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 601 to 700 (from 4,764) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 48  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 601  A*26:01:01-B*52:01:01-C*12:02:02-DRB1*15:02:01-DQB1*06:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 602  A*26:01:01-B*57:01:01-C*04:01:01-DRB1*13:01:01-DQB1*06:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 603  A*31:01:02-B*51:01:01-C*15:02:01-DRB1*15:02:05-DQB1*06:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 604  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*15:02:01-DQB1*06:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 605  A*33:03:01-B*51:01:01-C*07:06-DRB1*15:01:01-DQB1*06:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 606  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*15:02:01-DQB1*06:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 607  A*33:03:01-B*58:01:01-C*14:02:01-DRB1*15:01:01-DQB1*06:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 608  A*68:01:01-B*51:01:01-C*14:02:01-DRB1*15:01:01-DQB1*06:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 609  A*68:01:02-B*13:01:01-C*04:03:01-DRB1*15:02:02-DQB1*06:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 610  A*01:01:01:01-B*52:01:01:02-C*12:02:02-DRB1*15:02-DQB1*06:01  Russia Nizhny Novgorod, Russians 0.26791,510
 611  A*24:02-B*13:01-C*04:03-DRB1*15:01-DQB1*06:01  India Central UCBB 0.26704,204
 612  A*11:01-B*40:06-C*15:02-DRB1*15:01-DQB1*06:01  India East UCBB 0.26642,403
 613  A*11:01-B*40:01-C*07:02-DRB1*08:03-DQB1*06:01  USA Asian pop 2 0.26601,772
 614  A*11:01-B*07:06-C*07:02-DRB1*15:01-DQB1*06:01  India West UCBB 0.26575,829
 615  A*34:01-B*15:02-C*04:03-DRB1*15:02-DQB1*06:01  Malaysia Peninsular Malay 0.2639951
 616  A*01:01-B*52:01-C*12:02-DRB1*15:02-DRB5*01:02-DQB1*06:01  USA NMDP Mexican or Chicano 0.2639261,235
 617  A*32:01-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  India North UCBB 0.26225,849
 618  A*01:01-B*40:06-C*15:02-DRB1*15:02-DQB1*06:01  India Central UCBB 0.26054,204
 619  A*01:01:01:01-B*35:02:01-C*08:01:01-DRB1*11:04:01-DQB1*06:01  Russia Bashkortostan, Tatars 0.2604192
 620  A*02:01:01:01-B*15:01:01:01-C*03:03:01-DRB1*11:03-DQB1*06:01  Russia Bashkortostan, Tatars 0.2604192
 621  A*02:01:01:01-B*27:05:02-C*02:02:02-DRB1*15:02-DQB1*06:01  Russia Bashkortostan, Tatars 0.2604192
 622  A*02:11:01-B*40:06:01:02-C*15:02:01:01-DRB1*15:01:01-DQB1*06:01  Russia Bashkortostan, Tatars 0.2604192
 623  A*03:01:01:01-B*44:03:02-C*07:06-DRB1*15:02-DQB1*06:01  Russia Bashkortostan, Tatars 0.2604192
 624  A*24:02:01:01-B*35:01:01-C*04:01:01-DRB1*11:01:01-DQB1*06:01  Russia Bashkortostan, Tatars 0.2604192
 625  A*24:02:01:01-B*40:06:01-C*08:01:01-DRB1*15:02-DQB1*06:01  Russia Bashkortostan, Tatars 0.2604192
 626  A*26:01:01-B*52:01:01:02-C*12-DRB1*15:02-DQB1*06:01  Russia Bashkortostan, Tatars 0.2604192
 627  A*30:01:01-B*39:01:01:03-C*07:02:01-DRB1*13:02:01-DQB1*06:01  Russia Bashkortostan, Tatars 0.2604192
 628  A*33:03:01-B*35:03:01-C*03:02:02-DRB1*15:02-DQB1*06:01  Russia Bashkortostan, Tatars 0.2604192
 629  A*01:01-B*08:01-C*07:01-DRB1*15:02-DQA1*01:03-DQB1*06:01-DPB1*02:01  USA San Diego 0.2600496
 630  A*11:01-B*13:01-C*03:04-DRB1*11:01-DQA1*05:01-DQB1*06:01-DPB1*05:01  USA San Diego 0.2600496
