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 190) records   Pages: 1 2 of 2  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  A*33:03-B*58:01-C*03:02-DRB1*03:01-DRB3*02:02-DQB1*02:01  USA NMDP Chinese 4.600599,672
 2  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01:01  Vietnam Kinh 4.4550101
 3  A*33:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Chinese 4.1237194
 4  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01:01  China Zhejiang Han 4.01521,734
 5  A*33:03-B*58:01-C*03:02-DRB1*03:01-DRB3*02:02-DQB1*02:01  USA NMDP Vietnamese 3.668143,540
 6  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Vietnam Hanoi Kinh pop 2 3.5000170
 7  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  USA Asian pop 2 2.21401,772
 8  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01:01  India Andhra Pradesh Telugu Speaking 2.1050186
 9  A*33:03-B*58:01-C*03:02-DRB1*03:01-DRB3*02:02-DQB1*02:01  USA NMDP Filipino 1.950950,614
 10  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01/02:02  South Korea pop 3 1.9000485
 11  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Chinese 1.8041194
 12  A*33:03-B*58:01-C*03:02-DRB1*03:01-DRB3*02:02-DQB1*02:01  USA NMDP Southeast Asian 1.678627,978
 13  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India North UCBB 1.52475,849
 14  A*33:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Malay 1.4138951
 15  A*33-B*58-C*03:02-DRB1*03:01-DQB1*02  Russia Transbaikal Territory Buryats 1.3340150
 16  A*33:03-B*58:01-C*03:02-DRB1*03:01-DRB3*02:02-DQB1*02:01  USA NMDP Korean 1.289377,584
 17  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQA1*05:01-DQB1*02:01-DPB1*04:01  Sri Lanka Colombo 1.2605714
 18  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India Central UCBB 1.22414,204
 19  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India East UCBB 1.13112,403
 20  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India Tamil Nadu 1.08112,492
 21  A*33:03-B*58:01-C*03:02-DRB1*03:01-DRB3*02:02-DQB1*02:01  USA NMDP South Asian Indian 1.0562185,391
 22  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India South UCBB 1.047311,446
 23  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India Northeast UCBB 1.0135296
 24  A*11:01:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01:01  Vietnam Kinh 0.9900101
 25  A*01:01-B*58:01-C*03:02-DRB1*03:01-DQA1*05:01-DQB1*02:01  United Arab Emirates Abu Dhabi 0.960052
 26  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQA1*05:05-DQB1*02:01  United Arab Emirates Abu Dhabi 0.960052
 27  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.91035,829
 28  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  USA NMDP Hawaiian or other Pacific Islander 0.732811,499
 29  A*31:01:02-B*58:01:01-C*03:02:01-DRB1*03:01:01-DQB1*02:01  Mexico Hidalgo Mezquital Valley/ Otomi 0.694472
 30  A*02:01:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*04:01:01  Brazil Barra Mansa Rio State Caucasian 0.6250405
 31  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Malay 0.5783951
 32  A*33:03:01-B*58:01:01-C*03:02:01-DRB1*03:01:01-DQB1*02:01:01  India Karnataka Kannada Speaking 0.5750174
 33  A*24:02-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Chinese 0.5155194
 34  A*02:01-B*58:01-C*03:02-DRB1*03:01-DQA1*01:01-DQB1*02:01-DPB1*04:02  Kenya, Nyanza Province, Luo tribe 0.5000100
 35  A*11:01:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01:01  China Zhejiang Han 0.44481,734
 36  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQA1*05:01-DQB1*02:01-DPB1*04:01  Nicaragua Managua 0.4329339
 37  A*26:01:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQA1*05:01:01-DQB1*02:01:01-DPA1*01:03:01-DPB1*04:01  Russian Federation Vologda Region 0.4202119
 38  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01  Russia Bashkortostan, Bashkirs 0.4167120
 39  A*33:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01-DPB1*05:01  Panama 0.3800462
 40  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQA1*05:01-DQB1*02:01-DPB1*14:01  Sri Lanka Colombo 0.3501714
 41  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Mexico Mexico City Mestizo population 0.3497143
 42  B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Mexico Mexico City Mestizo population 0.3497143
 43  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01-DPB1*04:01  Russia Karelia 0.33861,075
 44  A*23-B*58-C*03:02-DRB1*03:01-DQB1*02  Russia Transbaikal Territory Buryats 0.3340150
 45  A*26-B*58-C*03:02-DRB1*03:01-DQB1*02  Russia Transbaikal Territory Buryats 0.3340150
 46  A*01:01:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01:01  India Andhra Pradesh Telugu Speaking 0.3143186
 47  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Italy pop 5 0.2900975
 48  A*11:01:01-B*58:01:01-C*03:02:01-DRB1*03:01:01-DQB1*02:01:01  India Kerala Malayalam speaking 0.2810356
 49  A*24:02-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  USA Asian pop 2 0.26301,772
