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 96 (from 96) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*02-B*52-DRB1*03:01-DQB1*02  Mexico Baja California Rural 1.000050
 2  A*32:01-B*52:01-DRB1*03:01-DQB1*02:01  Iran Saqqez-Baneh Kurds 0.833360
 3  A*02-B*52-DRB1*03:01-DQB1*02  Mexico Baja California, La Paz 0.666775
 4  A*02:01-B*52:01-DRB1*03:01-DQB1*02:01  Iran Tabriz Azeris 0.515597
 5  A*33-B*52-DRB1*03:01-DQB1*02  Mexico Durango Rural 0.3058326
 6  A*30:02-B*52:01-C*12:02-DRB1*03:01-DQA1*05:01-DQB1*02:01-DPB1*04:01  USA San Diego 0.2600496
 7  A*01:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.23165,849
 8  A*01:01-B*52:01-C*07:01-DRB1*03:01-DQA1*05:01-DQB1*02:01-DPB1*16:01  Nicaragua Managua 0.2165339
 9  A*30:02-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01-DPB1*02:01  Panama 0.1900462
 10  A*03:01-B*52:01-DRB1*03:01-DQB1*02:01  Mexico Mexico City Tlalpan 0.1515330
 11  A*30:01-B*52:01-C*03:02-DRB1*03:01-DQB1*02:01  Italy pop 5 0.1400975
 12  A*30-B*52-DRB1*03:01-DQB1*02  Mexico Jalisco Rural 0.0853585
 13  A*11:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.08145,829
 14  A*24:02-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.07804,204
 15  A*26-B*52-DRB1*03:01-DQA1*05:01-DQB1*02:01  Brazil Paraná Caucasian 0.0780641
 16  A*01:01-B*52:01-C*15:04-DRB1*03:01-DQB1*02:01  India West UCBB 0.07725,829
 17  A*01:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.07134,204
 18  A*23-B*52-DRB1*03:01-DQB1*02  Mexico Mexico City North 0.0664751
 19  A*32:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.06255,849
 20  A*68:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.06025,829
 21  A*11:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Malay 0.0526951
 22  A*33:03-B*52:01-C*07:21-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Malay 0.0526951
 23  A*01:01-B*52:01-C*15:04-DRB1*03:01-DQB1*02:01  India North UCBB 0.05005,849
 24  A*11:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India Tamil Nadu 0.04912,492
 25  A*68:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India East UCBB 0.04702,403
 26  A*02:01-B*52:01-C*16:01-DRB1*03:01-DQB1*02:01  USA African American pop 4 0.04402,411
 27  A*31:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  USA Asian pop 2 0.04401,772
 28  A*30-B*52-DRB1*03:01-DQB1*02  Mexico Jalisco, Guadalajara city 0.04191,189
 29  A*11:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.041711,446
 30  A*02:11-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.03824,204
 31  A*03:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.03804,856
 32  A*02:22-B*52:01-C*07:02-DRB1*03:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.03421,463
 33  A*68:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.03421,463
 34  A*24:02:01-B*52:01:01:02-C*12:02:02-DRB1*03:01:01-DQB1*02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 35  A*01:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.030611,446
 36  A*01:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.02925,829
 37  A*26:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.02804,856
 38  A*24:02-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India Tamil Nadu 0.02742,492
 39  A*02:06-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.02585,849
 40  A*02:11-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.025411,446
 41  A*01:01-B*52:01-C*15:04-DRB1*03:01-DQB1*02:01  India Central UCBB 0.02384,204
 42  A*11:03-B*52:01-C*07:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.02384,204
 43  A*26:01-B*52:01-C*03:04-DRB1*03:01-DQB1*02:01  USA Asian pop 2 0.02201,772
 44  A*11:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.02105,849
 45  A*01:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India East UCBB 0.02082,403
 46  A*24:07-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India East UCBB 0.02082,403
 47  A*01:01:01-B*52:01:01-C*12:02:02-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.019823,595
 48  A*11:01:01-B*52:01:01-C*12:02:02-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.016823,595
 49  A*24:02-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.015911,446
 50  A*02:06-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.01384,204
 51  A*33:03-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.01304,204
 52  A*03:01:01-B*52:01:01-C*12:16-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.012723,595
 53  A*11:01-B*52:01-C*15:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.01194,204
 54  A*11:01-B*52:01-C*15:04-DRB1*03:01-DQB1*02:01  India Central UCBB 0.01194,204
 55  A*11:01-B*52:01-C*16:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.01194,204
 56  A*24:02-B*52:04-C*12:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.01194,204
 57  A*30:01-B*52:01-C*06:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.01194,204
 58  A*30:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.01194,204
 59  A*32:01-B*52:01-C*04:01-DRB1*03:01-DQB1*02:01  India Central UCBB 0.01194,204
 60  A*33:03-B*52:01-C*03:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.01194,204
 61  A*69:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.01194,204
 62  A*68:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.01175,849
 63  A*03:01:01-B*52:01:01-C*12:02:02-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.011223,595
 64  A*24:02-B*52:01-C*07:02-DRB1*03:01-DQB1*02:01  USA Asian pop 2 0.01101,772
 65  A*24:07-B*52:01-C*07:02-DRB1*03:01-DQB1*02:01  USA Asian pop 2 0.01101,772
 66  A*01:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01-DPB1*04:01  Germany DKMS - German donors 0.01003,456,066
 67  A*01:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.01004,856
 68  A*29:02-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.01004,856
 69  A*03:02-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.00995,849
 70  A*03:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India Tamil Nadu 0.00972,492
 71  A*01:01-B*52:01-C*06:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.008711,446
 72  A*03:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:07  India South UCBB 0.008711,446
 73  A*01:01-B*52:01-C*04:01-DRB1*03:01-DQB1*02:01  India North UCBB 0.00865,849
 74  A*23:01-B*52:01-C*15:04-DRB1*03:01-DQB1*02:01  India West UCBB 0.00865,829
 75  A*24:02-B*52:01-C*07:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.00865,829
 76  A*68:01-B*52:01-C*07:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.00865,829
 77  A*02:11-B*52:01-C*04:01-DRB1*03:01-DQB1*02:01  India North UCBB 0.00855,849
 78  A*24:02-B*52:01-C*12:03-DRB1*03:01-DQB1*02:01  India North UCBB 0.00855,849
 79  A*31:12-B*52:04-C*12:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.00855,849
 80  A*24:07-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.007811,446
 81  A*24:02:01-B*52:01:01-C*12:16-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.007723,595
 82  A*02:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.00694,204
 83  A*02:06-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.006111,446
 84  A*02:01:01-B*52:01:01-C*12:02:02-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.004723,595
 85  A*01:01-B*52:04-C*12:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.004411,446
 86  A*24:07-B*52:01-C*07:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.004411,446
 87  A*26:01-B*52:01-C*16:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.004411,446
 88  A*11:01-B*52:04-C*12:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.004211,446
 89  A*02:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.00415,849
 90  A*68:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.00414,204
 91  A*23:01:01-B*52:01:01-C*12:02:02-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.004023,595
 92  A*26:01-B*52:01-C*12:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.00384,204
 93  A*30:01:01-B*52:01:01-C*12:02:02-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.002123,595
 94  A*32:01:01-B*52:01:01-C*12:02:02-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.001923,595
 95  A*32:01-B*52:01-C*15:04-DRB1*03:01-DQB1*02:01  India North UCBB 0.00135,849
 96  A*01:01:01-B*52:01:01-C*12:16-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.000811923,595

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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