 631  A*24:02-B*35:01-C*03:03-DRB1*08:03-DQA1*03:01-DQB1*06:01-DPB1*02:02  USA San Diego 0.2600496
 632  A*24:02-B*52:01-C*12:02-DRB1*09:01-DQA1*01:03-DQB1*06:01-DPB1*05:01  USA San Diego 0.2600496
 633  A*26:01-B*48:01-C*01:02-DRB1*14:07-DQA1*01:03-DQB1*06:01-DPB1*14:01  USA San Diego 0.2600496
 634  A*68:01-B*49:01-C*05:01-DRB1*04:01-DQA1*03:01-DQB1*06:01-DPB1*02:01  USA San Diego 0.2600496
 635  A*11:01-B*40:10-C*04:03-DRB1*08:03-DQB1*06:01  USA NMDP Hawaiian or other Pacific Islander 0.258611,499
 636  A*01:01-B*37:01-C*06:02-DRB1*11:04-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 637  A*02:01-B*15:02-C*07:02-DRB1*08:03-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 638  A*02:01-B*40:01-C*01:03-DRB1*08:03-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 639  A*02:01-B*46:01-C*01:02-DRB1*15:01-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 640  A*02:01-B*51:01-C*01:02-DRB1*15:01-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 641  A*02:03-B*13:01-C*07:04-DRB1*14:05-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 642  A*02:03-B*15:02-C*07:02-DRB1*12:01-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 643  A*02:03-B*38:02-C*03:02-DRB1*15:02-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 644  A*02:03-B*40:01-C*07:02-DRB1*14:01-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 645  A*02:06-B*13:01-C*03:04-DRB1*12:01-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 646  A*02:68-B*54:01-C*01:02-DRB1*04:05-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 647  A*11:01-B*13:01-C*12:02-DRB1*15:01-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 648  A*11:01-B*15:02-C*01:02-DRB1*03:01-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 649  A*11:01-B*40:01-C*07:02-DRB1*08:03-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 650  A*11:01-B*40:06-C*08:01-DRB1*08:03-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 651  A*11:01-B*46:01-C*03:03-DRB1*08:03-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 652  A*11:01-B*55:23-C*03:03-DRB1*08:03-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 653  A*24:02-B*40:01-C*03:04-DRB1*12:01-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 654  A*24:02-B*40:01-C*07:05-DRB1*15:07-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 655  A*24:02-B*40:02-C*03:03-DRB1*04:01-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 656  A*24:02-B*40:06-C*04:01-DRB1*08:03-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 657  A*24:02-B*40:10-C*04:03-DRB1*15:01-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 658  A*24:02-B*40:43-C*07:02-DRB1*15:01-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 659  A*24:02-B*52:01-C*03:03-DRB1*04:05-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 660  A*33:01-B*58:01-C*03:02-DRB1*11:01-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 661  A*33:03-B*44:03-C*07:01-DRB1*08:03-DQB1*06:01  Malaysia Peninsular Chinese 0.2577194
 662  A*11:01:01-B*46:01:01-C*01:02:01-DRB1*08:03:02-DQB1*06:01:01  China Zhejiang Han 0.25491,734
 663  A*68:01-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  India South UCBB 0.254911,446
 664  A*11:01-B*52:01-C*12:02-DRB1*15:02-DRB5*01:02-DQB1*06:01  USA NMDP Mexican or Chicano 0.2543261,235
