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 92 (from 92) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*11:01:01-B*07:02:01-C*07:02:01-DRB1*10:01:01-DQB1*05:01:01  Vietnam Kinh 0.9900101
 2  A*03:01-B*07:02-DRB1*10:01-DQB1*05:01  Iran Tabriz Azeris 0.515597
 3  A*29:01-B*07:02-DRB1*10:01-DQB1*05:01  Iran Tabriz Azeris 0.515597
 4  A*03:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  Italy pop 5 0.4400975
 5  A*02:01:01-B*07:02:01-C*07:02:01-DRB1*10:01:01-DQA1*01:03:01-DQB1*05:01:01-DPA1*01:03:01-DPB1*04:01:01  Russian Federation Vologda Region 0.4202119
 6  A*68:01-B*07:02-C*07:02-DRB1*10:01-DQA1*05:05-DQB1*05:01  Brazil Puyanawa 0.3333150
 7  A*32:01:01-B*07:02:01-C*07:02:01-DRB1*10:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 0.2760356
 8  A*31:01:02-B*07:02:01-C*07:02:01-DRB1*10:01:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 9  A*03:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India Tamil Nadu 0.24692,492
 10  A*03:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India East UCBB 0.23642,403
 11  A*02:01-B*07:02-C*07:02-DRB1*10:01-DQA1*01:01-DQB1*05:01-DPA1*02:01-DPB1*11:01  Mexico Chiapas Lacandon Mayans 0.2294218
 12  A*03:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India North UCBB 0.20895,849
 13  A*30:01-B*07:02-C*06:02-DRB1*10:01-DQB1*05:01  Malaysia Peninsular Indian 0.1845271
 14  A*03:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India Central UCBB 0.18394,204
 15  A*11:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India Northeast UCBB 0.1689296
 16  A*24:02-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India Tamil Nadu 0.16512,492
 17  A*33:03-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01-DPB1*17:01  Tanzania Maasai 0.1597336
 18  A*03:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India West UCBB 0.15635,829
 19  A*02:01-B*07:02-DRB1*10:01-DQB1*05:01  Mexico Mexico City Tlalpan 0.1515330
 20  A*01:01:01-B*07:02:01-C*07:02:01-DRB1*10:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 0.1450356
 21  A*02:01:01-B*07:02:21-C*07:02:01-DRB1*10:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 0.1400356
 22  A*03:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.134511,446
 23  A*11:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India East UCBB 0.12722,403
 24  A*24:02-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India Central UCBB 0.11824,204
 25  A*24:02-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India North UCBB 0.10615,849
 26  A*03:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.10251,463
 27  A*01:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India West UCBB 0.09715,829
 28  A*24:02-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.082211,446
 29  A*11:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India Central UCBB 0.07674,204
 30  A*11:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India West UCBB 0.07615,829
 31  A*11:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India Tamil Nadu 0.07562,492
 32  A*11:01-B*07:02-C*07:02-DRB1*10:01-DQA1*01:01-DQB1*05:01-DPB1*09:01  Sri Lanka Colombo 0.0700714
 33  A*24:02-B*07:02-C*07:02-DRB1*10:01-DQA1*01:01-DQB1*05:01-DPB1*17:01  Sri Lanka Colombo 0.0700714
 34  A*24:02-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India East UCBB 0.06742,403
 35  A*68:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India Central UCBB 0.06504,204
 36  A*11:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India North UCBB 0.05675,849
 37  A*26:01-B*07:02-C*12:03-DRB1*10:01-DQB1*05:01-DPB1*13:01  Russia Karelia 0.05651,075
 38  A*68:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India North UCBB 0.05445,849
 39  A*11:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.053611,446
 40  A*02:02-B*07:02-C*07:01-DRB1*10:01-DQB1*05:01  USA Hispanic pop 2 0.04701,999
 41  A*24:02-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  USA Hispanic pop 2 0.04701,999
 42  A*01:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  USA Asian pop 2 0.04401,772
 43  A*02:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  USA African American pop 4 0.04402,411
 44  A*32:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  USA Asian pop 2 0.04401,772
 45  A*32:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India East UCBB 0.04162,403
