Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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A B C DRB1 DPA1 DPB1 DQA1 DQB1

Population:  Country:  Source of dataset : 
Region:  Ethnic Origin:     Type of study :  Sort by: 
Sample Size:      Sample Year:     Loci Tested: 
Displaying 1 to 100 (from 319) records   Pages: 1 2 3 4 of 4  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*02-B*37-DRB1*10-DQB1*05  Mexico Veracruz, Coatzacoalcos 2.678655
 2  A*01-B*37-C*06:02-DRB1*10:01-DQB1*05  Russia Transbaikal Territory Buryats 2.3340150
 3  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Tamil Nadu 1.95162,492
 4  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India South UCBB 1.785911,446
 5  A*01-B*37-DRB1*10-DQB1*05  Mexico San Luis Potosi, San Luis Potosi city 1.666730
 6  A*24-B*37-DRB1*10-DQB1*05  Mexico Veracruz, Orizaba 1.666760
 7  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India West UCBB 1.43205,829
 8  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP South Asian Indian 1.3953185,391
 9  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Northeast UCBB 1.3514296
 10  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India East UCBB 1.34252,403
 11  B*37:01-DRB1*10:01-DQB1*05:01  South Korea pop 3 1.3000485
 12  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Malaysia Peninsular Indian 1.2915271
 13  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Central UCBB 1.27444,204
 14  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQA1*01:01-DQB1*05:01-DPB1*02:01  Sri Lanka Colombo 1.2605714
 15  A*01-B*37-DRB1*10-DQB1*05  Mexico Hidalgo, Pachuca 1.219541
 16  A*01:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  India Karnataka Kannada Speaking 1.1490174
 17  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India North UCBB 1.04995,849
 18  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Southeast Asian 1.034527,978
 19  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  South Korea pop 3 1.0000485
 20  A*01-B*37-DRB1*10-DQB1*05  Mexico Mexico City South 0.961552
 21  A*11:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 0.9490356
 22  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Korean 0.923177,584
 23  A*02:01-B*37:01-DRB1*10:01-DQB1*05:01  Iran Yazd 0.892956
 24  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  USA Asian pop 2 0.88901,772
 25  A*29-B*37-DRB1*10-DQB1*05  Mexico Veracruz, Orizaba 0.833360
 26  A*01-B*37-DRB1*10-DQB1*05  Mexico Chiapas Rural 0.8264121
 27  A*02:06:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.8065186
 28  A*01:01-B*37:01-C*03:02-DRB1*10:01-DQB1*05:02  Iran Gorgan 0.780064
 29  A*01:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 0.5960356
 30  A*02-B*37-DRB1*10-DQB1*05  Mexico Zacatecas, Zacatecas city 0.595284
 31  A*02:11-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Malaysia Peninsular Indian 0.5535271
 32  A*02:11:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.5376186
 33  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQA1*03:01-DQB1*05:01-DPB1*02:01  USA San Diego 0.5210496
 34  A*01:01:01:01-B*37:01:01-C*06:02:01:01-DRB1*10:01:01-DQB1*05:01  Russia Bashkortostan, Tatars 0.5208192
 35  A*02:01-B*37:01-DRB1*10:01-DQB1*05:01  Iran Tabriz Azeris 0.515597
 36  A*01-B*37-DRB1*10-DQB1*05  Mexico Durango Rural 0.4587326
 37  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Italy pop 5 0.4400975
 38  A*02:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 0.4210356
 39  A*02:06:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 0.4210356
 40  A*31:01:02:01-B*37:01:01-C*03:03:01-DRB1*10:01:01-DQB1*05:01  Russia Bashkortostan, Bashkirs 0.4167120
 41  A*01-B*37-C*06:02-DRB1*10-DQB1*05  Russia North Ossetian 0.3900127
 42  A*02-B*37-C*06:02-DRB1*10-DQB1*05  Russia North Ossetian 0.3900127
 43  A*11:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Tamil Nadu 0.38852,492
 44  A*02:06-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Tamil Nadu 0.37902,492
 45  A*03:01-B*37:01-C*01:02-DRB1*10:01-DQB1*05:01  Malaysia Peninsular Indian 0.3690271
 46  A*33:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Malaysia Peninsular Indian 0.3690271
 47  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Vietnamese 0.366843,540
 48  A*26-B*37-C*06-DRB1*10-DQB1*05  Albania pop 2 0.3400432
 49  A*33-B*37-C*03:04-DRB1*10:01-DQB1*05  Russia Transbaikal Territory Buryats 0.3340150
 50  A*01-B*37-DRB1*10-DQB1*05  Mexico Oaxaca, Oaxaca city 0.3311151
 51  A*01-B*37-DRB1*10-DQB1*05  Mexico Mexico City Center 0.3247152
