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 493) records   Pages: 1 2 3 4 5 of 5  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*02:01-B*51:01-C*01:02-DRB1*14:01-DQA1*01:01-DQB1*05:03  Kosovo 2.4190124
 2  A*02-B*51-DRB1*14-DQB1*05  Mexico Guanajuato, Guanajuato city 2.272722
 3  A*02-B*51-DRB1*14-DQB1*05  Mexico Veracruz, Poza Rica 2.222245
 4  A*02:01-B*51:01-C*02:02-DRB1*14:54-DQA1*01:04-DQB1*05:03  United Arab Emirates Abu Dhabi 1.920052
 5  A*02-B*51-DRB1*14-DQB1*05  Mexico Mexico City South 0.961552
 6  A*02:11:01-B*51:01:01-C*14:02:01-DRB1*14:04:01-DQB1*05:03:01  India Karnataka Kannada Speaking 0.8620174
 7  A*02:52-B*51:01-DRB1*14:01-DQB1*05:02  Iran Saqqez-Baneh Kurds 0.833360
 8  A*11-B*51-DRB1*14-DQB1*05  Mexico Colima, Colima city 0.819761
 9  A*02:01-B*51:01-C*01:02-DRB1*14:01-DQA1*01:01-DQB1*05:03  Kosovo 0.8060124
 10  A*02-B*51-DRB1*14-DQB1*05  Mexico Morelos, Cuernavaca 0.609882
 11  A*01-B*51-DRB1*14-DQB1*05  Mexico Coahuila Rural 0.4587216
 12  A*03-B*51-DRB1*14-DQA1*01:01-DQB1*05:03  Russia, South Ural, Chelyabinsk region, Nagaybaks 0.4400112
 13  A*68:01:02:02-B*51:01:01:01-C*07:04:01-DRB1*14:04:01-DQB1*05:03:01  Russia Bashkortostan, Bashkirs 0.4167120
 14  A*02:01-B*51:01-C*01:02-DRB1*14:01-DQA1*01:04-DQB1*05:03  Kosovo 0.4030124
 15  A*03:01-B*51:01-C*15:06-DRB1*14:01-DQA1*01:01-DQB1*05:01  Kosovo 0.4030124
 16  A*24-B*51-C*14:02-DRB1*14-DQB1*05  Russia North Ossetian 0.3900127
 17  A*24:02-B*51:01-C*15:02-DRB1*14:04-DQB1*05:03  Malaysia Peninsular Indian 0.3690271
 18  A*68-B*51-DRB1*14-DQB1*05  Mexico Sonora, Ciudad Obregón 0.3497143
 19  A*02-B*51-C*01-DRB1*14-DQB1*05  Albania pop 2 0.3400432
 20  A*03-B*51-C*01-DRB1*14-DQB1*05  Albania pop 2 0.3400432
 21  A*31-B*51-C*15-DRB1*14-DQB1*05  Albania pop 2 0.3400432
 22  A*01-B*51-C*04:01-DRB1*14:01-DQB1*05  Russia Transbaikal Territory Buryats 0.3340150
 23  A*02-B*51-C*14:02-DRB1*14:01-DQB1*05  Russia Transbaikal Territory Buryats 0.3340150
 24  A*02:01-B*51:01-C*14:02-DRB1*14:01-DQA1*01:01-DQB1*05:03  Brazil Puyanawa 0.3333150
 25  A*02-B*51-DRB1*14-DQB1*05  Mexico Mexico City Center 0.3247152
 26  A*03:02:01-B*51:01:01-C*15:02:01-DRB1*14:54:01-DQB1*05:03:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 27  A*68-B*51-DRB1*14-DQB1*05  Mexico Guanajuato Rural 0.3067162
 28  A*02:01:01-B*51:06:01-C*14:02:01-DRB1*14:54:01-DQB1*05:03:01  India Karnataka Kannada Speaking 0.2870174
 29  A*33:03:01-B*51:01:01-C*15:02:01-DRB1*14:04:01-DQB1*05:03:01  India Karnataka Kannada Speaking 0.2870174
 30  A*02-B*51-DRB1*14-DQB1*05  Mexico Tlaxcala, Tlaxcala city 0.2762181
 31  A*03:01:01-B*51:01:01-C*15:04:01-DRB1*14:04:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 32  A*24:02:01-B*51:01:05-C*14:02:01-DRB1*14:10-DQB1*05:10  India Andhra Pradesh Telugu Speaking 0.2688186
 33  A*24:02:01-B*51:06:01-C*14:02:01-DRB1*14:04:01-DQB1*05:03:01  India Andhra Pradesh Telugu Speaking 0.2688186
 34  A*32:01:01-B*51:01:01-C*12:03:01-DRB1*14:54:01-DQB1*05:03:01  India Andhra Pradesh Telugu Speaking 0.2688186
