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 112) records   Pages: 1 2 of 2  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*68-B*15-DRB1*04:04-DQB1*03:02  Mexico San Vicente Tancuayalab Teenek/Huastecos 1.890053
 2  A*02-B*15-DRB1*04:04-DQB1*03:02  Bolivia La Paz Aymaras 1.592087
 3  A*02-B*15-DRB1*04:04-DQB1*03:02  Guatemala Mayan 1.5000132
 4  A*24-B*15-DRB1*04:04-DQB1*03:02  Bolivia Quechua 1.150069
 5  A*02-B*15-DRB1*04:04-DQB1*03:02  Bolivia Quechua 0.820069
 6  A*68:01-B*15:01-DRB1*04:04-DQB1*03:02  Chile Mapuche 0.770066
 7  A*68:01-B*15:01-C*01:02-DRB1*04:04-DQA1*03:01-DQB1*03:02  Mexico Tixcacaltuyub Maya 0.746367
 8  A*69-B*15-DRB1*04:04-DQB1*03:02  Bolivia Quechua 0.720069
 9  A*02:01:01-B*15:01:01-C*04:01:01-DRB1*04:04:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 10  A*24:02:01-B*15:08:01-C*01:02:01-DRB1*04:04:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 11  A*02:01-B*15:01-DRB1*04:04-DQB1*03:02  Mexico Veracruz Xalapa 0.595284
 12  A*24:02-B*15:01-DRB1*04:04-DQB1*03:02  Mexico Veracruz Xalapa 0.595284
 13  A*33:01-B*15:01-DRB1*04:04-DQB1*03:02  Mexico Veracruz Xalapa 0.595284
 14  A*24:02-B*15:01-DRB1*04:04-DQB1*03:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 15  A*11:01:01-B*15:01:01-C*01:02:01-DRB1*04:04:01-DQB1*03:02:01  Spain, Canary Islands, Gran canaria island 0.4700215
 16  A*02:01-B*15:15-C*01:02-DRB1*04:04-DQA1*03:01-DQB1*03:02-DPB1*04:02  Nicaragua Managua 0.4329339
 17  B*15:01-C*01:02-DRB1*04:04-DQB1*03:02  Mexico Mexico City Mestizo pop 2 0.4300234
 18  A*02:01-B*15:01-C*01:02-DRB1*04:04-DQB1*03:02  Mexico Mexico City Mestizo pop 2 0.4274234
 19  A*02-B*15-DRB1*04:04-DQA1*03:01-DQB1*03:02  Brazil Paraná Caucasian 0.3120641
 20  A*02:01-B*15:02-DRB1*04:04-DQB1*03:02  Mexico Mexico City Tlalpan 0.3030330
 21  A*02:01-B*15:01-C*03:03-DRB1*04:04-DQB1*03:02:01  England North West 0.3000298
 22  A*23:01-B*15:10-C*06:02-DRB1*04:04-DQA1*03:01-DQB1*03:02-DPB1*01:01  South Africa Worcester 0.3000159
 23  A*24:02-B*15:01-C*03:03-DRB1*04:04-DQB1*03:02  USA NMDP Alaska Native or Aleut 0.28481,376
 24  A*01:01-B*15:01-C*01:02-DRB1*04:04-DQB1*03:02:01  England North West 0.2000298
 25  A*01:01-B*15:01-C*03:03-DRB1*04:04-DQB1*03:02:01  England North West 0.2000298
 26  A*24:02-B*15:07-C*03:03-DRB1*04:04-DQB1*03:02:01  England North West 0.2000298
 27  A*68:01:01-B*15:01:01-C*03:03:01-DRB1*04:04:01-DQB1*03:02:01-DPA1*01:03:01-DPB1*03:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 28  A*02:01-B*15:01-DRB1*04:04-DQB1*03:02  Mexico Mexico City Tlalpan 0.1515330
 29  A*02:01-B*15:05-DRB1*04:04-DQB1*03:02  Mexico Mexico City Tlalpan 0.1515330
 30  A*69:01-B*15:01-DRB1*04:04-DQB1*03:02  Mexico Mexico City Tlalpan 0.1515330
 31  A*02:01-B*15:01-C*04:01-DRB1*04:04-DQB1*03:02-DPB1*04:01  Russia Karelia 0.11251,075
 32  A*68-B*15-DRB1*04:04-DQA1*03:01-DQB1*03:02  Brazil Paraná Caucasian 0.0780641
 33  A*02:01:01:01-B*15:07:01-C*03:03:01-DRB1*04:04:01-DQB1*03:02  Russia Nizhny Novgorod, Russians 0.06621,510
 34  A*24:02:01:01-B*15:01:01:01-C*03:03:01-DRB1*04:04:01-DQB1*03:02  Russia Nizhny Novgorod, Russians 0.06621,510
 35  A*02:01:01-B*15:18:01-C*08:01:01-DRB1*04:04:01-DQB1*03:02:01  China Zhejiang Han 0.05771,734