 52  A*11:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 53  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Chinese 0.310399,672
 54  A*32-B*37-DRB1*10-DQB1*05  Mexico Guanajuato Rural 0.3067162
 55  A*02-B*37-DRB1*10-DQB1*05  Mexico Jalisco, Zapopan 0.2976168
 56  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Germany DKMS - Turkey minority 0.29404,856
 57  A*01:01:01-B*37:04:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  India Karnataka Kannada Speaking 0.2870174
 58  A*33:03:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 0.2810356
 59  A*26:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  USA NMDP Caribean Indian 0.273914,339
 60  A*11:01:01-B*37:01:01-C*03:04:01-DRB1*10:01:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 61  A*24:02:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 62  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Malaysia Peninsular Malay 0.2629951
 63  A*02-B*37-DRB1*10-DQB1*05  Mexico Coahuila, Torreon 0.2500396
 64  A*02:06-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.242611,446
 65  A*33:03-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India East UCBB 0.23802,403
 66  A*01:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01  Costa Rica Central Valley Mestizo (G) 0.2262221
 67  A*02:06-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India West UCBB 0.21505,829
 68  A*11:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.202811,446
 69  A*68:01-B*37:01:01-C*06:02-DRB1*10:01:01-DQB1*05:01:01  England North West 0.2000298
 70  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP Japanese 0.199324,582
 71  A*01:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 72  A*02:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 73  A*02:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01-DPA1*02:01:02-DPB1*01:01:01  Brazil Rio de Janeiro Caucasian 0.1946521
 74  A*01-B*37-DRB1*10-DQB1*05  Mexico Zacatecas Rural 0.1859266
 75  A*24-B*37-DRB1*10-DQB1*05  Mexico Zacatecas Rural 0.1859266
 76  A*29-B*37-DRB1*10-DQB1*05  Mexico Veracruz Rural 0.1848539
 77  A*11:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Malaysia Peninsular Indian 0.1845271
 78  A*24:02-B*37:14-C*06:02-DRB1*10:01-DQB1*05:01  Malaysia Peninsular Indian 0.1845271
 79  A*24:07-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Malaysia Peninsular Indian 0.1845271
 80  A*24:02-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Tamil Nadu 0.18122,492
 81  A*02:06-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Central UCBB 0.18074,204
 82  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  USA NMDP American Indian South or Central America 0.17915,926
 83  A*01:01:01-B*37:01:01-C*06:02:01-DRB1*10:01:01-DQB1*05:01:01  China Zhejiang Han 0.17301,734
 84  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  Germany DKMS - Italy minority 0.17301,159
 85  A*02:06-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Northeast UCBB 0.1689296
 86  A*03:02-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Northeast UCBB 0.1689296
 87  A*01:01-B*37:01-C*06:02-DRB1*10:01-DRBX*NNNN-DQB1*05:01  USA NMDP European Caucasian 0.15901,242,890
 88  A*03:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Tamil Nadu 0.15752,492
 89  A*02-B*37-DRB1*10:01-DQA1*01:01-DQB1*05:01  Brazil Paraná Caucasian 0.1560641
 90  A*32:01-B*37:01-DRB1*10:01-DQB1*05:01  Mexico Mexico City Tlalpan 0.1515330
 91  A*11:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Central UCBB 0.15134,204
 92  A*68:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India Tamil Nadu 0.14502,492
 93  A*01-B*37-DRB1*10-DQB1*05  Mexico Michoacan Rural 0.1433348
 94  A*01:01-B*37:01-C*07:04-DRB1*10:01-DQA1*01:01-DQB1*05:01-DPB1*04:01  Sri Lanka Colombo 0.1401714
 95  A*11:01-B*37:01-C*07:02-DRB1*10:01-DQA1*01:01-DQB1*05:01-DPB1*04:01  Sri Lanka Colombo 0.1401714
 96  A*02:03:01-B*37:01:01-C*15:02:01-DRB1*10:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 0.1400356
 97  A*32:01:01-B*37:01:01-C*05:01:01-DRB1*10:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 0.1400356
 98  A*24:02-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.139711,446
 99  A*68:01-B*37:01-C*06:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.137211,446
 100  A*01:01-B*37:01-C*06:02-DRB1*10:01-DQA1*01:05-DQB1*05:01-DPA1*01:03-DPB1*02:01  Japan pop 17 0.13003,078

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 319) records   Pages: 1 2 3 4 of 4  


   

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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