 50  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQA1*05:01-DQB1*02:01-DPB1*04:01  USA San Diego 0.2600496
 51  A*11:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Chinese 0.2577194
 52  A*33:03:01-B*58:01:01-C*03:02:01-DRB1*03:01:01-DQB1*02:01:01-DPB1*02:01:02  Saudi Arabia pop 6 (G) 0.255128,927
 53  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.25104,856
 54  A*02:01:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01:01  China Zhejiang Han 0.20331,734
 55  A*02:01:01-B*58:01:01-C*03:02:01-DRB1*03:01:01-DQB1*02:01:01-DPB1*02:01:02  Saudi Arabia pop 6 (G) 0.193528,927
 56  A*03:02:01-B*58:01:01-C*03:02:01-DRB1*03:01-DQB1*02:01  Costa Rica Central Valley Mestizo (G) 0.1909221
 57  A*24:02-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India Tamil Nadu 0.18552,492
 58  A*02:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Indian 0.1845271
 59  A*33:03:01-B*58:01:01-C*03:02:01-DRB1*03:01:01-DQB1*02:01:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.173628,927
 60  A*26:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India Northeast UCBB 0.1689296
 61  A*24:02-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.16654,204
 62  A*01:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India Tamil Nadu 0.16422,492
 63  A*26:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Malay 0.1577951
 64  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  USA NMDP Black South or Central American 0.14984,889
 65  A*11:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.14975,849
 66  A*01:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India East UCBB 0.14902,403
 67  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  USA NMDP Caribean Indian 0.146614,339
 68  A*33:03:01-B*58:01:01-C*03:02:01-DRB1*03:01:01-DQB1*02:01:01  India Kerala Malayalam speaking 0.1400356
 69  A*68:01:02-B*58:01:01-C*03:02:01-DRB1*03:01:01-DQB1*02:01:01  India Kerala Malayalam speaking 0.1400356
 70  A*02:20-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.13015,849
 71  A*11:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.12995,829
 72  A*33:03-B*58:01-C*03:02-DRB1*03:01-DRB3*02:02-DQB1*02:01  USA NMDP Japanese 0.127824,582
 73  A*11:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.12144,204
 74  A*01:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.11565,849
 75  A*01:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.11455,829
 76  A*01:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.107211,446
 77  A*33:03-B*58:01-C*03:02-DRB1*03:01-DRB3*02:02-DQB1*02:01  USA NMDP Caribean Black 0.107133,328
 78  A*24:02-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Malay 0.1053951
 79  A*11:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Malaysia Peninsular Malay 0.1052951
 80  A*24:02:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01:01  China Zhejiang Han 0.10461,734
 81  A*02:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Germany DKMS - Turkey minority 0.10004,856
 82  A*24:02-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India North UCBB 0.09995,849
 83  A*24:02-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India East UCBB 0.09702,403
 84  A*11:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.095011,446
 85  A*02:20-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.09484,204
 86  A*02:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  USA Asian pop 2 0.09301,772
 87  A*33:03-B*58:01-C*03:02-DRB1*03:01-DRB3*02:02-DQB1*02:01  USA NMDP Middle Eastern or North Coast of Africa 0.092670,890
 88  A*02:07-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  USA Asian pop 2 0.08901,772
 89  A*31:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India Tamil Nadu 0.08372,492
 90  A*01:01-B*58:01-C*03:02-DRB1*03:01-DQA1*05:01-DQB1*02:01-DPB1*02:01  Sri Lanka Colombo 0.0700714
 91  A*33:03-B*58:01-C*03:02-DRB1*03:01-DQA1*05:01-DQB1*02:01-DPB1*01:01  Sri Lanka Colombo 0.0700714
 92  A*30:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Colombia Bogotá Cord Blood 0.06841,463
 93  A*02:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, 0.06804,335
 94  A*02:01:01:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01  Russia Nizhny Novgorod, Russians 0.06621,510
 95  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*03:01:01-DQB1*02:01  Russia Nizhny Novgorod, Russians 0.06621,510
 96  A*02:11-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India East UCBB 0.06562,403
 97  A*24:02-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India South UCBB 0.064411,446
 98  A*26:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.06435,829
 99  A*02:20-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India West UCBB 0.06005,829
 100  A*01:01-B*58:01-C*03:02-DRB1*03:01-DQB1*02:01  India Central UCBB 0.05914,204

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 190) 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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