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 3,341) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 34  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 301  A*11:01-B*52:01-C*12:02-DRB1*14:04-DQB1*05:03  India South UCBB 0.251111,446
 302  A*03:01-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  India Central UCBB 0.24804,204
 303  A*01:01-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  Colombia Bogotá Cord Blood 0.24791,463
 304  A*11:01-B*52:01-C*12:02-DRB1*04:03-DQB1*03:02  India East UCBB 0.24742,403
 305  A*02:11-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  India Tamil Nadu 0.24632,492
 306  A*01:01-B*52:01-C*12:02-DRB1*15:02  Germany DKMS - Croatia minority 0.24402,057
 307  A*11:01-B*52:01-C*12:02-DRB1*15:02  Germany DKMS - Romania minority 0.24301,234
 308  A*01:01-C*12:02  Italy pop 5 0.2400975
 309  A*02:01:01:01-B*52:01:01:02-C*12:02:02-DRB1*15:02-DQB1*06:01  Russia Nizhny Novgorod, Russians 0.23791,510
 310  A*01:01-B*52:01-C*12:02-DRB1*15:02  Germany DKMS - China minority 0.23401,282
 311  A*11:02-B*27:04-C*12:02-DRB1*12:02  Germany DKMS - China minority 0.23401,282
 312  A*01:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.23165,849
 313  A*24:02-B*52:01-C*12:02-DRB1*04:03-DQB1*03:02  India East UCBB 0.23142,403
 314  A*02:01:01-B*52:01:01-C*12:02:02-DRB1*07:01:01-DQB1*02:02:01  Spain, Canary Islands, Gran canaria island 0.2300215
 315  A*02:01:01-B*52:01:01-C*12:02:02-DRB1*15:02:01-DQB1*06:01:01  Spain, Canary Islands, Gran canaria island 0.2300215
 316  A*03:01-B*52:01-C*12:02-DRB1*08:02-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218
 317  A*02:01:01-B*52:01:01-C*12:02:02  England Blood Donors of Mixed Ethnicity 0.2290519
 318  A*02:01:01:01-B*52:01:01:02-C*12:02:02-DRB1*07:01:01-DQB1*02:02  Russia Nizhny Novgorod, Russians 0.22881,510
 319  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*15:02:01-DQB1*06:01:01  China Zhejiang Han 0.22881,734
 320  A*01:01-B*52:01-C*12:02-DRB1*15:02  Germany DKMS - Portugal minority 0.22801,176
 321  A*11:01:01-B*52:01:01-C*12:02:02-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.227723,595
 322  A*11:01-B*52:01-C*12:02-DRB1*04:03-DQB1*03:02  India Central UCBB 0.22764,204
 323  A*29:02:01-B*52:01:01-C*12:02:02-DRB1*15:02:01-DQB1*06:01  Costa Rica Central Valley Mestizo (G) 0.2262221
 324  A*03:01-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  USA Asian pop 2 0.22201,772
 325  A*24:07-B*52:01-C*12:02-DRB1*10:01-DQB1*05:01  India East UCBB 0.22142,403
 326  A*03:01-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  India East UCBB 0.21822,403
 327  A*11:01-B*52:01-C*12:02-DRB1*01:01  Germany DKMS - Croatia minority 0.21802,057
 328  A*03:01-B*08:01-C*12:02-DRB1*13:03-DQA1*05:01-DQB1*03:01-DPB1*01:01  Nicaragua Managua 0.2165339
 329  A*01:01-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  USA NMDP American Indian South or Central America 0.21385,926
 330  A*24:07-B*52:01-C*12:02-DRB1*04:03-DQB1*03:02  India South UCBB 0.213411,446
 331  A*11:01-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  Germany DKMS - Italy minority 0.21201,159
 332  A*24:02-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  Germany DKMS - Turkey minority 0.21204,856
