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 : 
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Sample Size:      Sample Year:     Loci Tested: 
Displaying 1 to 62 (from 62) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*33-B*44-C*14-DRB1*15  Myanmar Rakhine 1.042048
 2  A*02:02-B*44:03-C*14:03-DRB1*15:03-DQA1*05:01-DQB1*03:01-DPB1*13:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 3  A*29:02-B*44:03-C*14:03-DRB1*15:03-DQA1*01:02-DQB1*06:02-DPB1*18:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 4  A*33:03-B*44:03-C*14:03-DRB1*15:01  Japan pop 16 0.110018,604
 5  A*33:03-B*44:03-C*14:03-DRB1*15:02  Japan pop 16 0.089018,604
 6  A*31:01-B*44:03-C*14:03-DRB1*15:02-DQA1*01:03-DQB1*06:09-DPB1*03:01  Sri Lanka Colombo 0.0700714
 7  A*33:03-B*44:03-C*14:03-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.07003,078
 8  A*33:03-B*44:03-C*14:03-DRB1*15:02-DQA1*01:03-DQB1*06:01-DPA1*02:01-DPB1*09:01  Japan pop 17 0.07003,078
 9  A*33:03-B*44:03-C*14:02-DRB1*15:01-DQB1*06:02  Malaysia Peninsular Malay 0.0526951
 10  A*03:01-B*44:03-C*14:03-DRB1*15:03-DQB1*06:02  USA African American pop 4 0.04402,411
 11  A*34:02-B*44:03-C*14:03-DRB1*15:03-DQB1*06:02  USA African American pop 4 0.04402,411
 12  A*11:01-B*44:02-C*14:02-DRB1*15:02-DQB1*04:02  Colombia Bogotá Cord Blood 0.03421,463
 13  A*02:07-B*44:03-C*14:03-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 14  A*33:03-B*44:03-C*14:03-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPA1*02:01-DPB1*13:01  Japan pop 17 0.03003,078
 15  A*33:03-B*44:03-C*14:03-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 16  A*02:01-B*44:03-C*14:03-DRB1*15:01  Germany DKMS - Greece minority 0.02601,894
 17  A*26:01-B*44:03-C*14:03-DRB1*15:01-DQB1*06:02  Germany DKMS - Turkey minority 0.02104,856
 18  A*33:03-B*44:03-C*14:03-DRB1*15:02-DQB1*06:01  India Central UCBB 0.01194,204
 19  A*33:03-B*44:03-C*14:03-DRB1*15:01  Hong Kong Chinese BMDR 0.00667,595
 20  A*02:01-B*44:03-C*14:03-DRB1*15:02  Japan pop 16 0.005018,604
 21  A*02:07-B*44:03-C*14:03-DRB1*15:01  Japan pop 16 0.005018,604
 22  A*26:01-B*44:03-C*14:03-DRB1*15:01  Japan pop 16 0.005018,604
 23  A*26:01-B*44:03-C*14:03-DRB1*15:02  Japan pop 16 0.005018,604
 24  A*02:01-B*44:02-C*14:02-DRB1*15:01  Poland DKMS 0.002420,653
 25  A*02:01:01-B*44:02:01-C*14:02:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.002123,595
 26  A*02:01:01-B*44:03:01-C*14:03-DRB1*15:01:01-DQB1*05:02:01  Poland BMR 0.002123,595
 27  A*32:01-B*44:02-C*14:02-DRB1*15:01-DQB1*06:01  India Tamil Nadu 0.00055702,492
 28  A*32:01-B*44:02-C*14:55-DRB1*15:01-DQB1*06:01  India Tamil Nadu 0.00055702,492
 29  A*32:01-B*44:03-C*14:02-DRB1*15:01-DQB1*06:01  India Tamil Nadu 0.00055702,492
 30  A*32:01-B*44:03-C*14:55-DRB1*15:01-DQB1*06:01  India Tamil Nadu 0.00055702,492
 31  A*32:02-B*44:02-C*14:02-DRB1*15:01-DQB1*06:01  India Tamil Nadu 0.00055702,492
