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 63 (from 63) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*26:01:01-B*35:03:01-C*12:03:01-DRB1*15:01:01-DQB1*03:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Parda 0.5882170
 2  A*02:11:01-B*35:03:01-C*12:03:01-DRB1*15:01:01-DQB1*06:01:01  India Karnataka Kannada Speaking 0.5750174
 3  A*02:01-B*35:03-C*12:03-DRB1*15:01-DQB1*05:01:01  England North West 0.2000298
 4  A*30:01-B*35:03-C*12:03-DRB1*15:01-DQB1*06:01  Malaysia Peninsular Indian 0.1845271
 5  A*24:02-B*35:03-C*12:03-DRB1*15:01-DQB1*06:01  India East UCBB 0.08102,403
 6  A*01:01-B*35:03-C*12:03-DRB1*15:01  Germany DKMS - Spain minority 0.06001,107
 7  A*24:02-B*35:03-C*12:03-DRB1*15:01-DQB1*06:02-DPB1*14:01  Russia Karelia 0.05651,075
 8  A*01:01-B*35:03-C*12:03-DRB1*15:01-DQB1*06:02  USA African American pop 4 0.04402,411
 9  A*33:03-B*35:03-C*12:03-DRB1*15:01-DQB1*05:02  USA Asian pop 2 0.04401,772
 10  A*03:01-B*35:03-C*12:03-DRB1*15:01-DQB1*06:01  India Tamil Nadu 0.04352,492
 11  A*33:03-B*35:03-C*12:03-DRB1*15:01  Hong Kong Chinese BMDR 0.04317,595
 12  A*11:01-B*35:03-C*12:03-DRB1*15:01-DQB1*05:02  Germany DKMS - Italy minority 0.04301,159
 13  A*24:02-B*35:03-C*12:03-DRB1*15:01-DQB1*06:02  Germany DKMS - Italy minority 0.04301,159
 14  A*26:01-B*35:03-C*12:03-DRB1*15:01  Germany DKMS - Portugal minority 0.04301,176
 15  A*23:01-B*35:03-C*12:03-DRB1*15:01  Germany DKMS - Romania minority 0.04101,234
 16  A*33:03:01-B*35:03:01-C*12:03:01-DRB1*15:01:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.04075,266
 17  A*03:01-B*35:03-C*12:03-DRB1*15:01  Germany DKMS - France minority 0.03601,406
 18  A*03:01-B*35:03-C*12:03-DRB1*15:01-DQB1*06:02  Colombia Bogotá Cord Blood 0.03421,463
 19  A*11:01-B*35:03-C*12:03-DRB1*15:01-DQB1*06:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 20  A*24:02-B*35:03-C*12:03-DRB1*15:01-DQB1*06:02  Germany DKMS - Turkey minority 0.03304,856
 21  A*02:01-B*35:03-C*12:03-DRB1*15:01  Germany DKMS - Croatia minority 0.02902,057
 22  A*24:02-B*35:03-C*12:03-DRB1*15:01-DQB1*06:01  India Central UCBB 0.02394,204
 23  A*68:01-B*35:03-C*12:03-DRB1*15:01-DQB1*06:02  India Central UCBB 0.02384,204
 24  A*02:11-B*35:03-C*12:03-DRB1*15:01-DQB1*06:140  India Tamil Nadu 0.02012,492
 25  A*24:02-B*35:03-C*12:03-DRB1*15:01-DQB1*06:01  India North UCBB 0.01745,849
 26  A*33:03-B*35:03-C*12:03-DRB1*15:01-DQB1*06:01  India West UCBB 0.01715,829
 27  A*32:01-B*35:03-C*12:03-DRB1*15:01-DQB1*06:01  India North UCBB 0.01695,849
 28  A*03:01-B*35:03-C*12:03-DRB1*15:01-DQB1*06:02  India North UCBB 0.01385,849
 29  A*02:01:01-B*35:03:01-C*12:03:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.013723,595
 30  A*24:02-B*35:03-C*12:03-DRB1*15:01-DQB1*06:48  India Central UCBB 0.01194,204
