Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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A B C DRB1 DPA1 DPB1 DQA1 DQB1

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Displaying 1 to 100 (from 282) records   Pages: 1 2 3 of 3  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*29-B*44-DRB1*13:01-DQB1*06:03  Spain Pas Valley 2.700088
 2  A*02:01:01-B*44:02:01-C*05:01:01-DRB1*13:01:01-DQB1*06:03:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Black 1.470668
 3  A*02:01:01-B*44:02:01-C*05:01:01-DRB1*13:01-DQB1*06:03  Costa Rica Central Valley Mestizo (G) 1.1312221
 4  A*24:02-B*44:03-C*07:06-DRB1*13:01-DQA1*01:03-DQB1*06:03  United Arab Emirates Abu Dhabi 0.960052
 5  A*02:01-B*44:02-C*05:01-E*01:03:01-F*01:01:01-G*01:01-DRB1*13:01-DQA1*01:03-DQB1*06:03  Portugal Azores Terceira Island 0.8772130
 6  A*02:01-B*44:02-C*05:01-DRB1*13:01:01-DQB1*06:03:01  England North West 0.8000298
 7  A*33:03:01-B*44:03:02-C*07:01:01-DRB1*13:01:01-DQB1*06:03:01  India Karnataka Kannada Speaking 0.7930174
 8  A*24:02:01-B*44:02:01-C*05:01:01-DRB1*13:01:01-DQB1*06:03:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.7782521
 9  A*34:02:01-B*44:03:01-C*04:01:01-DRB1*13:01:01-DQB1*06:03:01-DPB1*105:01:01  South African Black 0.7040142
 10  A*03:01-B*44:02-C*05:01-DRB1*13:01-DRB3*01:01-DQB1*06:03  USA NMDP Korean 0.607177,584
 11  A*34:02-B*44:03-C*04:01-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*04:02  South Africa Worcester 0.6000159
 12  A*01:01-B*44:02-DRB1*13:01-DQB1*06:03  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 13  A*11:04-B*44:02-DRB1*13:01-DQB1*06:03  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 14  A*02:01-B*44:02-C*05:01-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*02:01  USA San Diego 0.5210496
 15  A*03:02-B*44:02-DRB1*13:01-DQB1*06:03  Iran Tabriz Azeris 0.515597
 16  A*23:01:01-B*44:02:01-C*05:01:01-DRB1*13:01:01-DQB1*06:03:01  Spain, Canary Islands, Gran canaria island 0.4700215
 17  A*26:01:01-B*44:02:01-C*05:01:01-DRB1*13:01:01-DQB1*06:03:01  Spain, Canary Islands, Gran canaria island 0.4700215
 18  A*03-B*44-DRB1*13:01-DQA1*01:03-DQB1*06:03  Brazil Paraná Caucasian 0.4680641
 19  A*02:01-B*44:02-C*05:01-E*01:01:01-F*01:01:01-G*01:01-DRB1*13:01-DQA1*01:03-DQB1*06:03  Portugal Azores Terceira Island 0.4386130
 20  A*02:01-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03  Germany DKMS - Italy minority 0.43101,159
 21  A*24:02:01-B*44:03:01-C*04:01:01-DRB1*13:01:01-DQA1*05:05:01-DQB1*06:03-DPA1*01:03:01-DPB1*04:02  Russian Federation Vologda Region 0.4202119
 22  A*68:01:02-B*44:02:01-C*03:04:01-DRB1*13:01-DQA1*05:01:01-DQB1*06:03-DPA1*01:03:01-DPB1*04:02  Russian Federation Vologda Region 0.4202119
 23  A*23:01:01-B*44:03:01-C*04:01:01-DRB1*13:01:01-DQB1*06:03:01  Russia Bashkortostan, Bashkirs 0.4167120
 24  A*23:01-B*44:03-C*04:01-DRB1*13:01-DQA1*01:03-DQB1*06:03  Kosovo 0.4030124
 25  A*02:01:01-B*44:02:01-C*05:01:01-DRB1*13:01:01-DQB1*06:03:01  Poland BMR 0.401023,595
 26  A*02:01:01-B*44:02:01-C*05:01:01-DRB1*13:01:01-DQB1*06:03:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.3891521
 27  A*02:01-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03  USA Hispanic pop 2 0.37301,999
 28  A*02:01-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03  USA NMDP Alaska Native or Aleut 0.36831,376
 29  A*02:01-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03  USA NMDP American Indian South or Central America 0.35575,926
 30  A*34:02:01-B*44:03:01-C*04:01:01-DRB1*13:01:01-DQB1*06:03:01-DPB1*02:01:02  South African Black 0.3520142
 31  A*02-B*44-DRB1*13:01-DQA1*01:03-DQB1*06:03  Brazil Paraná Caucasian 0.3283641
