A*03:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India Tamil Nadu 0.24692,492
 378  A*03:01-B*39:01-DRB1*10:01  Israel Kavkazi Jews 0.24602,840
 379  A*24-B*45-DRB1*10:01  Chile Santiago 0.2446920
 380  A*02:06-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.242611,446
 381  A*01:01-B*37:01-C*06:02-DRB1*10:01  Germany DKMS - United Kingdom minority 0.24001,043
 382  A*01:01-B*41:01-C*17:01-DRB1*10:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.23921,463
 383  A*24:02-B*45:01-C*16:01-DRB1*10:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.23904,335
 384  A*33:03-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India East UCBB 0.23802,403
 385  A*03:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India East UCBB 0.23642,403
 386  A*02:01-B*44:03-DRB1*10:01  Israel USA Jews 0.23606,058
 387  A*01:01-B*41:01-DRB1*10:01  Israel Arab pop 2 0.233012,301
 388  A*02:01-B*37:01-C*06:02-DRB1*10:01  Germany DKMS - Netherlands minority 0.23301,374
 389  A*29:01:01-B*07:05:01-C*15:05:01-DRB1*10:01:01-DQB1*05:01:01-DPB1*03:01:01  Saudi Arabia pop 6 (G) 0.231128,927
 390  A*01:01-B*37:01-DRB1*10:01  Hong Kong Chinese cord blood registry 0.23113,892
 391  A*23:01:01-B*44:03:01-C*04:01:01-DRB1*10:01:01-DQB1*05:01:01  Spain, Canary Islands, Gran canaria island 0.2300215
 392  A*33:01:01-B*57:01:01-C*07:01:01-DRB1*10:01:01-DQB1*05:01:01  Spain, Canary Islands, Gran canaria island 0.2300215
 393  A*02:01-B*07:02-C*07:02-DRB1*10:01-DQA1*01:01-DQB1*05:01-DPA1*02:01-DPB1*11:01  Mexico Chiapas Lacandon Mayans 0.2294218
 394  A*01:01-B*37:01-C*06:02-DRB1*10:01  Japan pop 16 0.229018,604
 395  A*29:01-B*07:05-C*15:05-DRB1*10:01-DQB1*05:01  India East UCBB 0.22882,403
 396  A*01:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01  Costa Rica Central Valley Mestizo (G) 0.2262221
 397  A*23:01:01-B*35:01:01-C*07:01:01-DRB1*10:01:01-DQB1*05:01  Costa Rica Central Valley Mestizo (G) 0.2262221
 398  A*32:01:01-B*48:01:01-C*08:01:01-DRB1*10:01:01-DQB1*05:01  Costa Rica Central Valley Mestizo (G) 0.2262221
 399  A*68:01:01-B*49:01:01-C*03:04:01-DRB1*10:01:01-DQB1*03:01  Costa Rica Central Valley Mestizo (G) 0.2262221
 400  A*24:02-B*45:01-C*16:01-DRB1*10:01  Germany DKMS - Spain minority 0.22601,107

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 4,214) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 43  


   

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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