Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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A B C DRB1 DPA1 DPB1 DQA1 DQB1

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Displaying 1 to 100 (from 244) records   Pages: 1 2 3 of 3  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*03:01:01:01-B*51:01:01-C*01:02:01-DRB1*01:01:01-DQB1*05:01  Russia Bashkortostan, Bashkirs 1.6667120
 2  A*03:01:01-B*51:01:01-C*12:03:01-DRB1*01:01:01-DQB1*05:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Rio de Janeiro Black 1.470668
 3  A*02:01-B*51:01-DRB1*01:01-DQB1*05:01  Mexico Chihuahua Chihuahua City Pop 2 1.136488
 4  A*31:01:02-B*51:01:01-C*16:02:01-DRB1*01:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 1.1240356
 5  A*03:01-B*51:01-C*04:01-DRB1*01:01-DQA1*01:01-DQB1*05:01  United Arab Emirates Abu Dhabi 0.960052
 6  A*24:02:01-B*51:01:01-C*16:02:01-DRB1*01:01:01-DQB1*05:01:01  India Karnataka Kannada Speaking 0.7760174
 7  A*11:01-B*51:01-DRB1*01:01-DQB1*05:01  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 8  A*31:01-B*51:01-DRB1*01:01-DQB1*05:01  Mexico Chihuahua Chihuahua City Pop 2 0.568288
 9  A*31:01-B*51:01-C*16:02-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPB1*04:01  Sri Lanka Colombo 0.5602714
 10  A*02:01:01:01-B*51:01:01-C*01:02:01-DRB1*01:01:01-DQB1*05:01  Russia Bashkortostan, Tatars 0.5208192
 11  A*23:01-B*51:01-C*15:02-E*01:01:01-F*01:03:01-G*01:03-DRB1*01:01-DQA1*01:01-DQB1*05:01  Portugal Azores Terceira Island 0.4386130
 12  A*26:01:01-B*51:01:01-C*03:03:01-DRB1*01:01-DQB1*05:01:01  Russia Bashkortostan, Bashkirs 0.4167120
 13  A*31:01:02:01-B*51:01:01-C*15:02:01:01-DRB1*01:01:01-DQB1*05:01  Russia Bashkortostan, Bashkirs 0.4167120
 14  A*32:01-B*51:01-C*01:02-DRB1*01:01-DQA1*01:01-DQB1*05:01  Kosovo 0.4030124
 15  A*33:03:01-B*51:01:01-C*16:02:01-DRB1*01:01:01-DQB1*05:01:01  India Karnataka Kannada Speaking 0.3740174
 16  A*02:01-B*51:01-C*02:02-DRB1*01:01-DQB1*05:01  Italy pop 5 0.3000975
 17  A*11:01:01-B*51:01:01-C*14:02:01-DRB1*01:01:01-DQB1*05:01:01  India Karnataka Kannada Speaking 0.2870174
 18  A*33:03:01-B*51:01:01-C*16:02:01-DRB1*01:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 0.2810356
 19  A*24:02:01-B*51:01:01-C*15:02:01-DRB1*01:01:01-DQB1*05:01:01  India Andhra Pradesh Telugu Speaking 0.2688186
 20  A*03:01-B*51:01-C*14:02-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPB1*02:01  USA San Diego 0.2600496
 21  A*11:01-B*51:01-C*15:02-DRB1*01:01-DQA1*01:02-DQB1*05:01-DPB1*04:02  USA San Diego 0.2600496
 22  A*24:02-B*51:01-C*01:02-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPB1*03:01  USA San Diego 0.2600496
 23  A*32:03-B*51:01-C*14:02-DRB1*01:01-DQB1*05:01  Malaysia Peninsular Chinese 0.2577194
 24  A*31:01-B*51:01-C*16:02-DRB1*01:01-DQB1*05:01  India South UCBB 0.218311,446
 25  A*02:01-B*51:01-C*02:02:02-DRB1*01:01:01-DQB1*05:01:01  England North West 0.2000298
 26  A*02:01-B*51:01-C*15:02-DRB1*01:01:01-DQB1*05:01:01  England North West 0.2000298
 27  A*11:01-B*51:01-C*02:02:02-DRB1*01:01:01-DQB1*05:01:01  England North West 0.2000298
 28  A*32:01-B*51:01-C*15:02-DRB1*01:01-DQB1*05:01  Malaysia Peninsular Indian 0.1845271
 29  A*68:01-B*51:01-C*07:01-DRB1*01:01-DQB1*05:01  Malaysia Peninsular Indian 0.1845271