 35  A*11:01-B*51:01-C*14:02-DRB1*14:04-DQB1*05:03  Malaysia Peninsular Malay 0.2629951
 36  A*02:06:01-B*51:01:01-C*15:02:01:01-DRB1*14:54:01-DQB1*05:02:01  Russia Bashkortostan, Tatars 0.2604192
 37  A*11:01-B*51:02-C*15:02-DRB1*14:01-DQB1*05:03  Malaysia Peninsular Chinese 0.2577194
 38  A*68-B*51-DRB1*14-DQB1*05  Mexico Yucatan, Merida 0.2564192
 39  A*68-B*51-DRB1*14-DQB1*05  Mexico Sonora Rural 0.2538197
 40  A*01:01:01-B*51:01:01-C*15:02:01-DRB1*14:01:01-DQB1*05:03:01  Spain, Canary Islands, Gran canaria island 0.2300215
 41  A*01:01-B*51:01-C*15:02-DRB1*14:01-DQA1*01:01-DQB1*05:03-DPB1*13:01  Nicaragua Managua 0.2165339
 42  A*02:01-B*51:01-C*16:01-DRB1*14:01-DQA1*01:01-DQB1*05:03-DPB1*01:01  Nicaragua Managua 0.2165339
 43  A*11-B*51-DRB1*14-DQB1*05  Mexico Chihuahua Rural 0.2092236
 44  A*25:01-B*51:01-C*14:02:01-DRB1*14:01-DQB1*05:03:01  England North West 0.2000298
 45  A*02:07:01-B*51:02:01-C*15:02:01-DRB1*14:54:01-DQB1*05:02:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 46  A*03:01-B*51:01-C*15:02-DRB1*14:15-DQB1*05:03  Malaysia Peninsular Indian 0.1845271
 47  A*24:02-B*51:01-C*14:02-DRB1*14:71-DQB1*05:03  Malaysia Peninsular Indian 0.1845271
 48  A*24:02-B*51:08-C*16:02-DRB1*14:01-DQB1*05:03  Malaysia Peninsular Indian 0.1845271
 49  A*31:18-B*51:01-C*15:02-DRB1*14:07-DQB1*05:01  Malaysia Peninsular Indian 0.1845271
 50  A*32:01-B*51:06-C*14:02-DRB1*14:04-DQB1*05:03  Malaysia Peninsular Indian 0.1845271
 51  A*11:01-B*51:01-C*14:02-DRB1*14:04-DQB1*05:03  USA Asian pop 2 0.17801,772
 52  A*02:11-B*51:01-C*14:02-DRB1*14:04-DQB1*05:03  India South UCBB 0.171111,446
 53  A*02:03-B*51:01-C*14:02-DRB1*14:54-DQB1*05:02  India Northeast UCBB 0.1689296
 54  A*31:12-B*51:01-C*15:02-DRB1*14:04-DQB1*05:03  India Northeast UCBB 0.1689296
 55  A*68:152-B*51:01-C*14:02-DRB1*14:04-DQB1*05:03  India Northeast UCBB 0.1689296
 56  A*24:02-B*51:06-C*14:02-DRB1*14:04-DQB1*05:03  India Tamil Nadu 0.16272,492
 57  A*02:11-B*51:01-C*14:02-DRB1*14:04-DQB1*05:03  India Tamil Nadu 0.14082,492
 58  A*24:02-B*51:01-C*14:02-DRB1*14:04-DQB1*05:03  India Tamil Nadu 0.14022,492
 59  A*02:11-B*51:01-C*07:02-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*04:01  Sri Lanka Colombo 0.1401714
 60  A*02:11-B*51:01-C*14:02-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*04:01  Sri Lanka Colombo 0.1401714
 61  A*01:01-B*51:01-C*07:02-DRB1*14:54-DQB1*05:03  Italy pop 5 0.1400975
 62  A*02:01-B*51:01-C*15:02-DRB1*14:01-DQB1*05:03  Italy pop 5 0.1400975
 63  A*02:11:01-B*51:01:01-C*07:02:01-DRB1*14:01:01-DQB1*05:03:01  India Kerala Malayalam speaking 0.1400356
 64  A*02:11:01-B*51:01:01-C*14:02:01-DRB1*14:15-DQB1*05:03:01  India Kerala Malayalam speaking 0.1400356
 65  A*24:02:01-B*51:01:01-C*16:02:01-DRB1*14:04:01-DQB1*05:03:01  India Kerala Malayalam speaking 0.1400356
 66  A*11-B*51-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.1317641
 67  A*31-B*51-DRB1*14-DQB1*05  Mexico Puebla Rural 0.1199833
 68  A*31:01-B*51:01-C*14:02-DRB1*14:05-DQA1*01:04-DQB1*05:03-DPA1*01:03-DPB1*02:01  Japan pop 17 0.10003,078
