Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Displaying 1 to 83 (from 83) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*24:02-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  Iran Gorgan 0.780064
 2  A*23:01:01-B*57:01:01-C*06:02:01-DRB1*13:01  Costa Rica African -Caribbean (G) 0.4902102
 3  A*02:01:01-B*57:01:01-C*06:02:01-DRB1*13:01:01-DQA1*01:03:01-DQB1*06:03-DPA1*01:03:01-DPB1*02:01:02  Russia Belgorod region 0.3268153
 4  A*01:01-B*57:01-C*06:02-DRB1*13:01-DQA1*02:01-DQB1*06:03-DPB1*13:01  USA San Diego 0.2600496
 5  A*02:01-B*57:01-C*06:02-DRB1*13:01-DQA1*02:01-DQB1*02:02-DPB1*11:01  USA San Diego 0.2600496
 6  A*01:01-B*57:01-C*06:02-DRB1*13:01  Germany DKMS - United Kingdom minority 0.24301,043
 7  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*13:01:01-DQB1*06:03:01  Spain, Canary Islands, Gran canaria island 0.2300215
 8  A*29:02:01-B*57:01:01-C*06:02:01-DRB1*13:01:01-DQB1*06:03:01  Spain, Canary Islands, Gran canaria island 0.2300215
 9  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*13:01-DQB1*06:03  Costa Rica Central Valley Mestizo (G) 0.2262221
 10  A*01:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  India South UCBB 0.208611,446
 11  A*02:11-B*57:01-C*06:02-DRB1*13:01-DQB1*03:03  Malaysia Peninsular Indian 0.1845271
 12  A*11:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:14  Malaysia Peninsular Indian 0.1845271
 13  A*31:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  Malaysia Peninsular Indian 0.1845271
 14  A*26:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  India North UCBB 0.16245,849
 15  A*03:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  Italy pop 5 0.1400975
 16  A*01:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  India Central UCBB 0.13694,204
 17  A*01:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  India West UCBB 0.12665,829
 18  A*01:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  India Tamil Nadu 0.11732,492
 19  A*02:01:01-B*57:01:01-C*06:02:01-DRB1*13:01:01-DQB1*06:03:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.102328,927
 20  A*03:01-B*57:01-C*06:02-DRB1*13:01  Italy pop 5 0.1000975
 21  A*01:01-B*57:01-C*06:02-DRB1*13:01  Poland DKMS 0.098320,653
 22  A*02:01-B*57:01-C*06:02-DRB1*13:01  Germany DKMS - Austria minority 0.09501,698
 23  A*31:01-B*57:01-C*06:02-DRB1*13:01  Germany DKMS - Portugal minority 0.08501,176
 24  A*01:01-B*57:01-C*06:02-DRB1*13:01  Germany DKMS - China minority 0.07801,282
 25  A*01:01-B*57:01-C*06:02-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*04:01  Sri Lanka Colombo 0.0700714
 26  A*68:01-B*57:01-C*06:02-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*51:01  Sri Lanka Colombo 0.0700714
 27  A*01:01-B*57:01-C*06:02-DRB1*13:01  Germany DKMS - Portugal minority 0.07001,176
 28  A*02:01:01-B*57:01:01-C*06:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.059023,595
 29  A*24:02-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  India Tamil Nadu 0.05812,492
 30  A*02:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03-DPB1*04:01  Russia Karelia 0.05651,075
 31  A*03:01-B*57:01-C*06:02-DRB1*13:01  Germany DKMS - United Kingdom minority 0.05601,043
 32  A*24:02-B*57:01-C*06:02-DRB1*13:01  Germany DKMS - United Kingdom minority 0.05401,043
 33  A*02:01-B*57:01-C*06:02-DRB1*13:01  Germany DKMS - Romania minority 0.05101,234
 34  A*02:01-B*57:01-C*06:02-DRB1*13:01  Poland DKMS 0.050520,653
 35  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.049223,595
 36  A*01:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  India North UCBB 0.04915,849
 37  A*32:01-B*57:01-C*06:02-DRB1*13:01  Germany DKMS - United Kingdom minority 0.04801,043
 38  A*26:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  India Central UCBB 0.04764,204
 39  A*11:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  India Tamil Nadu 0.04682,492
 40  A*24:02-B*57:01-C*06:02-DRB1*13:01  Germany DKMS - Spain minority 0.04501,107
