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 1 to 54 (from 54) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Tamil Nadu 1.95162,492
 2  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India South UCBB 1.785911,446
 3  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India West UCBB 1.43205,829
 4  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP South Asian Indian 1.3953185,391
 5  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Northeast UCBB 1.3514296
 6  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India East UCBB 1.34252,403
 7  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Malaysia Peninsular Indian 1.2915271
 8  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Central UCBB 1.27444,204
 9  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQA1*01:01-DQB1*05:01-DPB1*02:01  Sri Lanka Colombo 1.2605714
 10  A*01:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  India Karnataka Kannada Speaking 1.1490174
 11  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India North UCBB 1.04995,849
 12  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Southeast Asian 1.034527,978
 13  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  South Korea pop 3 1.0000485
 14  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Korean 0.923177,584
 15  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  USA Asian pop 2 0.88901,772
 16  A*01:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 0.5960356
 17  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQA1*03:01-DQB1*05:01-DPB1*02:01  USA San Diego 0.5210496
 18  A*01:01:01:01-B*37:01:01-C*06:02:01:01-DRB1*10:01:01-DQB1*05:01  Russia Bashkortostan, Tatars 0.5208192
 19  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Italy pop 5 0.4400975
 20  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Vietnamese 0.366843,540
 21  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Chinese 0.310399,672
 22  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Germany DKMS - Turkey minority 0.29404,856
 23  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Malaysia Peninsular Malay 0.2629951
 24  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
 25  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Japanese 0.199324,582
 26  A*01:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 27  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  USA NMDP American Indian South or Central America 0.17915,926
 28  A*01:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  China Zhejiang Han 0.17301,734
 29  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Germany DKMS - Italy minority 0.17301,159
 30  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP European Caucasian 0.15901,242,890
 31  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQA1*01:05-DQB1*05:01-DPA1*01:03-DPB1*02:01  Japan pop 17 0.13003,078
 32  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Middle Eastern or North Coast of Africa 0.125470,890
 33  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Hispanic South or Central American 0.1163146,714
 34  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Filipino 0.106750,614
 35  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.10304,335
 36  A*01:01:01:01-B*37:01:01-C*06:02:01:01-DRB1*10:01:01-DQB1*05:01  Russia Nizhny Novgorod, Russians 0.09931,510
 37  A*01:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01-DPB1*03:01:01  Saudi Arabia pop 6 (G) 0.096028,927
 38  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP North American Amerindian 0.094735,791
 39  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  USA Hispanic pop 2 0.09401,999
 40  A*01:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  Poland BMR 0.089723,595
 41  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Mexican or Chicano 0.0831261,235
 42  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQA1*01:01-DQB1*05:01-DPB1*04:01  Sri Lanka Colombo 0.0700714
 43  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQA1*01:01-DQB1*05:01-DPB1*09:01  Sri Lanka Colombo 0.0700714
 44  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQA1*01:05-DQB1*05:01-DPA1*02:02-DPB1*05:01  Japan pop 17 0.07003,078
 45  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Caribean Hispanic 0.0659115,374
 46  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01-DPB1*02:01  Germany DKMS - German donors 0.06383,456,066
 47  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01-DPB1*04:01  Russia Karelia 0.05621,075
 48  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01-DPB1*04:01  Germany DKMS - German donors 0.05293,456,066
 49  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP African 0.048928,557
 50  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Caribean Black 0.042433,328
 51  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.03421,463
 52  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP African American pop 2 0.0303416,581
 53  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQA1*01:05-DQB1*05:01-DPA1*01:03-DPB1*04:01  Japan pop 17 0.03003,078
 54  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQA1*01:05-DQB1*05:01-DPA1*02:01-DPB1*05:01  Japan pop 17 0.03003,078

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).




   

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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