 69  A*11:01-B*51:01-C*14:02-DRB1*14:04-DQB1*05:03  India Central UCBB 0.09884,204
 70  A*11:01-B*51:01-C*14:02-DRB1*14:04-DQB1*05:03  India Tamil Nadu 0.09452,492
 71  A*68:01-B*51:01-C*16:02-DRB1*14:04-DQB1*05:03  India West UCBB 0.09075,829
 72  A*11:01-B*51:01-C*14:02-DRB1*14:04-DQB1*05:03  India South UCBB 0.090111,446
 73  A*29:02-B*51:01-C*15:02-DRB1*14:01-DQB1*05:03  Germany DKMS - Italy minority 0.08601,159
 74  A*03-B*51-C*01-DRB1*14-DQA1*01-DQB1*05  Spain, Castilla y Leon, Northwest, 0.08491,743
 75  A*01:01-B*51:01-C*15:02-DRB1*14:07-DQB1*05:03  India South UCBB 0.084211,446
 76  A*26:01-B*51:01-C*16:02-DRB1*14:04-DQB1*05:03  India Central UCBB 0.08234,204
 77  A*68:01-B*51:01-C*16:02-DRB1*14:04-DQB1*05:03  India North UCBB 0.08095,849
 78  A*02-B*51-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 79  A*03-B*51-DRB1*14:01-DQA1*01:04-DQB1*05:03  Brazil Paraná Caucasian 0.0780641
 80  A*24:02-B*51:01-C*14:02-DRB1*14:04-DQB1*05:03  India South UCBB 0.078011,446
 81  A*24:02:01-B*51:01:01-C*15:02:01-DRB1*14:05:01-DQB1*05:03:01  China Zhejiang Han 0.07741,734
 82  A*68:01-B*51:01-C*14:02-DRB1*14:04-DQB1*05:03  India South UCBB 0.070511,446
 83  A*02:01-B*51:01-C*07:02-DRB1*14:01-DQA1*01:01-DQB1*05:03-DPB1*04:01  Sri Lanka Colombo 0.0700714
 84  A*31:01-B*51:01-C*15:02-DRB1*14:07-DQA1*01:01-DQB1*05:03-DPB1*02:01  Sri Lanka Colombo 0.0700714
 85  A*68:01-B*51:01-C*15:02-DRB1*14:04-DQA1*01:01-DQB1*05:03-DPB1*03:01  Sri Lanka Colombo 0.0700714
 86  A*02:01-B*51:01-C*15:02-DRB1*14:54-DQA1*01:04-DQB1*05:02-DPA1*02:02-DPB1*05:01  Japan pop 17 0.07003,078
 87  A*26:05-B*51:01-C*15:02-DRB1*14:54-DQA1*01:04-DQB1*05:02-DPA1*01:03-DPB1*02:01  Japan pop 17 0.07003,078
 88  A*31:01-B*51:01-C*14:02-DRB1*14:05-DQA1*01:04-DQB1*05:03-DPA1*02:02-DPB1*05:01  Japan pop 17 0.07003,078
 89  A*31:01-B*51:01-C*15:02-DRB1*14:07-DQB1*05:03  India South UCBB 0.068711,446
 90  A*68:01-B*51:01-C*15:04-DRB1*14:54-DQB1*05:03  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 91  A*68-B*51-DRB1*14-DQB1*05  Mexico Mexico City North 0.0664751
 92  A*11-B*51-C*15-DRB1*14-DQA1*01-DQB1*05  Spain, Castilla y Leon, Northwest, 0.06571,743
 93  A*24-B*51-C*15-DRB1*14-DQA1*01-DQB1*05  Spain, Castilla y Leon, Northwest, 0.06571,743
 94  A*02-B*51-C*14-DRB1*14-DQA1*01-DQB1*05  Spain, Castilla y Leon, Northwest, 0.06541,743
 95  A*26:01-B*51:01-C*16:02-DRB1*14:04-DQB1*05:03  India North UCBB 0.06485,849
 96  A*01:01-B*51:01-C*15:02-DRB1*14:04-DQB1*05:03  India West UCBB 0.06365,829
 97  A*03:01-B*51:01-C*14:02-DRB1*14:04-DQB1*05:03  India East UCBB 0.06242,403
 98  A*68:01-B*51:01-C*16:02-DRB1*14:04-DQB1*05:03  India East UCBB 0.06242,403
 99  A*02-B*51-DRB1*14-DQB1*05  Ecuador Andes Mixed Ancestry 0.0607824
 100  A*01:01-B*51:01-C*15:02-DRB1*14:07-DQB1*05:03  India Tamil Nadu 0.06022,492

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 493) records   Pages: 1 2 3 4 5 of 5  


   

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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