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 100 (from 1,501) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 16  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*30-B*13-C*06:02  Pakistan Karachi Parsi 11.000091
 2  B*13-C*06:02  Pakistan Kalash 7.200069
 3  A*30-B*13-C*06:02  Pakistan Kalash 6.500069
 4  A*31:08-B*13:02-C*06:02  India West Coast Parsi 4.700050
 5  A*30:01-B*13:02-C*06:02-DRB1*07:01  Germany DKMS - China minority 4.51801,282
 6  B*13-C*06:02  Pakistan Mixed Pathan 4.4000100
 7  A*30:01-B*13:02-C*06:02-DRB1*07:01  Taiwan pop 2 3.9000364
 8  A*30-B*13-C*06:02  Pakistan Mixed Pathan 3.9000100
 9  A*02:01:01:01-B*13:02:01-C*06:02:01:01-DRB1*07:01:01:01-DQB1*02:02  Russia Bashkortostan, Tatars 3.6238192
 10  A*02:01:01:01-B*13:02:01-C*06:02:01:01-DRB1*07:01:01:01-DQB1*02:02  Russia Bashkortostan, Bashkirs 3.3333120
 11  A*02:01:01-B*13:02:01-C*06:02:01:01-DRB1*07:01-DQB1*02:02  Russia Bashkortostan, Bashkirs 3.3333120
 12  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  China Zhejiang Han 3.11091,734
 13  A*30:01-B*13:01-C*06:03  India Khandesh Region Pawra 3.100050
 14  A*30:01-B*13:02-C*06:02  South Korea pop 3 3.1000485
 15  A*30-B*13-C*06:02-DRB1*07:01-DQB1*02  Russia Transbaikal Territory Buryats 3.0000150
 16  B*13-C*06  Macedonia 2.9720286
 17  B*13:02-C*06:02-DRB1*07:01  South Korea pop 3 2.9000485
 18  A*02:01-B*13:02-C*06:02-DRB1*07:01  Russia Bering Island Aleuts 2.8846104
 19  A*30-B*13-C*06:02  South Korea pop 1 2.8000324
 20  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01/02:02  South Korea pop 3 2.7000485
 21  A*11:01:01-B*13:02:01-C*06:02:01-DRB1*01:02:01-DQB1*05:01:01-DPA1*03:01:01-DPB1*105:01:01  Brazil Barra Mansa Rio State Black 2.381073
 22  B*13:02-C*06:02  USA Asian pop 2 2.27401,772
 23  A*30:01-B*13:02-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Korean 2.258577,584
 24  A*02:01-B*13:02-C*06:02-DRB1*07:01  Germany DKMS - Bosnia and Herzegovina minority 2.24501,028
 25  A*02-B*13-C*06-DRB1*07  Russia Tatars 2.2100355
 26  B*13:02-C*06:02  Uganda Kampala 2.2000161
 27  A*30:01-B*13:02-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Chinese 2.025499,672
 28  A*24-B*13-C*06  Italy East Sicily 2.000050
 29  B*13:02-C*06:02  Tunisia 2.0000100
 30  B*13:02-C*06:02  USA North American Native 1.9000187
 31  A*02:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01-DPB1*04:01  Russia Karelia 1.84081,075
 32  B*13:02-C*06:02  USA Asian 1.8000358
 33  B*13:02-C*06:02  Taiwan Hakka 1.800055
 34  A*02:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 1.775923,595
 35  B*13:02-C*06:02  Ireland Northern 1.70001,000
 36  A*02:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DQA1*02:01:01-DQB1*02:02-DPA1*01:03:01-DPB1*04:01:01  Russia Belgorod region 1.6340153
 37  A*26:01-B*13:02-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02  Kosovo 1.6130124
 38  A*02:01-B*13:02-C*06:02-DRB1*07:01  Poland DKMS 1.609720,653
 39  A*02-B*13-C*06:02-DRB1*07-DQB1*02  Russia North Ossetian 1.6000127
 40  A*30:01-B*13:02-C*06:02  Uganda Kampala 1.6000161
 41  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:02  Italy pop 5 1.6000975
 42  A*02:01:01:01-B*13:02:01-C*06:02:01:01-DRB1*07:01:01-DQB1*02:02  Russia Nizhny Novgorod, Russians 1.57491,510
 43  A*02-B*13-C*06-DRB1*07  Macedonia MBMDR - Albanian 1.5625128
 44  A*03:01-B*13:01-C*06:02-DRB1*07:01-DQB1*02:01  Iran Gorgan 1.560064
 45  A*30:01-B*13:01-C*06:02-DRB1*15:01-DQB1*02:01  Iran Gorgan 1.560064
 46  A*30:01-B*13:02-C*06:02  China Canton Han 1.5000264
 47  B*13:02-C*06:02  Kenya Nandi 1.5000240
 48  B*13-C*06  Mexico Tapachula, Chiapas Mestizo Population 1.388972
 49  A*02:01-B*13:02-C*06:02-DRB1*07:01  Germany DKMS - Austria minority 1.36301,698
 50  A*30:01-B*13:02-C*06:02  Italy pop 5 1.3400975
 51  A*03:01-B*13:02-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02  Brazil Puyanawa 1.3333150
