Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Displaying 1 to 100 (from 119) records   Pages: 1 2 of 2  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*01:01:01-B*35:02:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.6250405
 2  A*02:01-B*15:01-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*03:01  Russia Karelia 0.47831,075
 3  A*02:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  Italy pop 5 0.4300975
 4  A*01:01:01-B*15:01:01-C*04:01:01-DRB1*08:01:01-DQA1*01:02:01-DQB1*04:02:01-DPA1*01:03:01-DPB1*14:01:01  Russian Federation Vologda Region 0.4202119
 5  A*24:02-B*35:08-C*04:01-DRB1*08:01-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 6  B*35:08-C*04:01-DRB1*08:01-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 7  A*03:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*03:01  Russia Karelia 0.27861,075
 8  A*03:01:01-B*35:03:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.267223,595
 9  A*01:01:01:01-B*35:02:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Russia Bashkortostan, Tatars 0.2604192
 10  A*02:01:01:01-B*15:01:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Russia Bashkortostan, Tatars 0.2604192
 11  A*02:01-B*15:01-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*04:02  Russia Karelia 0.25031,075
 12  A*23:01-B*15:01-C*04:01-DRB1*08:01-DQB1*04:02  England North West 0.2000298
 13  A*03:01:01:01-B*35:03:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Russia Nizhny Novgorod, Russians 0.19821,510
 14  A*68:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*04:02  Panama 0.1900462
 15  A*11:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02  India Northeast UCBB 0.1689296
 16  A*03:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  Italy pop 5 0.1600975
 17  A*02:01-B*35:08-C*04:01-DRB1*08:01-DQB1*04:02  Italy pop 5 0.1400975
 18  A*11:01:01:01-B*15:01:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Russia Nizhny Novgorod, Russians 0.13031,510
 19  A*11:01-B*15:01-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*03:01  Russia Karelia 0.11271,075
 20  A*02:01:01:01-B*15:01:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Russia Nizhny Novgorod, Russians 0.10151,510
 21  A*02:01:01-B*15:01:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.094623,595
 22  A*02:01-B*15:01-C*04:01-DRB1*08:01-DQB1*04:02  Germany DKMS - Italy minority 0.08601,159
 23  A*03:01-B*15:01-C*04:01-DRB1*08:01-DQB1*04:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 24  A*02:01:01:01-B*35:03:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Russia Nizhny Novgorod, Russians 0.06671,510
 25  A*03:01:01:01-B*35:01:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Russia Nizhny Novgorod, Russians 0.06621,510
 26  A*11:01:01:01-B*51:01:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Russia Nizhny Novgorod, Russians 0.06621,510
 27  A*03:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02  India North UCBB 0.06105,849
 28  A*03:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*04:01  Russia Karelia 0.05821,075
 29  A*11:01-B*15:01-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*01:01  Russia Karelia 0.05651,075
 30  A*26:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*06:01  Russia Karelia 0.05651,075
 31  A*26:01-B*15:34-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*04:01  Russia Karelia 0.05651,075
 32  A*32:01-B*15:01-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*01:01  Russia Karelia 0.05641,075
 33  A*11:01-B*51:01-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*04:02  Russia Karelia 0.05641,075
 34  A*24:02-B*15:01-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*20:01  Russia Karelia 0.05641,075
 35  A*68:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02  USA Hispanic pop 2 0.04701,999
 36  A*11:01:01-B*15:01:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.045623,595
 37  A*02:11-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  USA Asian pop 2 0.04401,772
 38  A*03:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  USA African American pop 4 0.04402,411
 39  A*26:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02  USA Asian pop 2 0.04401,772
 40  A*02:01-B*51:01-C*04:01-DRB1*08:01-DQB1*04:02  Germany DKMS - Italy minority 0.04301,159
 41  A*11:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  Germany DKMS - Italy minority 0.04301,159
 42  A*31:01-B*15:01-C*04:01-DRB1*08:01-DQB1*04:02  Germany DKMS - Italy minority 0.04301,159
 43  A*03:01:01-B*35:01:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.042623,595
 44  A*03:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*03:01  Germany DKMS - German donors 0.03973,456,066
 45  A*11:01:01-B*35:01:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.036223,595
 46  A*02:01-B*51:01-C*04:01-DRB1*08:01-DQB1*04:02  Colombia Bogotá Cord Blood 0.03421,463
 47  A*29:02-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02  Colombia Bogotá Cord Blood 0.03421,463
 48  A*68:02-B*53:01-C*04:01-DRB1*08:01-DQB1*04:02  Colombia Bogotá Cord Blood 0.03421,463
