Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Displaying 1 to 100 (from 165) records   Pages: 1 2 of 2  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*03:01:01:01-B*51:01:01-C*16:02:01-DRB1*04:04:01-DQB1*03:02  Russia Bashkortostan, Bashkirs 0.8333120
 2  A*24:02:01-B*51:01:01-C*15:02:01-DRB1*04:04:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 3  A*02:13-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  Colombia Bogotá Cord Blood 0.67411,463
 4  A*02:01-B*51:01-DRB1*04:04-DQB1*03:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 5  A*31:01-B*51:01-DRB1*04:04-DQB1*03:02  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 6  A*02:01-B*51:01-C*14:02-DRB1*04:04-DQB1*03:02  Mexico Mexico City Mestizo population 0.3497143
 7  A*68:05-B*51:01-C*15:09-DRB1*04:04-DQB1*03:02  Mexico Mexico City Mestizo population 0.3497143
 8  B*51:01-C*14:02-DRB1*04:04-DQB1*03:02  Mexico Mexico City Mestizo population 0.3497143
 9  B*51:01-C*15:09-DRB1*04:04-DQB1*03:02  Mexico Mexico City Mestizo population 0.3497143
 10  A*68:01:02-B*51:01:01-C*04:01:01-DRB1*04:04:01-DQB1*03:02:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Barra Mansa Rio State Caucasian 0.3125405
 11  A*24:02:01-B*51:01:01-C*16:02:01-DRB1*04:04:01-DQB1*03:02:01  India Andhra Pradesh Telugu Speaking 0.2688186
 12  A*31:01:02:01-B*51:01:01-C*03:04:01:01-DRB1*04:04:01-DQB1*03:02  Russia Bashkortostan, Tatars 0.2604192
 13  A*02:01-B*51:01-C*15:04-DRB1*04:04-DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218
 14  A*02:06-B*51:01-C*15:02-DRB1*04:04-DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218
 15  A*24:02-B*51:01-C*15:04-DRB1*04:04-DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*04:02  Mexico Chiapas Lacandon Mayans 0.2294218
 16  A*11:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02:01  England North West 0.2000298
 17  A*02:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  USA NMDP American Indian South or Central America 0.18775,926
 18  A*31:01-B*51:01-C*14:02-DRB1*04:04-DQB1*03:02  India Northeast UCBB 0.1689296
 19  A*11:01:01-B*51:01:01-C*15:02:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.167023,595
 20  A*02:02-B*51:01-DRB1*04:04-DQB1*03:02  Mexico Mexico City Tlalpan 0.1515330
 21  A*24:02-B*51:01-DRB1*04:04-DQB1*03:02  Mexico Mexico City Tlalpan 0.1515330
 22  A*31:01-B*51:01-DRB1*04:04-DQB1*03:02  Mexico Mexico City Tlalpan 0.1515330
 23  A*68:01-B*51:01-DRB1*04:04-DQB1*03:02  Mexico Mexico City Tlalpan 0.1515330
 24  A*24:02-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  Colombia Bogotá Cord Blood 0.13611,463
 25  A*11:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  Germany DKMS - Italy minority 0.12901,159
 26  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.115823,595
 27  A*02:01:01:01-B*51:01:01-C*15:02:01:01-DRB1*04:04:01-DQB1*03:02  Russia Nizhny Novgorod, Russians 0.09931,510
 28  A*02:01-B*51:01-C*15:09-DRB1*04:04-DQB1*03:02  USA Hispanic pop 2 0.09401,999
 29  A*02:13-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  USA Hispanic pop 2 0.09401,999
 30  A*24:02-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  USA Hispanic pop 2 0.08801,999
 31  A*24:02-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  India North UCBB 0.07615,849
 32  A*26:01-B*51:01-C*01:02-DRB1*04:04-DQA1*03:01-DQB1*03:02-DPB1*26:01  Sri Lanka Colombo 0.0700714
 33  A*11:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 34  A*02:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  Colombia Bogotá Cord Blood 0.06651,463
 35  A*11:01:01:01-B*51:01:01-C*15:02:01:01-DRB1*04:04:01-DQB1*03:02  Russia Nizhny Novgorod, Russians 0.06621,510
 36  A*24:02:01:01-B*51:01:01-C*15:02:01:01-DRB1*04:04:01-DQB1*03:02  Russia Nizhny Novgorod, Russians 0.06621,510
 37  A*11:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  Germany DKMS - Turkey minority 0.06304,856
 38  A*24:02-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02-DPB1*04:01  Russia Karelia 0.05651,075
 39  A*24:02-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  India South UCBB 0.055211,446
 40  A*11:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  India South UCBB 0.052111,446
 41  A*11:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02-DPB1*03:01  Germany DKMS - German donors 0.04973,456,066
 42  A*02:01-B*51:01-C*16:01-DRB1*04:04-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 43  A*31:01-B*51:01-C*03:03-DRB1*04:04-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 44  A*68:01-B*51:01-C*16:02-DRB1*04:04-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 45  A*02:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02-DPB1*04:01  Germany DKMS - German donors 0.04653,456,066
 46  A*03:01-B*51:01-C*15:04-DRB1*04:04-DQB1*03:02  Germany DKMS - Italy minority 0.04301,159
 47  A*11:08-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  Germany DKMS - Italy minority 0.04301,159
 48  A*24:02-B*51:01-C*07:02-DRB1*04:04-DQB1*03:02  Germany DKMS - Italy minority 0.04301,159
 49  A*31:01-B*51:01-C*04:01-DRB1*04:04-DQB1*03:02  Germany DKMS - Italy minority 0.04301,159
 50  A*31:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  India North UCBB 0.04275,849