 333  A*02:01-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01-DPB1*04:01  Russia Karelia 0.21171,075
 334  A*33:03-B*52:01-C*12:02-DRB1*15:02-DQA1*01:03-DQB1*06:01-DPB1*04:01  Sri Lanka Colombo 0.2101714
 335  A*01:01-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  India South UCBB 0.208311,446
 336  A*32:01-B*52:01-C*12:02-DRB1*15:02  Germany DKMS - China minority 0.20801,282
 337  A*01:01-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.20504,335
 338  A*68:01-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  India Central UCBB 0.20484,204
 339  A*11:01-B*52:01-C*12:02-DRB1*15:01-DQB1*06:01  India Tamil Nadu 0.20422,492
 340  A*02:01-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  India East UCBB 0.20352,403
 341  A*11:01-B*52:01-C*12:02-DRB1*01:01  Germany DKMS - Romania minority 0.20201,234
 342  A*69:01:01-B*52:01:01-C*12:02:02-DRB1*04:05:01-DQB1*04:01:01  China Zhejiang Han 0.20181,734
 343  A*02:01-C*12:02  Italy pop 5 0.2000975
 344  A*68:01-B*52:01-C*12:02-DRB1*11:01-DQB1*03:01  India South UCBB 0.198611,446
 345  A*01:01-B*52:01-C*12:02-DRB1*15:02-DRB5*01:02-DQB1*06:01  USA NMDP Southeast Asian 0.196127,978
 346  A*01:01-B*52:01-C*12:02-DRB1*15:02-DRB5*01:02-DQB1*06:01  USA NMDP South Asian Indian 0.1953185,391
 347  A*68:01-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  India West UCBB 0.19535,829
 348  A*01:01-B*52:01-C*12:02-DRB1*15:02  Germany DKMS - Bosnia and Herzegovina minority 0.19501,028
 349  A*02:01:01-B*52:01:01-C*12:02:02-DRB1*15:02:01-DQB1*06:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 350  A*11:01:01-B*52:01:01-C*12:02:02-DRB1*04:08:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 351  A*24:02:01-B*52:01:01-C*12:02:02-DRB1*15:02:01-DQB1*06:01:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 352  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
 353  A*02:01-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  Colombia Bogotá Cord Blood 0.19371,463
 354  A*24:02-B*52:01-C*12:02-DRB1*04:05  Japan pop 16 0.193018,604
 355  A*11:01-B*52:04-C*12:02-DRB1*14:04-DQB1*05:03  India East UCBB 0.19272,403
 356  A*24:02-B*40:06-C*12:02-DRB1*15:01-DQB1*06:01  India Tamil Nadu 0.19102,492
 357  A*02:01-B*52:01-C*12:02-DRB1*07:01-DQB1*02:02-DPB1*04:01  Panama 0.1900462
 358  A*11:01-B*52:01-C*12:02-DRB1*03:01-DQB1*03:01-DPB1*16:01  Panama 0.1900462
 359  A*29:32-B*18:01-C*12:02-DRB1*07:01-DQB1*02:02-DPB1*02:02  Panama 0.1900462
 360  A*30:02-B*27:05-C*12:02-DRB1*15:02-DQB1*05:03-DPB1*04:01  Panama 0.1900462
 361  A*30:02-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01-DPB1*02:01  Panama 0.1900462
 362  A*68:01-B*40:02-C*12:02-DRB1*04:07-DQB1*03:02-DPB1*02:01  Panama 0.1900462
 363  A*11:01-B*52:01-C*12:02-DRB1*04:03-DQB1*03:02  India North UCBB 0.18725,849
 364  A*02:11-B*40:06-C*12:02-DRB1*15:01-DQB1*06:01  India East UCBB 0.18572,403
 365  A*01:01-B*52:01-C*12:02-DRB1*15:02-DRB5*01:02-DQB1*06:01  USA NMDP European Caucasian 0.18461,242,890
 366  A*01:01-B*13:01-C*12:02-DRB1*09:01-DQB1*03:03  Malaysia Peninsular Indian 0.1845271
 367  A*01:01-B*13:01-C*12:02-DRB1*16:02-DQB1*05:02  Malaysia Peninsular Indian 0.1845271
