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 65 (from 65) 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-DQA1*01:01-DQB1*05:01-DPA1*01:03-DPB1*02:01  United Arab Emirates Pop 1 0.4673570
 20  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Italy pop 5 0.4400975
 21  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Vietnamese 0.366843,540
 22  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Chinese 0.310399,672
 23  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Germany DKMS - Turkey minority 0.29404,856
 24  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
 25  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Malaysia Peninsular Malay 0.2629951
 26  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
 27  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Japanese 0.199324,582
 28  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
 29  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
 30  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
 31  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Germany DKMS - Italy minority 0.17301,159
 32  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
 33  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
 34  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
 35  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
 36  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Filipino 0.106750,614
 37  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.10304,335
 38  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
 39  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
 40  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
 41  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  USA Hispanic pop 2 0.09401,999
 42  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQA1*01:01-DQB1*05:01-DPA1*01:03-DPB1*04:01  United Arab Emirates Pop 1 0.0935570
 43  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
 44  A*01:01-B*37:01-C*06:02-DRB1*10:02-DQB1*05:01  India Tamil Nadu 0.08342,492
 45  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
 46  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
 47  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
 48  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
 49  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Caribean Hispanic 0.0659115,374
 50  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
 51  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01-DPB1*04:01  Russia Karelia 0.05621,075
 52  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
 53  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP African 0.048928,557
 54  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQA1*01:05-DQB1*05:01-DPA1*01:03-DPB1*02:01  United Arab Emirates Pop 1 0.0467570
 55  A*01:01-B*37:04-C*06:02-DRB1*10:01-DQB1*05:01  Germany DKMS - Italy minority 0.04301,159
 56  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Caribean Black 0.042433,328
 57  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.03421,463
 58  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
 59  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
 60  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
 61  A*01:01-B*37:04-C*06:02-DRB1*10:01-DQB1*05:01  India Central UCBB 0.02384,204
 62  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:03  India Tamil Nadu 0.02092,492
 63  A*01:01-B*37:01-C*06:35-DRB1*10:01-DQB1*05:01  India North UCBB 0.00855,849
 64  A*01:01-B*37:04-C*06:02-DRB1*10:01-DQB1*05:01  India North UCBB 0.00855,849
 65  A*01:01:01-B*37:01:01-C*06:70:01-DRB1*10:01:01-DQB1*05:01:01  Poland BMR 0.002123,595

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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