 46  A*68:24-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India East UCBB 0.04162,403
 47  A*32:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India North UCBB 0.03535,849
 48  A*32:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.034811,446
 49  A*25:01-B*07:02-C*07:172-DRB1*10:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.03421,463
 50  A*02:05-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 51  A*03:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 52  A*24:02-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 53  A*11:01-B*07:02:01-C*07:02:01:03-DRB1*10:01:01-DQB1*05:01  Russia Nizhny Novgorod, Russians 0.03311,510
 54  A*26:01:01-B*07:02:01-C*07:02:01:03-DRB1*10:01:01-DQB1*05:01  Russia Nizhny Novgorod, Russians 0.03311,510
 55  A*29:01-B*07:02-C*15:05-DRB1*10:01-DQB1*05:01  India Tamil Nadu 0.02882,492
 56  A*02:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.027311,446
 57  A*24:02-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India West UCBB 0.02715,829
 58  A*68:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India West UCBB 0.02575,829
 59  A*02:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India Central UCBB 0.02264,204
 60  A*01:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.021311,446
 61  A*32:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India Central UCBB 0.02134,204
 62  A*02:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India East UCBB 0.02082,403
 63  A*33:03-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India Tamil Nadu 0.02012,492
 64  A*02:09-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.016911,446
 65  A*68:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.014411,446
 66  A*02:131-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.013111,446
 67  A*29:02-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  USA Hispanic pop 2 0.01201,999
 68  A*31:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  USA Hispanic pop 2 0.01201,999
 69  A*29:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India Central UCBB 0.01194,204
 70  A*33:03-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India West UCBB 0.01145,829
 71  A*26:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.011111,446
 72  A*30:02-B*07:02-C*15:05-DRB1*10:01-DQB1*05:01  USA African American pop 4 0.01102,411
 73  A*33:03-B*07:02-C*15:05-DRB1*10:01-DQB1*05:01  USA African American pop 4 0.01102,411
 74  A*03:01:01-B*07:02:01-C*07:02:01-DRB1*10:01:01-DQB1*05:01:01  Poland BMR 0.010823,595
 75  A*31:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.010511,446
 76  A*01:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  Germany DKMS - Turkey minority 0.01004,856
 77  A*24:02-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  Germany DKMS - Turkey minority 0.01004,856
 78  A*02:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India North UCBB 0.00965,849
 79  A*03:02-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India North UCBB 0.00925,849
 80  A*02:09-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India West UCBB 0.00865,829
 81  A*11:01-B*07:02-C*01:02-DRB1*10:01-DQB1*05:01  India West UCBB 0.00865,829
 82  A*31:12-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India North UCBB 0.00865,849
 83  A*01:01:01-B*07:02:01-C*07:02:01-DRB1*10:01:01-DQB1*05:01:01  Poland BMR 0.006223,595
 84  A*02:11-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India North UCBB 0.00615,849
 85  A*02:06-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.005411,446
 86  A*33:03-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.005211,446
 87  A*02:01:01-B*07:02:01-C*07:02:01-DRB1*10:01:01-DQB1*05:01:01  Poland BMR 0.004423,595
 88  A*03:01-B*07:02-C*07:48-DRB1*10:01-DQB1*05:01  India South UCBB 0.004411,446
 89  A*24:02-B*07:02-C*12:02-DRB1*10:01-DQB1*05:01  India South UCBB 0.004411,446
 90  A*24:02:01-B*07:02:01-C*07:02:01-DRB1*10:01:01-DQB1*05:01:01  Poland BMR 0.002223,595
 91  A*03:26-B*07:02:01-C*07:02:01-DRB1*10:01:01-DQB1*05:01:01  Poland BMR 0.002123,595
 92  A*01:01-B*07:02-C*07:02-DRB1*10:01-DQB1*05:01  India East UCBB 0.00182,403

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).




   

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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