 32  A*32:02-B*44:02-C*14:55-DRB1*15:01-DQB1*06:01  India Tamil Nadu 0.00055702,492
 33  A*32:02-B*44:03-C*14:02-DRB1*15:01-DQB1*06:01  India Tamil Nadu 0.00055702,492
 34  A*32:02-B*44:03-C*14:55-DRB1*15:01-DQB1*06:01  India Tamil Nadu 0.00055702,492
 35  A*32:08-B*44:02-C*14:02-DRB1*15:01-DQB1*06:01  India Tamil Nadu 0.00055702,492
 36  A*32:08-B*44:02-C*14:55-DRB1*15:01-DQB1*06:01  India Tamil Nadu 0.00055702,492
 37  A*32:08-B*44:03-C*14:02-DRB1*15:01-DQB1*06:01  India Tamil Nadu 0.00055702,492
 38  A*32:08-B*44:03-C*14:55-DRB1*15:01-DQB1*06:01  India Tamil Nadu 0.00055702,492
 39  A*32:01-B*44:02-C*14:02-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.00013902,492
 40  A*32:01-B*44:02-C*14:02-DRB1*15:02-DQB1*06:01  India Tamil Nadu 0.00013902,492
 41  A*32:01-B*44:02-C*14:55-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.00013902,492
 42  A*32:01-B*44:02-C*14:55-DRB1*15:02-DQB1*06:01  India Tamil Nadu 0.00013902,492
 43  A*32:01-B*44:03-C*14:02-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.00013902,492
 44  A*32:01-B*44:03-C*14:02-DRB1*15:02-DQB1*06:01  India Tamil Nadu 0.00013902,492
 45  A*32:01-B*44:03-C*14:55-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.00013902,492
 46  A*32:01-B*44:03-C*14:55-DRB1*15:02-DQB1*06:01  India Tamil Nadu 0.00013902,492
 47  A*32:02-B*44:02-C*14:02-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.00013902,492
 48  A*32:02-B*44:02-C*14:02-DRB1*15:02-DQB1*06:01  India Tamil Nadu 0.00013902,492
 49  A*32:02-B*44:02-C*14:55-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.00013902,492
 50  A*32:02-B*44:02-C*14:55-DRB1*15:02-DQB1*06:01  India Tamil Nadu 0.00013902,492
 51  A*32:02-B*44:03-C*14:02-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.00013902,492
 52  A*32:02-B*44:03-C*14:02-DRB1*15:02-DQB1*06:01  India Tamil Nadu 0.00013902,492
 53  A*32:02-B*44:03-C*14:55-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.00013902,492
 54  A*32:02-B*44:03-C*14:55-DRB1*15:02-DQB1*06:01  India Tamil Nadu 0.00013902,492
 55  A*32:08-B*44:02-C*14:02-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.00013902,492
 56  A*32:08-B*44:02-C*14:02-DRB1*15:02-DQB1*06:01  India Tamil Nadu 0.00013902,492
 57  A*32:08-B*44:02-C*14:55-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.00013902,492
 58  A*32:08-B*44:02-C*14:55-DRB1*15:02-DQB1*06:01  India Tamil Nadu 0.00013902,492
 59  A*32:08-B*44:03-C*14:02-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.00013902,492
 60  A*32:08-B*44:03-C*14:02-DRB1*15:02-DQB1*06:01  India Tamil Nadu 0.00013902,492
 61  A*32:08-B*44:03-C*14:55-DRB1*15:01-DQB1*06:02  India Tamil Nadu 0.00013902,492
 62  A*32:08-B*44:03-C*14:55-DRB1*15:02-DQB1*06:01  India Tamil Nadu 0.00013902,492

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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