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 237) records   Pages: 1 2 3 of 3  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*24-B*51-DRB1*04:03-DQB1*03:02  Colombia Wayu from Guajira Peninsula 9.220048
 2  A*68:01-B*51:01-DRB1*04:03-DQB1*03:02  Chile Mapuche 3.850066
 3  A*02-B*51-DRB1*04:03-DQB1*03:02  Colombia Wayu from Guajira Peninsula 2.080048
 4  A*26:01:01-B*51:01:01-C*16:02:01-DRB1*04:03:01-DQB1*03:02:01  India Andhra Pradesh Telugu Speaking 1.0753186
 5  A*24-B*51-DRB1*04:03-DQB1*03:02  Mexico Sinaloa Capomos Mayo Yoremes 0.833360
 6  A*24:02-B*51:01-C*01:02-DRB1*04:03-DQA1*03:01-DQB1*03:02  Kosovo 0.8060124
 7  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*04:03:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 8  A*68:03:01-B*51:01:01-C*15:02:01-DRB1*04:03:01-DQB1*03:02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 9  A*24:02-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  Malaysia Peninsular Indian 0.5535271
 10  A*11:01:01-B*51:01:01-C*15:02:01-DRB1*04:03:01-DQB1*03:02:01  India Andhra Pradesh Telugu Speaking 0.5376186
 11  A*03:01-B*51:01-C*01:02-DRB1*04:03-DQA1*03:01-DQB1*03:02  Kosovo 0.4030124
 12  A*26:01:01-B*51:01:01-C*15:04:01-DRB1*04:03:01-DQB1*03:02:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.313028,927
 13  A*24:07:01-B*51:01:01-C*07:02:01-DRB1*04:03:01-DQB1*03:02:01  India Karnataka Kannada Speaking 0.2870174
 14  A*03:01:01-B*51:01:01-C*14:02:01-DRB1*04:03:01-DQB1*03:02:01  India Kerala Malayalam speaking 0.2810356
 15  A*68:01:02-B*51:01:01-C*14:02:01-DRB1*04:03:01-DQB1*03:02:01  India Kerala Malayalam speaking 0.2810356
 16  A*02:11:01-B*51:01:01-C*07:02:01-DRB1*04:03:01-DQB1*03:02:01  India Andhra Pradesh Telugu Speaking 0.2688186
 17  A*24:02:01-B*51:01:01-C*15:02:01-DRB1*04:03:01-DQB1*03:02:01  India Andhra Pradesh Telugu Speaking 0.2688186
 18  A*24:33-B*51:06:01-C*12:04:02-DRB1*04:03:01-DQB1*03:02:01  India Andhra Pradesh Telugu Speaking 0.2688186
 19  A*01:01-B*51:01-C*14:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPB1*04:01  USA San Diego 0.2600496
 20  A*68:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  India Tamil Nadu 0.22702,492
 21  A*02:01:01-B*51:01:01-C*14:02:01-DRB1*04:03:01-DQB1*03:02:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.215328,927
 22  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*04:03:01-DQB1*03:02:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.194528,927
 23  A*01:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  Malaysia Peninsular Indian 0.1845271
 24  A*11:01-B*51:01-C*06:02-DRB1*04:03-DQB1*03:02  Malaysia Peninsular Indian 0.1845271
 25  A*24:07-B*51:01-C*12:02-DRB1*04:03-DQB1*03:02  Malaysia Peninsular Indian 0.1845271
 26  A*26:12-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  Malaysia Peninsular Indian 0.1845271
 27  A*33:03-B*51:01-C*07:02-DRB1*04:03-DQB1*03:02  Malaysia Peninsular Indian 0.1845271
 28  A*68:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  Malaysia Peninsular Indian 0.1845271
 29  A*26:01-B*51:01-C*16:02-DRB1*04:03-DQB1*03:02  India South UCBB 0.174811,446
 30  A*26:01-B*51:01-C*16:02-DRB1*04:03-DQB1*03:02  India Tamil Nadu 0.15412,492
 31  A*03:01-B*51:01-C*16:02-DRB1*04:03-DQB1*03:02  India Tamil Nadu 0.15352,492