 665  A*02:01-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  India North UCBB 0.25135,849
 666  A*02:11-B*40:06-C*15:02-DRB1*15:01-DQB1*06:01  USA Asian pop 2 0.25101,772
 667  A*11:01-B*51:06-C*14:02-DRB1*15:01-DQB1*06:01  India Tamil Nadu 0.24922,492
 668  A*03:01-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  India Central UCBB 0.24804,204
 669  A*01:01-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  Colombia Bogotá Cord Blood 0.24791,463
 670  A*02:07-B*46:01-C*01:02-DRB1*08:03-DRBX*NNNN-DQB1*06:01  USA NMDP Vietnamese 0.247843,540
 671  DQA1*01:03-DQB1*06:01-DPA1*02:02-DPB1*13:01  Hong Kong Chinese HKBMDR. DQ and DP 0.24751,064
 672  A*01:01-B*57:01-C*06:02-DRB1*15:02-DQB1*06:01  India East UCBB 0.24652,403
 673  A*24:02-B*40:06-C*15:02-DRB1*15:02-DQB1*06:01  India North UCBB 0.24655,849
 674  A*02:11-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  India Tamil Nadu 0.24632,492
 675  A*01:01-B*40:06-C*15:02-DRB1*15:01-DQB1*06:01  India South UCBB 0.243911,446
 676  A*24:02-B*51:01-C*14:02-DRB1*08:03-DQB1*06:01  USA Asian pop 2 0.24101,772
 677  A*11:01-B*35:01-C*04:01-DRB1*15:02-DQB1*06:01  India West UCBB 0.24085,829
 678  A*24:02-B*13:01-C*04:03-DRB1*15:01-DQB1*06:01  India Tamil Nadu 0.23922,492
 679  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
 680  A*68:01-B*40:06-C*15:02-DRB1*15:01-DQB1*06:01  India West UCBB 0.23735,829
 681  A*33:03-B*35:01-C*04:01-DRB1*15:02-DQB1*06:01  India East UCBB 0.23602,403
 682  A*11:01-B*40:06-C*15:02-DRB1*15:01-DQB1*06:01  India Tamil Nadu 0.23562,492
 683  A*11:01-B*35:01-C*04:01-DRB1*15:02-DQB1*06:01  India Central UCBB 0.23464,204
 684  A*68:01-B*40:06-C*15:02-DRB1*15:01-DQB1*06:01  India Tamil Nadu 0.23322,492
 685  A*24:02-B*39:01-C*07:02-DRB1*08:03-DQB1*06:01  USA NMDP Hawaiian or other Pacific Islander 0.232911,499
 686  A*34:01-B*15:21-C*04:03-DRB1*15:01-DQB1*06:01  Malaysia Peninsular Malay 0.2314951
 687  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
 688  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
 689  DRB1*08:03:02-DQB1*06:01-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 0.2280496
 690  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
 691  A*01:01-B*57:01-C*06:02-DRB1*15:01-DQB1*06:01  India Tamil Nadu 0.22552,492
 692  A*24:02-B*40:01-C*03:04-DRB1*08:03-DQB1*06:01  Malaysia Peninsular Chinese 0.2244194
 693  DQB1*06:01-DPB1*14:01  China Inner Mongolia Autonomous Region Northeast 0.2230496
 694  A*03:01-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  USA Asian pop 2 0.22201,772
 695  DRB1*15:02:01-DQB1*06:01-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 0.2210496
 696  A*03:01-B*52:01-C*12:02-DRB1*15:02-DQB1*06:01  India East UCBB 0.21822,403
 697  A*11:01-B*40:06-C*15:02-DRB1*15:01-DQB1*06:01  India Central UCBB 0.21744,204
 698  A*11:01-B*40:01-C*03:04-DRB1*15:02-DQB1*06:01  India East UCBB 0.21652,403
 699  A*24:02-B*52:01-C*12:03-DRB1*13:01-DQA1*01:03-DQB1*06:01-DPB1*02:01  Nicaragua Managua 0.2165339
 700  A*69:01-B*38:01-C*12:03-DRB1*15:02-DQA1*01:03-DQB1*06:01-DPB1*02:01  Nicaragua Managua 0.2165339

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 601 to 700 (from 4,764) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 48  


   

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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