 36  A*01:01-B*15:01-C*04:01-DRB1*04:04-DQB1*03:02-DPB1*02:01  Russia Karelia 0.05641,075
 37  A*11:01:01-B*15:18:01-C*08:01:01-DRB1*04:04:01-DQB1*03:02:01  China Zhejiang Han 0.05451,734
 38  A*02:02-B*15:02-C*01:02-DRB1*04:04-DQB1*03:02  Malaysia Peninsular Malay 0.0526951
 39  A*01:01-B*15:01-C*03:03-DRB1*04:04-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 40  A*24:02-B*15:39-C*01:02-DRB1*04:04-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 41  A*24:02-B*15:39-C*03:03-DRB1*04:04-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 42  A*31:01-B*15:01-C*01:02-DRB1*04:04-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 43  A*02:01:01:01-B*15:01:01-C*04:01:01-DRB1*04:04:01-DQB1*03:02  Russia Nizhny Novgorod, Russians 0.04661,510
 44  A*02:01-B*15:34-C*04:01-DRB1*04:04-DQB1*03:02  USA Asian pop 2 0.04401,772
 45  A*23:01-B*15:03-C*02:02-DRB1*04:04-DQB1*03:02  USA African American pop 4 0.04402,411
 46  A*02:17-B*15:01-C*01:02-DRB1*04:04-DQB1*03:02  Germany DKMS - Italy minority 0.04301,159
 47  A*24:02-B*15:01-C*03:03-DRB1*04:04-DQB1*03:02-DPB1*06:01  Germany DKMS - German donors 0.03593,456,066
 48  A*02:01-B*15:01-C*03:03-DRB1*04:04-DQB1*03:02  Colombia Bogotá Cord Blood 0.03421,463
 49  A*11:01-B*15:01-C*08:01-DRB1*04:04-DQB1*03:02  Colombia Bogotá Cord Blood 0.03421,463
 50  A*68:01-B*15:17-C*14:02-DRB1*04:04-DQB1*03:02  Colombia Bogotá Cord Blood 0.03421,463
 51  A*68:02-B*15:20-C*04:01-DRB1*04:04-DQB1*03:02  Colombia Bogotá Cord Blood 0.03421,463
 52  A*11:01-B*15:01-C*01:02-DRB1*04:04-DQB1*03:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 53  A*68:01-B*15:20-C*03:04-DRB1*04:04-DQB1*03:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 54  A*69:01-B*15:01-C*01:02-DRB1*04:04-DQB1*03:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 55  A*02:01-B*15:01-C*04:01-DRB1*04:04-DQB1*03:02-DPB1*04:01  Germany DKMS - German donors 0.03123,456,066
 56  A*02:01:01-B*15:01:01-C*07:02:01-DRB1*04:04:01-DQB1*03:02:01  China Zhejiang Han 0.02881,734
 57  A*11:01:01-B*15:01:01-C*04:01:01-DRB1*04:04:01-DQB1*03:02:01  China Zhejiang Han 0.02881,734
 58  A*31:01:02-B*15:02:01-C*08:01:01-DRB1*04:04:01-DQB1*03:02:01  China Zhejiang Han 0.02881,734
 59  A*31:01:02-B*15:18:01-C*08:01:01-DRB1*04:04:01-DQB1*03:02:01  China Zhejiang Han 0.02881,734
 60  A*24:02:01-B*15:01:01-C*03:03:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.022023,595
 61  A*02:01:01-B*15:01:01-C*03:03:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.020323,595
 62  A*24:07-B*15:18-C*02:02-DRB1*04:04-DQB1*03:02  India Tamil Nadu 0.02012,492
 63  A*24:02:01:01-B*15:01:01-C*04:01:01-DRB1*04:04:01-DQB1*03:02  Russia Nizhny Novgorod, Russians 0.01951,510
 64  A*02:01:01-B*15:01:01-C*03:04:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.018923,595
 65  A*24:02-B*15:07-C*03:03-DRB1*04:04-DQB1*03:02-DPB1*06:01  Germany DKMS - German donors 0.01803,456,066
 66  A*24:02:01-B*15:07:01-C*03:03:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.012723,595
 67  A*02:01-B*15:01-C*03:04-DRB1*04:04-DQB1*03:02-DPB1*04:01  Germany DKMS - German donors 0.01203,456,066
 68  A*01:02-B*15:10-C*03:04-DRB1*04:04-DQB1*03:02  USA Hispanic pop 2 0.01201,999