 368  A*01:01-B*51:01-C*12:02-DRB1*15:01-DQB1*06:01  Malaysia Peninsular Indian 0.1845271
 369  A*01:01-B*52:01-C*12:02-DRB1*10:01-DQB1*05:01  Malaysia Peninsular Indian 0.1845271
 370  A*01:01-B*52:01-C*12:02-DRB1*14:04-DQB1*05:03  Malaysia Peninsular Indian 0.1845271
 371  A*01:01-B*52:11-C*12:02-DRB1*07:01-DQB1*03:03  Malaysia Peninsular Indian 0.1845271
 372  A*02:01-B*40:04-C*12:02-DRB1*04:01-DQB1*03:01  Malaysia Peninsular Indian 0.1845271
 373  A*02:01-B*40:04-C*12:02-DRB1*13:01-DQB1*05:01  Malaysia Peninsular Indian 0.1845271
 374  A*02:01-B*44:03-C*12:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Indian 0.1845271
 375  A*02:01-B*52:01-C*12:02-DRB1*15:02-DQB1*03:03  Malaysia Peninsular Indian 0.1845271
 376  A*02:06-B*15:02-C*12:02-DRB1*10:01-DQB1*05:01  Malaysia Peninsular Indian 0.1845271
 377  A*02:06-B*52:01-C*12:02-DRB1*15:01-DQB1*06:01  Malaysia Peninsular Indian 0.1845271
 378  A*02:11-B*40:01-C*12:02-DRB1*07:01-DQB1*03:03  Malaysia Peninsular Indian 0.1845271
 379  A*02:11-B*40:06-C*12:02-DRB1*14:04-DQB1*06:01  Malaysia Peninsular Indian 0.1845271
 380  A*02:11-B*40:22N-C*12:02-DRB1*15:02-DQB1*06:01  Malaysia Peninsular Indian 0.1845271
 381  A*02:11-B*52:01-C*12:02-DRB1*04:03-DQB1*03:02  Malaysia Peninsular Indian 0.1845271
 382  A*03:01-B*15:17-C*12:02-DRB1*13:02-DQB1*05:01  Malaysia Peninsular Indian 0.1845271
 383  A*03:01-B*40:01-C*12:02-DRB1*08:03-DQB1*02:02  Malaysia Peninsular Indian 0.1845271
 384  A*03:01-B*57:01-C*12:02-DRB1*07:01-DQB1*03:02  Malaysia Peninsular Indian 0.1845271
 385  A*11:01-B*18:01-C*12:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Indian 0.1845271
 386  A*11:01-B*27:04-C*12:02-DRB1*15:08-DQB1*05:02  Malaysia Peninsular Indian 0.1845271
 387  A*11:01-B*40:01-C*12:02-DRB1*15:01-DQB1*06:01  Malaysia Peninsular Indian 0.1845271
 388  A*11:01-B*51:01-C*12:02-DRB1*07:07-DQB1*05:01  Malaysia Peninsular Indian 0.1845271
 389  A*11:01-B*51:01-C*12:02-DRB1*10:01-DQB1*05:01  Malaysia Peninsular Indian 0.1845271
 390  A*11:01-B*51:01-C*12:02-DRB1*15:31-DQB1*06:03  Malaysia Peninsular Indian 0.1845271
 391  A*11:29-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  Malaysia Peninsular Indian 0.1845271
 392  A*24:02-B*15:25-C*12:02-DRB1*03:01-DQB1*05:01  Malaysia Peninsular Indian 0.1845271
 393  A*24:02-B*51:01-C*12:02-DRB1*15:01-DQB1*06:01  Malaysia Peninsular Indian 0.1845271
 394  A*24:02-B*52:01-C*12:02-DRB1*04:01-DQB1*02:02  Malaysia Peninsular Indian 0.1845271
 395  A*24:02-B*52:01-C*12:02-DRB1*08:03-DQB1*03:01  Malaysia Peninsular Indian 0.1845271
 396  A*24:02-B*52:01-C*12:02-DRB1*15:01-DQB1*06:01  Malaysia Peninsular Indian 0.1845271
 397  A*24:02-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  Malaysia Peninsular Indian 0.1845271
 398  A*24:07-B*15:01-C*12:02-DRB1*14:04-DQB1*05:03  Malaysia Peninsular Indian 0.1845271
 399  A*24:07-B*51:01-C*12:02-DRB1*04:03-DQB1*03:02  Malaysia Peninsular Indian 0.1845271
 400  A*24:15-B*52:01-C*12:02-DRB1*11:06-DQB1*06:01  Malaysia Peninsular Indian 0.1845271

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 3,341) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 34  


   

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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