 52  A*30:01-B*13:02-C*06:02  USA Asian 1.3000358
 53  B*13:02-C*06:02  USA Caucasian pop 2 1.3000265
 54  A*30:01-B*13:02-C*06:02-DRB1*07:01  Hong Kong Chinese BMDR 1.28347,595
 55  A*02:01:01-B*13:02:01-C*06:02:01-DRB1*07:01  Costa Rica Amerindians (G) 1.2647125
 56  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01  Germany DKMS - Italy minority 1.25101,159
 57  B*13:02-C*06:02  Italy pop 5 1.2300975
 58  A*02:01-B*13:02-C*06:02  Ireland South 1.2000250
 59  A*30:01-B*13:02-C*06:02  USA San Francisco Caucasian 1.2000220
 60  A*30-B*13-C*06  USA San Francisco Caucasian 1.2000220
 61  B*13:02-C*06:02  USA African American 1.2000252
 62  A*03-B*13-C*06:02-DRB1*03-DQB1*02  Russia North Ossetian 1.1800127
 63  A*30:01-B*13:02-C*06:02-DRB1*07:01  Italy pop 5 1.1800975
 64  A*32-B*13-C*06:02-DRB1*07-DQB1*02  Russia North Ossetian 1.1800127
 65  B*13:02-C*06:02  USA Hispanic pop 2 1.17901,999
 66  B*13:02-C*06:02  USA Hispanic 1.1000234
 67  B*13:02-C*06:02  Uganda Kampala pop 2 1.1000175
 68  A*30:01-B*13:02-C*06:02-DRB1*07:01  USA Italy Ancestry 1.0990273
 69  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  India Andhra Pradesh Telugu Speaking 1.0753186
 70  A*02:01-B*13:02-C*06:02-DRB1*07:01  Germany DKMS - Croatia minority 1.07102,057
 71  B*13:02-C*06:02  Mexico Mexico City Mestizo pop 2 1.0600234
 72  A*30:01:01-B*13:02:01-C*06:02:01:01-DRB1*07:01:01-DQB1*02:02  Russia Nizhny Novgorod, Russians 1.05641,510
 73  A*29:11-B*13:02:01-C*06:02:01-DRB1*12:01:01-DQB1*05:01:01-DPB1*105:01:01  South African Black 1.0560142
 74  A*02:01-B*13:02-C*06:02-DRB1*07:01  Germany DKMS - Portugal minority 1.05301,176
 75  A*02-B*13-C*06  Macedonia 1.0490286
 76  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*17:01  USA San Diego 1.0420496
 77  A*30-B*13-C*06-DRB1*13-DQB1*05  Sudan Khartoum 1.020098
 78  A*01-B*13-C*06  Italy East Sicily 1.000050
 79  A*02-B*13-C*06  Italy East Sicily 1.000050
 80  A*03:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:02  Poland 1.0000200
 81  A*24:07-B*13:01:01-C*06:02:01  South African Indian population 1.000050
 82  A*32-B*13-C*06  Italy East Sicily 1.000050
 83  A*68:02-B*13:02-C*06:02  Kenya Nandi 1.0000240
 84  A*30:01-B*13:02-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Southeast Asian 0.989427,978
 85  A*30:01-B*13:02-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP South Asian Indian 0.9874185,391
 86  A*30:01-B*13:02-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Middle Eastern or North Coast of Africa 0.983870,890
 87  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01  Germany DKMS - Turkey minority 0.98204,856
 88  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01  USA Asian pop 2 0.97801,772
 89  A*30:01:01-B*13:02:01-C*06:02:01  England Blood Donors of Mixed Ethnicity 0.9634519
 90  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  Spain, Canary Islands, Gran canaria island 0.9300215
 91  A*02-B*13-C*06-DRB1*04  Iran pop 4 0.9000855
 92  A*30:01-B*13:02-C*06:02-DRB1*07:01  Poland DKMS 0.898720,653
 93  A*24:02-B*13:02-C*06:02-DRB1*07:01  Poland DKMS 0.891820,653
 94  A*30:01-B*13:02-C*06:02-DRB1*07:01  Germany DKMS - Romania minority 0.88901,234
 95  A*30:01-B*13:02-C*06:02-DRB1*07:01  Germany DKMS - France minority 0.88701,406
 96  A*02:01-B*13:02-C*06:02-DRB1*07:01  Germany DKMS - Romania minority 0.88201,234
 97  A*24-B*13-C*06  Macedonia 0.8741286
 98  A*24-B*13-C*06-DRB1*07  Macedonia 0.8741286
 99  A*30-B*13-C*06  Macedonia 0.8741286
 100  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:02  Mexico Mexico City Mestizo pop 2 0.8600234

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).


Displaying 1 to 100 (from 1,501) records   Pages: 1 2 3 4 5 6 7 8 9 10 of 16  


   

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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