Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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Displaying 1 to 100 (from 116) records   Pages: 1 2 of 2  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*68-B*35-DRB1*08:01-DQB1*04:02  Russia Chuvash 3.700082
 2  A*31-B*35-DRB1*08:01-DQB1*04:02  Bolivia Quechua 0.720069
 3  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
 4  A*02:01-B*35:01-DRB1*08:01-DQB1*04:02  Mexico Veracruz Xalapa 0.595284
 5  A*02:05-B*35:27-C*12:03-E*01:01:01-F*01:01:02-G*01:03-DRB1*08:01-DQA1*01:01-DQB1*04:02  Portugal Azores Terceira Island 0.4386130
 6  A*02:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  Italy pop 5 0.4300975
 7  A*23:01:01-B*35:01:01-C*03:03:01-DRB1*08:01:01-DQA1*05:01:01-DQB1*04:02:01-DPA1*01:03:01-DPB1*03:01  Russian Federation Vologda Region 0.4202119
 8  A*02:01:01:01-B*35:01:01:02-C*12:03:01:01-DRB1*08:01:01-DQB1*04:02:01  Russia Bashkortostan, Bashkirs 0.4167120
 9  A*24:02-B*35:08-C*04:01-DRB1*08:01-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 10  B*35:08-C*04:01-DRB1*08:01-DQB1*04:02  Mexico Mexico City Mestizo population 0.3497143
 11  A*25:01:01-B*35:03:01-C*02:02:02-DRB1*08:01-DQA1*01:01:01-DQB1*04:02-DPA1*01:03:01-DPB1*03:01  Russia Belgorod region 0.3268153
 12  A*02-B*35-DRB1*08:01-DQA1*04:01-DQB1*04:02  Brazil Paraná Caucasian 0.3120641
 13  A*68:01-B*35:01-C*03:03-DRB1*08:01-DQB1*04:02-DPB1*03:01  Russia Karelia 0.28121,075
 14  A*03:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*03:01  Russia Karelia 0.27861,075
 15  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
 16  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
 17  A*68:03-B*35:01-C*07:02-DRB1*08:01-DQA1*04:01-DQB1*04:02-DPA1*01:03-DPB1*04:01  Mexico Chiapas Lacandon Mayans 0.2294218
 18  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
 19  A*68:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*04:02  Panama 0.1900462
 20  A*11:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02  India Northeast UCBB 0.1689296
 21  A*03:01-B*35:01-C*03:03-DRB1*08:01-DQB1*04:02-DPB1*04:01  Russia Karelia 0.16621,075
 22  A*03:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  Italy pop 5 0.1600975
 23  A*02:01-B*35:08-C*04:01-DRB1*08:01-DQB1*04:02  Italy pop 5 0.1400975
 24  A*11:01-B*35:01-C*07:01-DRB1*08:01-DQB1*04:02  Italy pop 5 0.1400975
 25  A*02:01:01-B*35:01:01-C*03:03:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.136823,595
 26  A*03-B*35-DRB1*08:01-DQA1*04:01-DQB1*04:02  Brazil Paraná Caucasian 0.1121641
 27  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
 28  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
 29  A*03:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02  India North UCBB 0.06105,849
 30  A*03:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*04:01  Russia Karelia 0.05821,075
 31  A*02:01-B*35:01-C*03:03-DRB1*08:01-DQB1*04:02-DPB1*03:01  Russia Karelia 0.05751,075
 32  A*26:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02-DPB1*06:01  Russia Karelia 0.05651,075
 33  A*68:01-B*35:01-C*03:03-DRB1*08:01-DQB1*04:02-DPB1*04:02  Russia Karelia 0.05651,075
 34  A*68:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02  USA Hispanic pop 2 0.04701,999
 35  A*02:11-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  USA Asian pop 2 0.04401,772
 36  A*03:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  USA African American pop 4 0.04402,411
 37  A*26:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02  USA Asian pop 2 0.04401,772
 38  A*11:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  Germany DKMS - Italy minority 0.04301,159
 39  A*24:02-B*35:03-C*12:03-DRB1*08:01-DQB1*04:02  Germany DKMS - Italy minority 0.04301,159
 40  A*01:01-B*35:01-C*03:03-DRB1*08:01-DQB1*04:02  India West UCBB 0.04295,829
 41  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
 42  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
 43  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
 44  A*02:01-B*35:01-C*03:03-DRB1*08:01-DQB1*04:02  India West UCBB 0.03435,829
 45  A*02:01-B*35:01-C*03:03-DRB1*08:01-DQB1*04:02  India North UCBB 0.03425,849
 46  A*29:02-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02  Colombia Bogotá Cord Blood 0.03421,463
