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 74 (from 74) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*02-B*07-DRB1*08:01-DQB1*04:02  Colombia San Basilio de Palenque 5.952042
 2  A*03:01:01-B*07:02:01-C*07:02:01-DRB1*08:01:01-DQB1*04:02:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Parda 0.5882170
 3  A*02-B*07-DRB1*08:01-DQA1*04:01-DQB1*04:02  Brazil Paraná Caucasian 0.4537641
 4  A*24:02:01-B*07:02:01-C*07:02:01-DRB1*08:01:01-DQB1*04:02:01-DPB1*04:01:01  South African Black 0.3520142
 5  A*02:01:01-B*07:02:01-C*07:02:01-DRB1*08:01:01-DQA1*04:01:01-DQB1*04:02:01-DPA1*02:01:02-DPB1*26:01:02  Russia Belgorod region 0.3268153
 6  A*11:01:79-B*07:02:01-C*07:02:01-DRB1*08:01-DQA1*04:01:01-DQB1*04:02-DPA1*01:03:01-DPB1*03:01  Russia Belgorod region 0.3268153
 7  A*68:01:01-B*07:02:01-C*07:01:01-DRB1*08:01:01-DQA1*03:01:01-DQB1*04:02:01-DPA1*02:01:01-DPB1*10:01  Russia Belgorod region 0.3268153
 8  A*24:02:01-B*07:02:01-C*07:02:01-DRB1*08:01:01-DQB1*04:02:01  Spain, Canary Islands, Gran canaria island 0.2300215
 9  A*26:01-B*07:02-C*07:02-DRB1*08:01-DQA1*04:01-DQB1*04:02-DPB1*04:01  Nicaragua Managua 0.2165339
 10  A*31:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  England North West 0.2000298
 11  A*02:01:01-B*07:02:01-C*07:02:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.192123,595
 12  A*03:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02-DPB1*03:01  Russia Karelia 0.16231,075
 13  A*02:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Russia Karelia 0.15911,075
 14  A*03:01:01-B*07:02:01-C*07:02:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.150623,595
 15  A*02:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  Italy pop 5 0.1400975
 16  A*24:02:01:01-B*07:02:01-C*07:02:01:03-DRB1*08:01:01-DQB1*04:02:01  Russia Nizhny Novgorod, Russians 0.13481,510
 17  A*02:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  USA NMDP American Indian South or Central America 0.12975,926
 18  A*02:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.10304,335
 19  A*24:02-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.10304,335
 20  A*68-B*07-DRB1*08:01-DQA1*06:01-DQB1*04:02  Brazil Paraná Caucasian 0.0780641
 21  A*03:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 22  A*03:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.06303,456,066
 23  A*03:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02-DPB1*03:01  Germany DKMS - German donors 0.06133,456,066
 24  A*03-B*07-DRB1*08:01-DQA1*04:01-DQB1*04:02  Brazil Paraná Caucasian 0.0583641
 25  A*30:01-B*07:04-C*07:02-DRB1*08:01-DQB1*04:02-DPB1*17:01  Russia Karelia 0.05651,075
 26  A*03:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  USA Asian pop 2 0.04401,772
 27  A*03:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  India East UCBB 0.04162,403
 28  A*03:01:01:01-B*07:02:01-C*07:02:01:03-DRB1*08:01:01-DQB1*04:02:01  Russia Nizhny Novgorod, Russians 0.04101,510
 29  A*02:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.04053,456,066
 30  A*02:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  Germany DKMS - Turkey minority 0.04004,856
 31  A*24:02-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  Colombia Bogotá Cord Blood 0.03961,463
 32  A*25:01:01-B*07:02:01-C*07:02:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.037023,595
 33  A*33:03-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  India Central UCBB 0.03574,204
 34  A*02:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02-DPB1*03:01  Germany DKMS - German donors 0.03493,456,066
 35  A*02:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  Colombia Bogotá Cord Blood 0.03421,463
 36  A*01:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 37  A*31:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 38  A*02:07:01-B*07:02:01-C*07:02:01:03-DRB1*08:01:01-DQB1*04:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 39  A*26:01:01-B*07:02:01-C*07:02:01:03-DRB1*08:01:01-DQB1*04:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 40  A*29:01:01:01-B*07:05:01-C*15:05:02-DRB1*08:01:01-DQB1*04:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 41  A*11:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  Germany DKMS - Turkey minority 0.03104,856
 42  A*11:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  India Central UCBB 0.02384,204
 43  A*03:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  USA Hispanic pop 2 0.02301,999
 44  A*68:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  USA Hispanic pop 2 0.02301,999
 45  A*02:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  USA Asian pop 2 0.02201,772
 46  A*11:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  India East UCBB 0.02082,403
 47  A*24:02-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  India North UCBB 0.02065,849
 48  A*24:02:01-B*07:02:01-C*07:02:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.020123,595
 49  A*01:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02-DPB1*03:01  Germany DKMS - German donors 0.01973,456,066
 50  A*11:01:01-B*07:02:01-C*07:02:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.018723,595
 51  A*24:02-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.01863,456,066
 52  A*01:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  India West UCBB 0.01725,829
 53  A*24:02-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02-DPB1*03:01  Germany DKMS - German donors 0.01653,456,066
 54  A*32:01:01-B*07:02:01-C*07:02:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.013823,595
 55  A*01:01:01-B*07:02:01-C*07:02:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.012823,595
 56  A*33:03-B*07:05-C*15:05-DRB1*08:01-DQB1*04:02  India Central UCBB 0.01194,204
 57  A*01:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  Germany DKMS - Turkey minority 0.01004,856
 58  A*11:01-B*07:05-C*15:05-DRB1*08:01-DQB1*04:02  Germany DKMS - Turkey minority 0.01004,856
 59  A*29:01-B*07:05-C*15:05-DRB1*08:01-DQB1*04:02  India West UCBB 0.00865,829
 60  A*30:02-B*07:06-C*03:04-DRB1*08:01-DQB1*04:02  India West UCBB 0.00865,829
 61  A*33:03-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  India West UCBB 0.00865,829
 62  A*11:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  India North UCBB 0.00855,849
 63  A*23:01:01-B*07:02:01-C*07:02:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.007023,595
 64  A*26:01:01-B*07:02:01-C*07:02:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.006723,595
 65  A*31:01:02-B*07:02:01-C*03:04:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.004523,595
 66  A*11:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  India South UCBB 0.004411,446
 67  A*68:01-B*07:06-C*07:02-DRB1*08:01-DQB1*04:02  India South UCBB 0.004411,446
 68  A*01:01-B*07:02-C*07:02-DRB1*08:01-DQB1*04:02  India South UCBB 0.004311,446
 69  A*31:01:02-B*07:02:01-C*07:02:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.003423,595
 70  A*02:01:01-B*07:02:01-C*01:02:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.002123,595
 71  A*24:02:01-B*07:05:01-C*15:05:02-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.002123,595
 72  A*29:01:01-B*07:05:02-C*15:05:02-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.002123,595
 73  A*02:01:01-B*07:02:01-C*12:03:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.002023,595
 74  A*11:01:79-B*07:02:01-C*07:02:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.000997323,595

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.

support@allelefrequencies.net

Valid XHTML 1.0 Transitional