 32  A*24:02-B*51:01-DRB1*04:03-DQB1*03:02  Mexico Mexico City Tlalpan 0.1515330
 33  A*11:01-B*51:01-C*16:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPB1*02:01  Sri Lanka Colombo 0.1401714
 34  A*02:11:01-B*51:01:01-C*14:02:01-DRB1*04:03:01-DQB1*03:02:01  India Kerala Malayalam speaking 0.1400356
 35  A*03:02:01-B*51:06:01-C*14:02:01-DRB1*04:03:01-DQB1*03:02:01  India Kerala Malayalam speaking 0.1400356
 36  A*11:01:01-B*51:01:01-C*14:02:01-DRB1*04:03:01-DQB1*03:02:01  India Kerala Malayalam speaking 0.1400356
 37  A*68:01:01-B*51:01:01-C*15:04:01-DRB1*04:03:01-DQB1*03:02:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.137828,927
 38  A*03:01:01-B*51:02-C*07:02:01-DRB1*04:03:01-DQB1*03:02:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.127428,927
 39  A*03:01:01-B*51:01:01-C*16:02:01-DRB1*04:03:01-DQB1*03:02:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.127128,927
 40  A*11:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  India Tamil Nadu 0.10902,492
 41  A*68:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  India South UCBB 0.104211,446
 42  A*68:01:01-B*51:01:01-C*15:02:01-DRB1*04:03:01-DQB1*03:02:01-DPB1*02:01:02  Saudi Arabia pop 6 (G) 0.092028,927
 43  A*02:01-B*51:01-C*16:02-DRB1*04:03-DQB1*03:02  Germany DKMS - Turkey minority 0.09004,856
 44  A*02:01-B*51:01-C*15:02-DRB1*04:03-DQB1*03:02  USA Asian pop 2 0.08901,772
 45  A*31:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  USA Asian pop 2 0.08901,772
 46  A*11:01-B*51:01-C*07:02-DRB1*04:03-DQB1*03:02  India East UCBB 0.08322,403
 47  A*02-B*51-DRB1*04:03-DQA1*03:01-DQB1*03:02  Brazil Paraná Caucasian 0.0780641
 48  A*02-B*51-DRB1*04:03-DQA1*03:02-DQB1*03:02  Brazil Paraná Caucasian 0.0780641
 49  A*02:11-B*51:01-C*07:02-DRB1*04:03-DQB1*03:02  India Tamil Nadu 0.07392,492
 50  A*02:16-B*51:01-C*14:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPB1*81:01  Sri Lanka Colombo 0.0700714
 51  A*24:02-B*51:01-C*12:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPB1*04:01  Sri Lanka Colombo 0.0700714
 52  A*02:01-B*51:01-C*14:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*03:01  Japan pop 17 0.07003,078
 53  A*31:01-B*51:01-C*14:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.07003,078
 54  A*24:02-B*51:01-C*16:02-DRB1*04:03-DQB1*03:02  India Tamil Nadu 0.06322,492
 55  A*33:03-B*51:01-C*16:02-DRB1*04:03-DQB1*03:02  India Tamil Nadu 0.06022,492
 56  A*01:01-B*51:01-C*16:02-DRB1*04:03-DQB1*03:02  India South UCBB 0.058811,446
 57  A*02:11-B*51:01-C*16:02-DRB1*04:03-DQB1*03:02  India South UCBB 0.055711,446
 58  A*11:01-B*51:01-C*16:02-DRB1*04:03-DQB1*03:02  India South UCBB 0.054111,446
 59  A*24:02-B*51:01-C*15:02-DRB1*04:03-DQB1*03:02  Malaysia Peninsular Malay 0.0526951
 60  A*68:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  India East UCBB 0.05122,403
 61  A*02:01-B*51:01-C*15:02-DRB1*04:03-DQB1*03:02  India Tamil Nadu 0.05122,492
 62  A*02:11-B*51:01-C*15:02-DRB1*04:03-DQB1*03:02  India Tamil Nadu 0.05122,492
 63  A*32:01-B*51:01-C*15:04-DRB1*04:03-DQB1*03:02  Germany DKMS - Turkey minority 0.05104,856
 64  A*31:01-B*51:02-C*08:01-DRB1*04:03-DQB1*03:02  USA Hispanic pop 2 0.04701,999
 65  A*02:06-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  USA Asian pop 2 0.04401,772
 66  A*11:01-B*51:02-C*15:02-DRB1*04:03-DQB1*03:02  USA Asian pop 2 0.04401,772