 47  A*01:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 48  A*03:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 49  A*24:02-B*35:01-C*03:03-DRB1*08:01-DQB1*04:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 50  A*24:02-B*35:02-C*04:01-DRB1*08:01-DQB1*04:02  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 51  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
 52  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
 53  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
 54  A*29:01:01:01-B*35:03:01-C*07:04:01-DRB1*08:01:01-DQB1*04:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 55  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
 56  A*68:01:02:02-B*35:01:01:02-C*03:03:01-DRB1*08:01:01-DQB1*04:02:01  Russia Nizhny Novgorod, Russians 0.03311,510
 57  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
 58  A*02:01-B*35:01-C*03:03-DRB1*08:01-DQB1*04:02-DPB1*04:01  Germany DKMS - German donors 0.02853,456,066
 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-B*35:01-C*03:03-DRB1*08:01-DQB1*04:02  USA Asian pop 2 0.02201,772
 62  A*03:01-B*35:01-C*03:03-DRB1*08:01-DQB1*04:02  Germany DKMS - Turkey minority 0.02104,856
 63  A*68:01-B*35:01-C*03:03-DRB1*08:01-DQB1*04:02  Germany DKMS - Turkey minority 0.02104,856
 64  A*11:01-B*35:03-C*12:03-DRB1*08:01-DQB1*04:02  India East UCBB 0.02082,403
 65  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
 66  A*31:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02  India Tamil Nadu 0.02012,492
 67  A*03:01:01-B*35:01:01-C*03:03:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.018523,595
 68  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
 69  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
 70  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
 71  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
 72  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
 73  A*02:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  USA Hispanic pop 2 0.01201,999
 74  A*11:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  USA Hispanic pop 2 0.01201,999
 75  A*24:02-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  USA Hispanic pop 2 0.01201,999
 76  A*30:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  USA Hispanic pop 2 0.01201,999
 77  A*34:02-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  USA Hispanic pop 2 0.01201,999
 78  A*68:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  USA Hispanic pop 2 0.01201,999
 79  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
 80  A*01:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  India Central UCBB 0.01194,204
 81  A*02:01-B*35:01-C*03:03-DRB1*08:01-DQB1*04:02  India Central UCBB 0.01194,204
 82  A*02:06-B*35:01-C*03:03-DRB1*08:01-DQB1*04:02  India Central UCBB 0.01194,204
 83  A*02:131-B*35:01-C*03:03-DRB1*08:01-DQB1*04:02  India Central UCBB 0.01194,204
 84  A*24:03-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02  India Central UCBB 0.01194,204
 85  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
 86  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
 87  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
 88  A*02:01-B*35:02-C*06:02-DRB1*08:01-DQB1*04:02  Germany DKMS - Turkey minority 0.01004,856
 89  A*30:01-B*35:01-C*03:03-DRB1*08:01-DQB1*04:02  Germany DKMS - Turkey minority 0.01004,856
 90  A*68:01-B*35:01-C*01:02-DRB1*08:01-DQB1*04:02  Germany DKMS - Turkey minority 0.01004,856
 91  A*32:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  India North UCBB 0.00965,849
 92  A*32:01-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02  India North UCBB 0.00935,849
 93  A*03:02-B*35:03-C*04:01-DRB1*08:01-DQB1*04:02  India West UCBB 0.00865,829
 94  A*24:02-B*35:03-C*12:03-DRB1*08:01-DQB1*04:02  India West UCBB 0.00865,829
 95  A*24:07-B*35:01-C*03:03-DRB1*08:01-DQB1*04:02  India West UCBB 0.00865,829
 96  A*33:03-B*35:02-C*04:01-DRB1*08:01-DQB1*04:02  India West UCBB 0.00865,829
 97  A*31:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  India North UCBB 0.00855,849
 98  A*68:01-B*35:01-C*04:01-DRB1*08:01-DQB1*04:02  India North UCBB 0.00855,849
 99  A*68:01:02-B*35:01:01-C*03:03:01-DRB1*08:01:01-DQB1*04:02:01  Poland BMR 0.007923,595
 100  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

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 116) 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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