 69  A*02:01-B*15:17-C*05:01-DRB1*04:04-DQB1*03:02  USA Hispanic pop 2 0.01201,999
 70  A*03:01-B*15:03-C*02:02-DRB1*04:04-DQB1*03:02  USA Hispanic pop 2 0.01201,999
 71  A*31:01-B*15:17-C*05:01-DRB1*04:04-DQB1*03:02  USA Hispanic pop 2 0.01201,999
 72  A*66:02-B*15:03-C*02:02-DRB1*04:04-DQB1*03:02  USA Hispanic pop 2 0.01201,999
 73  A*68:02-B*15:10-C*03:04-DRB1*04:04-DQB1*03:02  USA Hispanic pop 2 0.01201,999
 74  A*11:01-B*15:02-C*08:01-DRB1*04:04-DQB1*03:02  India UCBB_Central Indian HLA 0.01194,204
 75  A*24:02-B*15:18-C*07:04-DRB1*04:04-DQB1*03:02  India UCBB_Central Indian HLA 0.01194,204
 76  A*24:11N-B*15:01-C*12:03-DRB1*04:04-DQB1*03:02  India UCBB_Central Indian HLA 0.01194,204
 77  A*68:01-B*15:18-C*07:02-DRB1*04:04-DQB1*03:02  India UCBB_Central Indian HLA 0.01194,204
 78  A*02:06-B*15:11-C*03:03-DRB1*04:04-DQB1*03:02  USA Asian pop 2 0.01101,772
 79  A*11:01-B*15:11-C*03:03-DRB1*04:04-DQB1*03:02  USA Asian pop 2 0.01101,772
 80  A*24:02-B*15:01-C*03:03-DRB1*04:04-DQB1*03:02  USA African American pop 4 0.01102,411
 81  A*24:02-B*15:03-C*02:02-DRB1*04:04-DQB1*03:02  USA African American pop 4 0.01102,411
 82  A*29:01-B*15:01-C*03:03-DRB1*04:04-DQB1*03:02  USA African American pop 4 0.01102,411
 83  A*29:01-B*15:03-C*02:02-DRB1*04:04-DQB1*03:02  USA African American pop 4 0.01102,411
 84  A*03:01-B*15:01-C*07:04-DRB1*04:04-DQB1*03:02  Germany DKMS - Turkey minority 0.01004,856
 85  A*29:02-B*15:01-C*03:03-DRB1*04:04-DQB1*03:02  Germany DKMS - Turkey minority 0.01004,856
 86  A*33:03-B*15:17-C*07:01-DRB1*04:04-DQB1*03:02  Germany DKMS - Turkey minority 0.01004,856
 87  A*01:01:01-B*15:01:01-C*03:03:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.008123,595
 88  A*03:01:01-B*15:01:01-C*03:03:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.006523,595
 89  A*24:02:01-B*15:01:01-C*03:04:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.004223,595
 90  A*02:01:01-B*15:01:01-C*04:01:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.004023,595
 91  A*03:01:01-B*15:01:01-C*04:01:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.003723,595
 92  A*01:01:01-B*15:01:01-C*03:04:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.003623,595
 93  A*26:01:01-B*15:01:01-C*04:01:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.002223,595
 94  A*02:01:01-B*15:01:01-C*02:02:02-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.002123,595
 95  A*01:01:01-B*15:17:01-C*07:01:02-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.002123,595
 96  A*24:02:01-B*15:39:01-C*04:01:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.002123,595
 97  A*31:08-B*15:07:01-C*03:03:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.002123,595
 98  A*32:01:01-B*15:135-C*03:03:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.002123,595
 99  A*33:03:01-B*15:01:01-C*01:02:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.002123,595
 100  A*31:01:02-B*15:01:01-C*03:03:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.001923,595

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).


Displaying 1 to 100 (from 112) 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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