 30  A*02:01:01-B*51:01:01-C*15:02:01-DRB1*01:01:01-DQB1*05:01:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.168028,927
 31  A*29:01-B*51:01-DRB1*01:01-DQB1*05:01  Mexico Mexico City Tlalpan 0.1515330
 32  A*24:02-B*51:01-C*14:02-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPB1*04:01  Sri Lanka Colombo 0.1401714
 33  A*02:01-B*51:01-C*14:02-DRB1*01:01-DQB1*05:01  USA Hispanic pop 2 0.14001,999
 34  A*11:01:01-B*51:01:01-C*12:02:01-DRB1*01:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 0.1400356
 35  A*29:02-B*51:01-C*02:02-DRB1*01:01-DQB1*05:01  Italy pop 5 0.1400975
 36  A*68:01:02-B*51:01:01-C*16:02:01-DRB1*01:01:01-DQB1*05:01:01  India Kerala Malayalam speaking 0.1400356
 37  A*31:01-B*51:01-C*16:02-DRB1*01:01-DQB1*05:01  India Tamil Nadu 0.11752,492
 38  A*31:01-B*51:01-C*16:02-DRB1*01:01-DQB1*05:01  India West UCBB 0.10265,829
 39  A*31:01-B*51:01-C*16:02-DRB1*01:01-DQB1*05:01  USA Asian pop 2 0.08901,772
 40  A*68:01-B*51:01-C*15:02-DRB1*01:01-DQB1*05:01  Germany DKMS - Italy minority 0.08601,159
 41  A*26:01-B*51:01-C*16:02-DRB1*01:01-DQB1*05:01  India Tamil Nadu 0.07752,492
 42  A*24:02-B*51:01-C*16:02-DRB1*01:01-DQB1*05:01  India South UCBB 0.075311,446
 43  A*02:01-B*51:01-C*15:02-DRB1*01:01-DQB1*05:01  Germany DKMS - Turkey minority 0.07404,856
 44  A*24:02-B*51:01-C*06:02-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPB1*04:02  Sri Lanka Colombo 0.0700714
 45  A*31:01-B*51:01-C*16:02-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPB1*26:01  Sri Lanka Colombo 0.0700714
 46  A*68:01-B*51:01-C*07:01-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPB1*01:01  Sri Lanka Colombo 0.0700714
 47  A*68:01-B*51:01-C*15:07-DRB1*01:01-DQA1*01:01-DQB1*05:01-DPB1*09:01  Sri Lanka Colombo 0.0700714
 48  A*33:03-B*51:01-C*16:02-DRB1*01:01-DQB1*05:01  India West UCBB 0.06855,829
 49  A*02:01-B*51:01-C*02:02-DRB1*01:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.06841,463
 50  A*02:01-B*51:01-C*14:02-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 51  A*03:01-B*51:01-C*15:02-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 52  A*02:01-B*51:01-C*01:02-DRB1*01:01-DQB1*05:01  Germany DKMS - Turkey minority 0.06204,856
 53  A*68:01-B*51:01-C*16:02-DRB1*01:01-DQB1*05:01  India Tamil Nadu 0.06142,492
 54  A*68:01-B*51:01-C*15:02-DRB1*01:01-DQB1*05:01-DPB1*10:01  Russia Karelia 0.05651,075
 55  A*02:01-B*51:01-C*02:02-DRB1*01:01-DQB1*05:01-DPB1*04:02  Russia Karelia 0.05631,075
 56  A*02:07-B*51:01-C*16:02-DRB1*01:01-DQB1*05:01  Malaysia Peninsular Malay 0.0526951
 57  A*11:01-B*51:01-C*16:02-DRB1*01:01-DQB1*05:01  India West UCBB 0.05235,829
 58  A*02:01-B*51:01-C*01:02-DRB1*01:01-DQB1*05:01-DPB1*03:01  Germany DKMS - German donors 0.05163,456,066
 59  A*03:01-B*51:01-C*01:02-DRB1*01:01-DQB1*05:01-DPB1*03:01  Germany DKMS - German donors 0.05033,456,066
 60  A*03:01:01-B*51:01:01-C*01:02:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.049723,595
 61  A*24:02-B*51:01-C*14:02-DRB1*01:01-DQB1*05:01  USA Asian pop 2 0.04801,772
 62  A*02:01-B*51:01-C*15:02-DRB1*01:01-DQB1*05:01  USA Hispanic pop 2 0.04701,999
 63  A*01:01-B*51:01-C*14:02-DRB1*01:01-DQB1*05:01  USA Asian pop 2 0.04401,772
 64  A*23:01-B*51:01-C*15:02-DRB1*01:01-DQB1*05:01  USA African American pop 4 0.04402,411
 65  A*24:02-B*51:01-C*15:02-DRB1*01:01-DQB1*05:01  USA Asian pop 2 0.04401,772