 51  A*32:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  India North UCBB 0.04185,849
 52  A*68:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  Germany DKMS - Turkey minority 0.04104,856
 53  A*11:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02-DPB1*04:01  Germany DKMS - German donors 0.03783,456,066
 54  A*03:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  Colombia Bogotá Cord Blood 0.03671,463
 55  A*24:14-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  Colombia Bogotá Cord Blood 0.03421,463
 56  A*68:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  Colombia Bogotá Cord Blood 0.03421,463
 57  A*03:01-B*51:01-C*07:02-DRB1*04:04-DQB1*03:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 58  A*11:01-B*51:01-C*04:01-DRB1*04:04-DQB1*03:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 59  A*68:01-B*51:01-C*14:02-DRB1*04:04-DQB1*03:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 60  A*02:01:01:01-B*51:01:01-C*02:02:02-DRB1*04:04:01-DQB1*03:02  Russia Nizhny Novgorod, Russians 0.03311,510
 61  A*25:01:01-B*51:01:01-C*15:02:01:01-DRB1*04:04:01-DQB1*03:02  Russia Nizhny Novgorod, Russians 0.03311,510
 62  A*02:06-B*51:01-C*14:02-DRB1*04:04-DQB1*03:02  Germany DKMS - Turkey minority 0.03104,856
 63  A*31:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  Germany DKMS - Turkey minority 0.03104,856
 64  A*02:01-B*51:01-C*14:02-DRB1*04:04-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*03:01  Japan pop 17 0.03003,078
 65  A*24:02-B*51:01-C*14:02-DRB1*04:04-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*03:01  Japan pop 17 0.03003,078
 66  A*24:02-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  Germany DKMS - Turkey minority 0.03004,856
 67  A*01:01-B*51:01-C*14:02-DRB1*04:04-DQB1*03:02  Germany DKMS - Turkey minority 0.02904,856
 68  A*02:01:01-B*51:01:01-C*14:02:01-DRB1*04:04:01-DQB1*03:02:01  China Zhejiang Han 0.02881,734
 69  A*24:02:01-B*51:01:01-C*14:02:01-DRB1*04:04:01-DQB1*03:02:01  China Zhejiang Han 0.02881,734
 70  A*32:01:01-B*51:01:01-C*15:02:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.026523,595
 71  A*26:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  India North UCBB 0.02645,849
 72  A*02:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  India Tamil Nadu 0.02562,492
 73  A*68:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02-DPB1*04:01  Germany DKMS - German donors 0.02493,456,066
 74  A*01:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  India Central UCBB 0.02384,204
 75  A*32:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  India Central UCBB 0.02384,204
 76  A*68:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  India Central UCBB 0.02384,204
 77  A*11:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  India Tamil Nadu 0.02302,492
 78  A*26:01-B*51:01-C*16:02-DRB1*04:04-DQB1*03:02  India Tamil Nadu 0.02262,492
 79  A*11:01-B*51:01-C*14:02-DRB1*04:04-DQB1*03:02  USA Asian pop 2 0.02201,772
 80  A*02:11-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  India Tamil Nadu 0.02192,492
 81  A*26:01-B*51:01-C*14:02-DRB1*04:04-DQB1*03:02  Germany DKMS - Turkey minority 0.02104,856
 82  A*32:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  Germany DKMS - Turkey minority 0.02104,856
 83  A*23:01-B*51:01-C*14:02-DRB1*04:04-DQB1*03:02  India East UCBB 0.02082,403
 84  A*24:02-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  India East UCBB 0.02082,403
 85  A*30:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  India East UCBB 0.02082,403
 86  A*03:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  India Tamil Nadu 0.02012,492
 87  A*11:01-B*51:01-C*04:01-DRB1*04:04-DQB1*03:02  India Tamil Nadu 0.02012,492
 88  A*01:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  India North UCBB 0.01735,849
 89  A*11:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  India West UCBB 0.01725,829
 90  A*24:02:01-B*51:01:01-C*15:02:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.015123,595
 91  A*26:01-B*51:01-C*16:02-DRB1*04:04-DQB1*03:02  India North UCBB 0.01465,849
 92  A*02:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02-DPB1*03:01  Germany DKMS - German donors 0.01453,456,066
 93  A*02:01-B*51:01-C*07:02-DRB1*04:04-DQB1*03:02  India South UCBB 0.013111,446
 94  A*68:01:02-B*51:01:01-C*15:02:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.012723,595
 95  A*24:02-B*51:01-C*16:02-DRB1*04:04-DQB1*03:02  India South UCBB 0.012211,446
 96  A*01:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02  Germany DKMS - Turkey minority 0.01204,856
 97  A*02:01-B*51:01-C*07:02-DRB1*04:04-DQB1*03:02  India Central UCBB 0.01194,204
 98  A*03:01-B*51:01-C*07:02-DRB1*04:04-DQB1*03:02  India Central UCBB 0.01194,204
 99  A*01:01:01-B*51:01:01-C*15:02:01-DRB1*04:04:01-DQB1*03:02:01  Poland BMR 0.011223,595
 100  A*32:01-B*51:01-C*15:02-DRB1*04:04-DQB1*03:02-DPB1*04:01  Germany DKMS - German donors 0.01113,456,066

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 165) 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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