Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

Please specify your search by selecting options from boxes. Then, click "Search" to find HLA Haplotype frequencies that match your criteria. Remember at least one option must be selected.
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 122) records   Pages: 1 2 of 2  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*01:01:01-B*50:01-C*06:02-DRB1*03:01-DQA1*05:01-DQB1*02:01  Morocco Atlantic Coast Chaouya 2.100098
 2  A*02:01-B*50:01-DRB1*03:01-DQB1*02:01  Iran Saqqez-Baneh Kurds 0.833360
 3  A*02:01-B*50:01-DRB1*03:01-DQB1*02:01  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 4  A*02:05-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.51975,849
 5  A*03:02-B*50:01-DRB1*03:01-DQB1*02:01  Iran Tabriz Azeris 0.515597
 6  B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Mexico Mexico City Mestizo pop 2 0.4300234
 7  A*11:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Mexico Mexico City Mestizo population 0.3497143
 8  B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Mexico Mexico City Mestizo population 0.3497143
 9  A*02:05-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.31794,204
 10  A*24:02:01-B*50:01:01-C*07:02:01-DRB1*03:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 11  A*02:05-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.26745,829
 12  A*68:01:02:01-B*50:01:01-C*06:02:01:02-DRB1*03:01:01-DQB1*02:01:01  Russia Bashkortostan, Tatars 0.2604192
 13  A*03:02-B*50:01-C*15:02-DRB1*03:01-DQA1*05:01-DQB1*02:01-DPB1*04:01  USA San Diego 0.2600496
 14  A*01:01:01-B*50:01:01-C*06:02:01-DRB1*03:01:01-DQB1*02:01:01  Spain, Canary Islands, Gran canaria island 0.2300215
 15  A*02:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.20511,463
 16  A*02:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.20504,335
 17  A*02:01-B*50:01-C*06:02-DRB1*03:01:01-DQB1*02:01  England North West 0.2000298
 18  A*23:01-B*50:01-C*06:02-DRB1*03:01:01-DQB1*02:01  England North West 0.2000298
 19  A*33:03-B*50:01-C*06:02-DRB1*03:01:01-DQB1*02:01  England North West 0.2000298
 20  A*23:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.19904,856
 21  A*02:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.14104,856
 22  A*11:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Italy pop 5 0.1400975
 23  A*24:02-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Italy pop 5 0.1400975
 24  A*03:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.13365,849
 25  A*02:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Italy minority 0.12901,159
 26  A*02:05-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India East UCBB 0.12532,403
 27  A*68:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.12325,849
 28  A*03:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  USA Hispanic pop 2 0.12201,999
 29  A*01:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.10234,204
 30  A*01:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.09515,849
 31  A*23:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.09435,849
 32  A*02:05-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  USA Asian pop 2 0.08901,772
 33  A*01:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.07895,829
 34  A*02:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01-DPB1*04:01  Germany DKMS - German donors 0.07373,456,066
 35  A*03:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.07364,204
 36  A*03:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.07104,856
 37  A*01:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 38  A*23:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 39  A*03:01:01:01-B*50:01:01-C*06:02:01:02-DRB1*03:01:01-DQB1*02:01  Russia Nizhny Novgorod, Russians 0.06621,510
 40  A*01:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.06604,856
 41  A*02:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  USA Hispanic pop 2 0.06501,999
 42  A*02:05-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India Tamil Nadu 0.06172,492
 43  A*23:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.06005,829
 44  A*02:06:01-B*50:01:01-C*06:02:01-DRB1*03:01:01-DQB1*02:01:01  China Zhejiang Han 0.05771,734
 45  A*31:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01-DPB1*02:01  Russia Karelia 0.05651,075
 46  A*11:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India Tamil Nadu 0.05122,492
 47  A*23:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.04834,204
 48  A*31:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  USA Hispanic pop 2 0.04701,999
 49  A*24:02-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.04505,849
 50  A*23:01:01-B*50:01:01-C*06:02:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.044423,595
 51  A*02:01:01-B*50:01:01-C*06:02:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.044323,595
 52  A*02:01-B*50:01-C*15:02-DRB1*03:01-DQB1*02:01  USA Asian pop 2 0.04401,772
 53  A*24:02-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  USA Asian pop 2 0.04401,772
 54  A*02:05-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Italy minority 0.04301,159
 55  A*33:03-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.04234,204
 56  A*03:02-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.03804,856
 57  A*11:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.03705,849
 58  A*32:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.03421,463
 59  A*02:05-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 60  A*03:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 61  A*30:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 62  A*30:02-B*50:01-C*04:01-DRB1*03:01-DQB1*02:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 63  A*30:01:01-B*50:01:01-C*06:02:01:02-DRB1*03:01:01-DQB1*02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 64  A*68:01:02:02-B*50:01:01-C*06:02:01:02-DRB1*03:01:01-DQB1*02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 65  A*03:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.031011,446
 66  A*24:02-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.02805,829
 67  A*68:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.02625,829
 68  A*02:05-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.02604,856
 69  A*02:08-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.02595,849
 70  A*02:06-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.02585,849
 71  A*68:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.02364,204
 72  A*02:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.02324,204
 73  A*02:05-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.022211,446
 74  A*26:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.02175,849
 75  A*33:03-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.02155,849
 76  A*23:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01-DPB1*04:01  Germany DKMS - German donors 0.02133,456,066
 77  A*30:04-B*50:01-C*08:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.02104,856
 78  A*02:11-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India East UCBB 0.02082,403
 79  A*03:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India East UCBB 0.02082,403
 80  A*31:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India East UCBB 0.02082,403
 81  A*68:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India East UCBB 0.02082,403
 82  A*68:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.02004,856
 83  A*24:02-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.016111,446
 84  A*03:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.01575,829
 85  A*02:05:01-B*50:01:01-C*06:02:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.015323,595
 86  A*11:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.01504,856
 87  A*24:02-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.01364,204
 88  A*23:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.013111,446
 89  A*23:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01-DPB1*02:01  Germany DKMS - German donors 0.01283,456,066
 90  A*02:01-B*50:01-C*01:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.01194,204
 91  A*02:08-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.01194,204
 92  A*03:02-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.01194,204
 93  A*30:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.01195,849
 94  A*32:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.01194,204
 95  A*02:06-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.01185,829
 96  A*01:01:01-B*50:01:01-C*06:02:01-DRB1*03:01:01-DQB1*02:01:01  Poland BMR 0.011123,595
 97  A*02:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01-DPB1*03:01  Germany DKMS - German donors 0.01113,456,066
 98  A*03:01-B*50:01-C*15:04-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.01004,856
 99  A*33:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.01004,856
 100  A*66:01-B*50:01-C*06:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.01004,856

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 122) records   Pages: 1 2 of 2  


   

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.

support@allelefrequencies.net


Valid XHTML 1.0 Transitional