Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Displaying 1 to 100 (from 114) records   Pages: 1 2 of 2  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*30:01-B*13:02-C*06:02-DRB1*07:01  Germany DKMS - China minority 4.51801,282
 2  A*30:01-B*13:02-C*06:02-DRB1*07:01  Taiwan pop 2 3.9000364
 3  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
 4  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01/02:02  South Korea pop 3 2.7000485
 5  A*30:01-B*13:02-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Korean 2.258577,584
 6  A*30:01-B*13:02-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Chinese 2.025499,672
 7  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:02  Italy pop 5 1.6000975
 8  A*30:01-B*13:02-C*06:02-DRB1*07:01  Hong Kong Chinese BMDR 1.28347,595
 9  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01  Germany DKMS - Italy minority 1.25101,159
 10  A*30:01-B*13:02-C*06:02-DRB1*07:01  Italy pop 5 1.1800975
 11  A*30:01-B*13:02-C*06:02-DRB1*07:01  USA Italy Ancestry 1.0990273
 12  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
 13  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
 14  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
 15  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
 16  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
 17  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
 18  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01  Germany DKMS - Turkey minority 0.98204,856
 19  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01  USA Asian pop 2 0.97801,772
 20  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
 21  A*30:01-B*13:02-C*06:02-DRB1*07:01  Poland DKMS 0.898720,653
 22  A*30:01-B*13:02-C*06:02-DRB1*07:01  Germany DKMS - Romania minority 0.88901,234
 23  A*30:01-B*13:02-C*06:02-DRB1*07:01  Germany DKMS - France minority 0.88701,406
 24  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:02  Mexico Mexico City Mestizo pop 2 0.8600234
 25  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  Poland BMR 0.859823,595
 26  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:02  India West UCBB 0.85835,829
 27  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:02  India South UCBB 0.828011,446
 28  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DPB1*17:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.77855,266
 29  A*30:01-B*13:02-C*06:02-DRB1*07:01  Germany DKMS - Austria minority 0.70301,698
 30  A*30:01-B*13:02-C*06:02-DRB1*07:01  Germany DKMS - Bosnia and Herzegovina minority 0.67901,028
 31  A*30:01-B*13:02-C*06:02-DRB1*07:01  Germany DKMS - Spain minority 0.67801,107
 32  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02  Brazil Puyanawa 0.6667150
 33  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01  India Tamil Nadu 0.66192,492
 34  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01  Nicaragua Mestizo (G) 0.6452155
 35  A*30:01-B*13:02-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP European Caucasian 0.63911,242,890
 36  A*30:01-B*13:02-C*06:02-DRB1*07:01  Germany DKMS - Portugal minority 0.63501,176
 37  A*30:01-B*13:02-C*06:02-DRB1*07:01  Germany DKMS - Greece minority 0.62301,894
 38  A*30:01-B*13:02-C*06:02-DRB1*07:01  Germany DKMS - Croatia minority 0.61902,057
 39  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.61604,335
 40  A*30:01-B*13:02-C*06:02-DRB1*07:01  Germany DKMS - Netherlands minority 0.58201,374
 41  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:02  India East UCBB 0.52012,403
 42  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:02  India North UCBB 0.50595,849
 43  A*30:01-B*13:02-C*06:02-DRB1*07:01  Germany DKMS - United Kingdom minority 0.47901,043
 44  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.47851,463
 45  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01  USA Hispanic pop 2 0.46801,999
 46  A*30:01-B*13:02-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Hispanic South or Central American 0.4457146,714
 47  A*30:01-B*13:02-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Mexican or Chicano 0.4443261,235
 48  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*17:01  Nicaragua Managua 0.4329339
 49  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01  USA NMDP American Indian South or Central America 0.43065,926
 50  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DQB1*02:01:01  India Kerala Malayalam speaking 0.4210356
 51  A*30:01:01-B*13:02:01-C*06:02:01:01-DRB1*07:01-DQB1*02:02  Russia Bashkortostan, Bashkirs 0.4167120
 52  A*30:01-B*13:02-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP North American Amerindian 0.411435,791
 53  A*30:01-B*13:02-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Vietnamese 0.403543,540
 54  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:02  India Central UCBB 0.36734,204
 55  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01  USA NMDP Alaska Native or Aleut 0.36171,376
 56  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:02  Mexico Mexico City Mestizo population 0.3497143
 57  A*30:01-B*13:02-C*06:02-DRB1*07:01  Brazil Vale do Ribeira Quilombos 0.3472144