 32  A*32:01:01-B*44:02:01-C*05:01:01-DRB1*13:01:01-DQA1*01:03:01-DQB1*06:03-DPA1*01:03:01-DPB1*04:01:01  Russia Belgorod region 0.3268153
 33  A*68:01:01-B*44:02:01-C*05:01:01-DRB1*13:01:01-DQA1*01:02:01-DQB1*06:03-DPA1*01:03:01-DPB1*04:01:01  Russia Belgorod region 0.3268153
 34  A*31:01:02-B*44:02:01-C*05:01:01-DRB1*13:01:01-DQB1*06:03:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 35  A*02:01-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.30804,335
 36  A*30:04-B*44:03-C*04:01-DRB1*13:01-DQA1*01:02-DQB1*06:03-DPB1*01:01  South Africa Worcester 0.3000159
 37  A*02:01-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03  Italy pop 5 0.2900975
 38  A*03:01-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03  Italy pop 5 0.2900975
 39  A*33:03-B*44:03-C*07:01-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*04:01  Sri Lanka Colombo 0.2801714
 40  A*02:01:01:01-B*44:02:01:01-C*05:01:01:02-DRB1*13:01:01-DQB1*06:03:01  Russia Nizhny Novgorod, Russians 0.27801,510
 41  A*02:01-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03-DPB1*02:01  Russia Karelia 0.27231,075
 42  A*11:01:01-B*44:03:02-C*07:06-DRB1*13:01:01-DQB1*06:03:01  India Andhra Pradesh Telugu Speaking 0.2688186
 43  A*02:01-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03  Colombia Bogotá Cord Blood 0.26141,463
 44  A*02:01:01-B*44:02:01-C*05:01:01-DRB1*13:01:01-DQB1*06:03:01  Spain, Canary Islands, Gran canaria island 0.2300215
 45  A*24:02:01-B*44:02:01-C*05:01:01-DRB1*13:01:01-DQB1*06:03:01  Spain, Canary Islands, Gran canaria island 0.2300215
 46  A*33:01:01-B*44:02:01-C*05:01:01-DRB1*13:01:01-DQB1*06:03:01  Spain, Canary Islands, Gran canaria island 0.2300215
 47  A*34:02:01-B*44:02:01-C*05:01:01-DRB1*13:01:01-DQB1*06:03:01  Spain, Canary Islands, Gran canaria island 0.2300215
 48  A*80:01:01-B*44:02:01-C*05:01:01-DRB1*13:01:01-DQB1*06:03:01  Spain, Canary Islands, Gran canaria island 0.2300215
 49  A*30:01-B*44:02-C*05:01-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPA1*02:02-DPB1*01:01  Mexico Chiapas Lacandon Mayans 0.2294218
 50  A*29:02:01-B*44:03:01-C*16:01:01-DRB1*13:01-DQB1*06:03  Costa Rica Central Valley Mestizo (G) 0.2262221
 51  A*02:01-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03  USA NMDP Caribean Indian 0.222314,339
 52  A*03:01-B*44:04-C*16:01-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*04:01  Nicaragua Managua 0.2165339
 53  A*11:01-B*44:03-C*12:03-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPB1*02:01  Nicaragua Managua 0.2165339
 54  A*11:01-B*44:03-C*04:01-DRB1*13:01:01-DQB1*06:03:01  England North West 0.2000298
 55  A*02:01:01-B*44:02:01-C*05:01:01-DRB1*13:01:01-DQB1*06:03:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 56  A*11:01:01-B*44:03:01-C*01:02:01-DRB1*13:01:01-DQB1*06:03:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 57  A*23:01:01-B*44:03:01-C*04:01:01-DRB1*13:01:01-DQB1*06:03:01-DPA1*01:03:01-DPB1*03:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 58  A*29:02:01-B*44:03:01-C*16:01:01-DRB1*13:01:01-DQB1*06:03:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 59  A*74:03-B*44:03:01-C*04:01:01-DRB1*13:01:01-DQB1*06:03:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 60  A*02:01-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03  USA NMDP Black South or Central American 0.19274,889
 61  A*02:01-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03-DPB1*04:01  Germany DKMS - German donors 0.18793,456,066
 62  A*29:02-B*44:03-C*16:01-DRB1*13:01-DQB1*06:03  USA NMDP Caribean Indian 0.180714,339
 63  A*03:01-B*44:02-C*05:01-DRB1*13:01-DRB3*01:01-DQB1*06:03  USA NMDP Japanese 0.178424,582