 49  A*01:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 50  A*03:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 51  A*24:02-B*35:02-C*04:01-DRB1*08:01-DQB1*04:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 52  A*02:01-B*15:01-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*03:01  Germany DKMS - German donors 0.03373,456,066
 53  A*11:01:01:01-B*35:03:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 54  A*24:02:01:01-B*35:01:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 55  A*24:02:01:01-B*35:03:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 56  A*24:02:01-B*15:01:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 57  A*31:01:02:01-B*35:03:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 58  A*68:01:01-B*35:03:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.028923,595
 59  A*01:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  India North UCBB 0.02565,849
 60  A*03:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  India Central UCBB 0.02384,204
 61  A*02:01:01-B*51:01:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.023023,595
 62  A*02:01-B*51:01-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*03:01  Germany DKMS - German donors 0.02183,456,066
 63  A*01:01:01-B*35:03:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.020723,595
 64  A*31:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02  India Tamil Nadu 0.02012,492
 65  A*03:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.01773,456,066
 66  A*03:01:01-B*15:01:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.016923,595
 67  A*68:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.01613,456,066
 68  A*02:01:01-B*35:03:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.014323,595
 69  A*03:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*03:01  Germany DKMS - German donors 0.01323,456,066
 70  A*68:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*03:01  Germany DKMS - German donors 0.01253,456,066
 71  A*02:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  USA Hispanic pop 2 0.01201,999
 72  A*11:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  USA Hispanic pop 2 0.01201,999
 73  A*24:02-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  USA Hispanic pop 2 0.01201,999
 74  A*30:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  USA Hispanic pop 2 0.01201,999
 75  A*34:02-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  USA Hispanic pop 2 0.01201,999
 76  A*68:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  USA Hispanic pop 2 0.01201,999
 77  A*01:01:01-B*35:01:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.012023,595
 78  A*01:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  India Central UCBB 0.01194,204
 79  A*24:03-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02  India Central UCBB 0.01194,204
 80  A*26:01-B*15:34-C*04:01-DRB1*08:01-DQB1*04:02  India Central UCBB 0.01194,204
 81  A*24:02:01-B*15:01:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.011123,595
 82  A*11:01-B*15:01-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*03:01  Germany DKMS - German donors 0.01073,456,066
 83  A*03:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.01063,456,066
 84  A*24:02:01-B*35:03:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.010523,595
 85  A*68:01:02-B*35:01:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.010323,595
 86  A*02:11-B*15:04-C*04:01-DRB1*08:01-DQB1*04:02  India Tamil Nadu 0.01002,492
 87  A*03:01-B*51:01-C*04:01-DRB1*08:01-DQB1*04:02  Germany DKMS - Turkey minority 0.01004,856
 88  A*32:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  India North UCBB 0.00965,849
 89  A*32:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02  India North UCBB 0.00935,849
 90  A*32:01:01-B*15:01:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.009223,595
 91  A*03:02-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02  India West UCBB 0.00865,829
 92  A*33:03-B*35:02-C*04:01-DRB1*08:01-DQB1*04:02  India West UCBB 0.00865,829
 93  A*23:01-B*15:34-C*04:01-DRB1*08:01-DQB1*04:02  India North UCBB 0.00855,849
 94  A*31:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  India North UCBB 0.00855,849
 95  A*68:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  India North UCBB 0.00855,849
 96  A*02:01:01-B*35:01:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.007823,595
 97  A*02:11-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02  India North UCBB 0.00755,849
 98  A*68:02:01-B*53:01:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.007023,595
 99  A*26:01:01-B*35:03:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.006123,595
 100  A*25:01:01-B*15:01:01-C*04:01:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.005223,595

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).


Displaying 1 to 100 (from 119) 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.

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