 58  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:01-DPA1*02:01-DPB1*17:01  United Arab Emirates Pop 1 0.3271570
 59  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DQA1*02:01-DQB1*02:02-DPA1*01:03:01-DPB1*04:01:01  Russia Belgorod region 0.3268153
 60  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01-DPA1*02:01:01-DPB1*14:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 61  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DQB1*05:03:01-DPA1*01:03:01-DPB1*271:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 62  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02-DPB1*17:01  South Africa Worcester 0.3000159
 63  A*30:01:01-B*13:02:01-C*06:02:01:01-DRB1*07:01:01:01-DQB1*02:02  Russia Bashkortostan, Tatars 0.2824192
 64  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DQB1*02:02:01  India Kerala Malayalam speaking 0.2810356
 65  A*30:01-B*13:02-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Filipino 0.236150,614
 66  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02-DPA1*02:01-DPB1*17:01  Mexico Chiapas Lacandon Mayans 0.2294218
 67  A*30:01-B*13:02-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Caribean Hispanic 0.2287115,374
 68  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01-DPB1*17:01  Germany DKMS - German donors 0.21613,456,066
 69  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:02  Malaysia Peninsular Malay 0.2103951
 70  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01-DPB1*04:02  Russia Karelia 0.19311,075
 71  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01-DPB1*04:01  Russia Karelia 0.19011,075
 72  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*03:02  Malaysia Peninsular Indian 0.1845271
 73  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01-DPB1*04:01  Germany DKMS - German donors 0.15943,456,066
 74  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01  USA NMDP Black South or Central American 0.15494,889
 75  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DQB1*02:01:01-DPB1*17:01:01  Saudi Arabia pop 6 (G) 0.152128,927
 76  A*30:01-B*13:02-C*06:02-DRB1*07:01  Japan pop 16 0.151018,604
 77  A*30:01-B*13:02-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Japanese 0.142324,582
 78  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:01-DPA1*01:03-DPB1*02:01  United Arab Emirates Pop 1 0.1402570
 79  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DPB1*05:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.12695,266
 80  A*30:01-B*13:02-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP African American pop 2 0.1174416,581
 81  A*30:01-B*13:02-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP Caribean Black 0.114233,328
 82  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DQB1*02:01:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.111928,927
 83  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01-DPB1*04:02  Germany DKMS - German donors 0.10243,456,066
 84  A*30:01-B*13:02-C*06:02-DRB1*07:01-DRB4*01:01-DQB1*02:01  USA NMDP African 0.088328,557
 85  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01-DPB1*02:01  Germany DKMS - German donors 0.08583,456,066
 86  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DPB1*02:01:02  Hong Kong Chinese HKBMDR HLA 11 loci 0.08085,266
 87  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02-DPA1*02:01-DPB1*17:01  Japan pop 17 0.07003,078
 88  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DPB1*13:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.05455,266
 89  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*03:03  India West UCBB 0.05155,829
 90  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DPB1*19:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.04745,266
 91  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DPB1*09:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.04725,266
 92  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:01-DPA1*02:01-DPB1*01:01  United Arab Emirates Pop 1 0.0467570
 93  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01-DPB1*03:01  Germany DKMS - German donors 0.04613,456,066
 94  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DPB1*02:02:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.04595,266
 95  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*03:03  India South UCBB 0.036511,446
 96  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01-DPB1*14:01  Germany DKMS - German donors 0.03633,456,066
 97  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQA1*02:01-DQB1*02:02-DPA1*02:02-DPB1*02:02  Japan pop 17 0.03003,078
 98  A*30:01:01-B*13:02:01-C*06:02:01-DRB1*07:01:01-DQB1*03:03:02  China Zhejiang Han 0.02881,734
 99  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*02:01-DPB1*01:01  Germany DKMS - German donors 0.02483,456,066
 100  A*30:01-B*13:02-C*06:02-DRB1*07:01-DQB1*03:02  India Tamil Nadu 0.02412,492

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).


Displaying 1 to 100 (from 114) records   Pages: 1 2 of 2  


   

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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