 67  A*11:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  India South UCBB 0.042311,446
 68  A*24:02-B*51:01-C*16:02-DRB1*04:03-DQB1*03:02  India East UCBB 0.04162,403
 69  A*11:01-B*51:01-C*15:02-DRB1*04:03-DQB1*03:02  Germany DKMS - Turkey minority 0.04104,856
 70  A*03:01-B*51:01-C*15:02-DRB1*04:03-DQB1*03:02  India Tamil Nadu 0.04012,492
 71  A*33:03-B*51:01-C*07:01-DRB1*04:03-DQB1*03:02  India Tamil Nadu 0.04012,492
 72  A*02:11-B*51:01-C*16:02-DRB1*04:03-DQB1*03:02  India West UCBB 0.03945,829
 73  A*68:01-B*51:01-C*16:02-DRB1*04:03-DQB1*03:02  India South UCBB 0.037511,446
 74  A*03:01-B*51:01-C*16:02-DRB1*04:03-DQB1*03:02  India Central UCBB 0.03474,204
 75  A*24:02-B*51:10-C*15:02-DRB1*04:03-DQB1*03:02  Colombia Bogotá Cord Blood 0.03421,463
 76  A*30:02-B*51:01-C*03:02-DRB1*04:03-DQB1*03:02  Colombia Bogotá Cord Blood 0.03421,463
 77  A*31:01-B*51:01-C*04:01-DRB1*04:03-DQB1*03:02  Colombia Bogotá Cord Blood 0.03421,463
 78  A*01:01-B*51:08-C*16:02-DRB1*04:03-DQB1*03:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 79  A*03:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 80  A*32:01-B*51:01-C*15:02-DRB1*04:03-DQB1*03:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 81  A*01:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  India South UCBB 0.033211,446
 82  A*02:01:01:01-B*51:01:01-C*15:02:01:01-DRB1*04:03:01-DQB1*03:02  Russia Nizhny Novgorod, Russians 0.03311,510
 83  A*02:01-B*51:01-C*15:02-DRB1*04:03-DQB1*03:02  Germany DKMS - Turkey minority 0.03204,856
 84  A*03:01-B*51:01-C*16:02-DRB1*04:03-DQB1*03:02  India South UCBB 0.031811,446
 85  A*68:01-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  India North UCBB 0.03175,849
 86  A*02:01-B*51:01-C*07:02-DRB1*04:03-DQB1*03:02  Germany DKMS - Turkey minority 0.03104,856
 87  A*03:02-B*51:01-C*14:02-DRB1*04:03-DQB1*03:02  Germany DKMS - Turkey minority 0.03104,856
 88  A*11:01-B*51:01-C*15:04-DRB1*04:03-DQB1*03:02  Germany DKMS - Turkey minority 0.03104,856
 89  A*11:01-B*51:01-C*15:02-DRB1*04:03-DQB1*03:02  India West UCBB 0.03055,829
 90  A*02:01-B*51:01-C*14:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*02:01-DPB1*14:01  Japan pop 17 0.03003,078
 91  A*02:07-B*51:01-C*14:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 92  A*24:02-B*51:01-C*03:04-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 93  A*24:02-B*51:01-C*14:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 94  A*26:02-B*51:01-C*14:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*02:01  Japan pop 17 0.03003,078
 95  A*31:01-B*51:01-C*14:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.03003,078
 96  A*31:01-B*51:01-C*15:02-DRB1*04:03-DQA1*03:01-DQB1*03:02-DPA1*01:03-DPB1*04:02  Japan pop 17 0.03003,078
 97  A*11:01-B*51:01-C*16:02-DRB1*04:03-DQB1*03:02  India West UCBB 0.02965,829
 98  A*02:01:01-B*51:01:01-C*14:02:01-DRB1*04:03:01-DQB1*03:02:01  China Zhejiang Han 0.02881,734
 99  A*02:01:01-B*51:02:01-C*15:02:01-DRB1*04:03:01-DQB1*03:02:01  China Zhejiang Han 0.02881,734
 100  A*11:01:01-B*51:01:01-C*04:01:01-DRB1*04:03:01-DQB1*03:02:01  China Zhejiang Han 0.02881,734

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 237) 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.
Liverpool, U.K.

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