 31  A*02:01-B*35:03-C*12:03-DRB1*15:01-DQB1*06:01  India Central UCBB 0.01114,204
 32  A*11:01-B*35:03-C*12:03-DRB1*15:01-DQB1*06:01  India South UCBB 0.009411,446
 33  A*24:02-B*35:03-C*12:03-DRB1*15:01-DQB1*06:01  India West UCBB 0.00925,829
 34  A*01:01:01-B*35:03:01-C*12:03:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.008923,595
 35  A*33:03-B*35:03-C*12:03-DRB1*15:01-DQB1*06:01  India South UCBB 0.008911,446
 36  A*01:01-B*35:03-C*12:03-DRB1*15:01-DQB1*06:02  India West UCBB 0.00865,829
 37  A*02:01-B*35:03-C*12:03-DRB1*15:01-DQB1*05:03  India West UCBB 0.00865,829
 38  A*03:01-B*35:03-C*12:03-DRB1*15:01-DQB1*05:03  India North UCBB 0.00865,849
 39  A*03:01-B*35:03-C*12:03-DRB1*15:01-DQB1*06:01  India West UCBB 0.00865,829
 40  A*24:02-B*35:03-C*12:03-DRB1*15:01-DQB1*06:02  India West UCBB 0.00865,829
 41  A*31:01-B*35:03-C*12:03-DRB1*15:01-DQB1*06:01  India West UCBB 0.00865,829
 42  A*01:01-B*35:03-C*12:03-DRB1*15:01-DQB1*06:03  India North UCBB 0.00855,849
 43  A*11:01-B*35:03-C*12:03-DRB1*15:01-DQB1*05:03  India North UCBB 0.00855,849
 44  A*11:01-B*35:03-C*12:03-DRB1*15:01-DQB1*06:01  India West UCBB 0.00855,829
 45  A*24:02-B*35:03-C*12:03-DRB1*15:01-DQB1*05:02  India North UCBB 0.00855,849
 46  A*24:07-B*35:03-C*12:03-DRB1*15:01-DQB1*06:01  India North UCBB 0.00855,849
 47  A*26:01-B*35:03-C*12:03-DRB1*15:01-DQB1*05:03  India North UCBB 0.00855,849
 48  A*31:01-B*35:03-C*12:03-DRB1*15:01-DQB1*06:01  India North UCBB 0.00855,849
 49  A*68:01-B*35:03-C*12:03-DRB1*15:01-DQB1*06:02  India North UCBB 0.00855,849
 50  A*24:02-B*35:03-C*12:03-DRB1*15:01  Poland DKMS 0.008020,653
 51  A*02:01-B*35:03-C*12:03-DRB1*15:01-DQB1*06:02  India West UCBB 0.00765,829
 52  A*24:02-B*35:03-C*12:03-DRB1*15:01-DQB1*06:01  India South UCBB 0.005811,446
 53  A*03:01-B*35:03-C*12:03-DRB1*15:01-DQB1*06:01  India South UCBB 0.005211,446
 54  A*24:02-B*35:03-C*12:03-DRB1*15:01-DQB1*06:02  India South UCBB 0.005211,446
 55  A*24:07-B*35:03-C*12:03-DRB1*15:01-DQB1*06:01  India South UCBB 0.004011,446
 56  A*24:07-B*35:03-C*12:03-DRB1*15:01-DQB1*06:02  India South UCBB 0.004011,446
 57  A*03:01-B*35:03-C*12:03-DRB1*15:01-DQB1*06:02  India South UCBB 0.003611,446
 58  A*02:06-B*35:03-C*12:03-DRB1*15:01-DQB1*05:02  India South UCBB 0.003411,446
 59  A*03:01-B*35:03-C*12:03-DRB1*15:01  Poland DKMS 0.003120,653
 60  A*02:01-B*35:03-C*12:03-DRB1*15:01  Poland DKMS 0.002720,653
 61  A*31:01-B*35:03-C*12:03-DRB1*15:01  Poland DKMS 0.002720,653
 62  A*31:01-B*35:03-C*12:03-DRB1*15:01-DQB1*06:01  India Central UCBB 0.00204,204
 63  A*03:01:01-B*35:03:01-C*12:03:01-DRB1*15:01:01-DQB1*06:02:01  Poland BMR 0.001423,595

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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