 66  A*24:02-B*51:01-C*16:02-DRB1*01:01-DQB1*05:01  USA Asian pop 2 0.04401,772
 67  A*30:01-B*51:01-C*15:02-DRB1*01:01-DQB1*05:01  USA Asian pop 2 0.04401,772
 68  A*03:01-B*51:01-C*12:03-DRB1*01:01-DQB1*05:01  Germany DKMS - Italy minority 0.04301,159
 69  A*03:01-B*51:01-C*14:02-DRB1*01:01-DQB1*05:01  Germany DKMS - Italy minority 0.04301,159
 70  A*24:02-B*51:01-C*05:01-DRB1*01:01-DQB1*05:01  Germany DKMS - Italy minority 0.04301,159
 71  A*25:01-B*51:01-C*02:02-DRB1*01:01-DQB1*05:01  Germany DKMS - Italy minority 0.04301,159
 72  A*26:01-B*51:01-C*01:02-DRB1*01:01-DQB1*05:01  Germany DKMS - Italy minority 0.04301,159
 73  A*26:01-B*51:01-C*15:04-DRB1*01:01-DQB1*05:01  Germany DKMS - Italy minority 0.04301,159
 74  A*32:01-B*51:01-C*14:02-DRB1*01:01-DQB1*05:01  Germany DKMS - Italy minority 0.04301,159
 75  A*33:03-B*51:01-C*16:02-DRB1*01:01-DQB1*05:01  India North UCBB 0.04265,849
 76  A*31:01-B*51:01-C*16:02-DRB1*01:01-DQB1*05:01  India East UCBB 0.04162,403
 77  A*33:03-B*51:01-C*16:02-DRB1*01:01-DQB1*05:01  India East UCBB 0.04162,403
 78  A*68:01-B*51:01-C*07:29-DRB1*01:01-DQB1*05:01  India North UCBB 0.04075,849
 79  A*11:01-B*51:01-C*15:02-DRB1*01:01-DQB1*05:01  India Tamil Nadu 0.04012,492
 80  A*02:11-B*51:01-C*16:02-DRB1*01:01-DQB1*05:01  India South UCBB 0.040111,446
 81  A*24:02-B*51:01-C*16:02-DRB1*01:01-DQB1*05:01  India Tamil Nadu 0.03832,492
 82  A*02:01-B*51:01-C*14:02-DRB1*01:01-DQB1*05:01  Germany DKMS - Turkey minority 0.03604,856
 83  A*02:01:01-B*51:01:01-C*14:02:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.035823,595
 84  A*02:01:01-B*51:01:01-C*01:02:01-DRB1*01:01:01-DQB1*05:01:01  Poland BMR 0.035623,595
 85  A*02:01-B*51:01-C*02:02-DRB1*01:01-DQB1*05:01  Germany DKMS - Turkey minority 0.03504,856
 86  A*02:01-B*51:01-C*14:02-DRB1*01:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.03421,463
 87  A*02:13-B*51:01-C*15:02-DRB1*01:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.03421,463
 88  A*03:01-B*51:01-C*14:02-DRB1*01:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.03421,463
 89  A*31:01-B*51:01-C*15:02-DRB1*01:01-DQB1*05:01  Colombia Bogotá Cord Blood 0.03421,463
 90  A*24:02-B*51:01-C*16:02-DRB1*01:01-DQB1*05:01  India Central UCBB 0.03414,204
 91  A*02:01-B*51:01-C*15:02-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 92  A*03:01-B*51:01-C*14:02-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 93  A*24:02-B*51:01-C*15:02-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 94  A*26:01-B*51:01-C*01:02-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 95  A*29:02-B*51:01-C*02:02-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 96  A*29:02-B*51:01-C*15:02-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 97  A*31:01-B*51:01-C*14:02-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 98  A*68:03-B*51:01-C*05:01-DRB1*01:01-DQB1*05:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.03404,335
 99  A*26:01:01-B*51:01:01-C*01:02:01-DRB1*01:01:01-DQB1*05:01  Russia Nizhny Novgorod, Russians 0.03311,510
 100  A*26:01:01-B*51:01:01-C*15:02:01-DRB1*01:01:01-DQB1*05:01  Russia Nizhny Novgorod, Russians 0.03311,510

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 244) records   Pages: 1 2 3 of 3  


   

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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