 64  A*33:03-B*44:03-C*07:06-DRB1*13:01-DQB1*06:03  India Northeast UCBB 0.1689296
 65  A*02:01-B*44:02-DRB1*13:01-DQB1*06:03  Mexico Mexico City Tlalpan 0.1515330
 66  A*03:01-B*44:02-DRB1*13:01-DQB1*06:03  Mexico Mexico City Tlalpan 0.1515330
 67  A*01:01-B*44:02-C*07:01-DRB1*13:01-DQB1*06:03  Italy pop 5 0.1400975
 68  A*02:17-B*44:02-C*01:02-DRB1*13:01-DQB1*06:03  Italy pop 5 0.1400975
 69  A*68:01-B*44:03-C*04:01-DRB1*13:01-DQB1*06:03  Italy pop 5 0.1400975
 70  A*29:02-B*44:03-C*16:01-DRB1*13:01-DQB1*06:03  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.13704,335
 71  A*33:03-B*44:03-C*07:01-DRB1*13:01-DQB1*06:03  India Tamil Nadu 0.13392,492
 72  A*03:01-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03  USA Asian pop 2 0.13301,772
 73  A*03:01:01-B*44:02:01-C*05:01:01-DRB1*13:01:01-DQB1*06:03:01  China Zhejiang Han 0.11531,734
 74  A*29:02-B*44:03-C*16:01-DRB1*13:01-DQB1*06:03  Colombia Bogotá Cord Blood 0.10341,463
 75  A*26:01-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.10304,335
 76  A*32:01-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03  Colombia Bogotá Cord Blood 0.10251,463
 77  A*33:03-B*44:03-C*07:06-DRB1*13:01-DQB1*06:03  India Central UCBB 0.09774,204
 78  A*02:01-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03-DPB1*02:01  Germany DKMS - German donors 0.09353,456,066
 79  A*33:03-B*44:03-C*07:06-DRB1*13:01-DQB1*06:03  India South UCBB 0.091311,446
 80  A*29-B*44-DRB1*13:01-DQA1*01:03-DQB1*06:03  Brazil Paraná Caucasian 0.0870641
 81  A*68-B*44-DRB1*13:01-DQA1*01:03-DQB1*06:03  Brazil Paraná Caucasian 0.0780641
 82  A*03:01-B*44:02-C*05:01-DRB1*13:01-DRB3*01:01-DQB1*06:03  USA NMDP Chinese 0.076399,672
 83  A*01:01:01-B*44:02:01-C*05:01:01-DRB1*13:01-DQB1*06:03  Costa Rica Central Valley Mestizo (G) 0.0748221
 84  A*03:01-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03  Germany DKMS - Turkey minority 0.07104,856
 85  A*03:01-B*44:02-C*05:01-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPA1*01:03-DPB1*02:01  Japan pop 17 0.07003,078
 86  A*03:01-B*44:02-C*05:01-DRB1*13:01-DQA1*01:03-DQB1*06:03-DPA1*02:02-DPB1*05:01  Japan pop 17 0.07003,078
 87  A*02:05-B*44:02-C*06:02-DRB1*13:01-DQB1*06:03  Colombia Bogotá Cord Blood 0.06841,463
 88  A*11:01-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03  Colombia Bogotá Cord Blood 0.06841,463
 89  A*31:01-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03  Colombia Bogotá Cord Blood 0.06841,463
 90  A*02:01-B*44:02-C*05:09-DRB1*13:01-DQB1*06:03  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 91  A*03:01-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 92  A*11:01-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 93  A*23:01-B*44:03-C*04:01-DRB1*13:01-DQB1*06:03  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 94  A*24:02-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 95  A*32:01-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 96  A*33:03-B*44:03-C*07:06-DRB1*13:01-DQB1*06:03  India North UCBB 0.06785,849
 97  A*02:01:01:01-B*44:02:01:01-C*05:01:01-DRB1*13:01:01-DQB1*06:03:01  Russia Nizhny Novgorod, Russians 0.06701,510
 98  A*11:01-B*44:03-C*07:06-DRB1*13:01-DQB1*06:03  India West UCBB 0.06665,829
 99  A*02:01-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03-DPB1*04:02  Germany DKMS - German donors 0.06323,456,066
 100  A*24:02-B*44:02-C*05:01-DRB1*13:01-DQB1*06:03-DPB1*04:01  Russia Karelia 0.05681,075

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 282) records   Pages: 1 2 3 of 3  


   

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.
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