 41  A*02:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 42  A*68:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 43  A*01:01:01:01-B*57:01:01-C*06:02:01:01-DRB1*13:01:01-DQB1*06:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 44  A*02:01:01:01-B*57:01:01-C*06:02:01:01-DRB1*13:01:01-DQB1*06:03:01  Russia Nizhny Novgorod, Russians 0.03311,510
 45  A*29:02-B*57:01-C*06:02-DRB1*13:01  Germany DKMS - Austria minority 0.02901,698
 46  A*26:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  India West UCBB 0.02155,829
 47  A*68:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  India South UCBB 0.021011,446
 48  A*02:06-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  India Tamil Nadu 0.02012,492
 49  A*31:01:02-B*57:01:01-C*06:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.018223,595
 50  A*01:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03-DPB1*04:01  Germany DKMS - German donors 0.01813,456,066
 51  A*02:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03-DPB1*04:01  Germany DKMS - German donors 0.01583,456,066
 52  A*01:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03-DPB1*02:01  Germany DKMS - German donors 0.01393,456,066
 53  A*02:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03-DPB1*02:01  Germany DKMS - German donors 0.01383,456,066
 54  A*01:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03-DPB1*03:01  Germany DKMS - German donors 0.01313,456,066
 55  A*24:02-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  India North UCBB 0.01185,849
 56  A*01:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  USA Asian pop 2 0.01101,772
 57  A*01:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  Germany DKMS - Turkey minority 0.01104,856
 58  A*02:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  USA Asian pop 2 0.01101,772
 59  A*31:01-B*57:01-C*06:02-DRB1*13:01  Poland DKMS 0.010420,653
 60  A*01:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03-DPB1*04:02  Germany DKMS - German donors 0.01013,456,066
 61  A*01:01-B*57:01-C*06:02-DRB1*13:01-DQB1*05:03  India Tamil Nadu 0.01002,492
 62  A*02:11-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  Germany DKMS - Turkey minority 0.01004,856
 63  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*13:01:01-DPB1*09:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00955,266
 64  A*01:01:01-B*57:01:01-C*06:02:01-DRB1*13:01:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.00945,266
 65  A*31:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  India South UCBB 0.009011,446
 66  A*24:02:01-B*57:01:01-C*06:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.009023,595
 67  A*01:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:110  India West UCBB 0.00865,829
 68  A*33:03-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  India South UCBB 0.008611,446
 69  A*24:02-B*57:01-C*06:02-DRB1*13:01-DQB1*06:144N  India North UCBB 0.00855,849
 70  A*30:01:01-B*57:01:01-C*06:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.008523,595
 71  A*26:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  India South UCBB 0.006711,446
 72  A*02:01:01-B*57:01:01-C*06:02:01-DRB1*13:01:01-DQB1*06:03:02  Poland BMR 0.006423,595
 73  A*02:01-B*57:01-C*06:02-DRB1*13:01  Hong Kong Chinese BMDR 0.00617,595
 74  A*02:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  India South UCBB 0.005311,446
 75  A*01:01-B*57:01-C*06:02-DRB1*13:01  Hong Kong Chinese BMDR 0.00507,595
 76  A*02:06-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  India South UCBB 0.004811,446
 77  A*03:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:03  India South UCBB 0.004611,446
 78  A*03:01-B*57:01-C*06:02-DRB1*13:01-DQB1*06:88  India South UCBB 0.004411,446
 79  A*25:01:01-B*57:01:01-C*06:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.004123,595
 80  A*03:01-B*57:01-C*06:02-DRB1*13:01  Poland DKMS 0.003320,653
 81  A*03:02-B*57:01-C*06:02-DRB1*13:01  Poland DKMS 0.002420,653
 82  A*26:01:01-B*57:01:01-C*06:02:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.002423,595
 83  A*24:02-B*57:01-C*06:02-DRB1*13:01  Poland DKMS 0.001220,653

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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