Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

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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 100 (from 161) records   Pages: 1 2 of 2  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  B*18:01-C*07:04  Philippines Ivatan 7.000050
 2  B*18:01-C*07:04  Kenya Nandi 3.1000240
 3  B*18:01-C*07:04  Kenya Luo 2.8000265
 4  A*30:02-B*18:01-C*07:04  Kenya Luo 1.7000265
 5  A*02:01-B*18:01-C*07:04  Kenya Nandi 1.5000240
 6  A*68:02-B*18:01-C*07:04-DRB1*08:04-DQB1*04:02-DPB1*04:01  Tanzania Maasai 1.2780336
 7  A*02:05-B*18:01-C*07:04  Kenya Nandi 1.2000240
 8  B*18:01-C*07:04  Uganda Kampala 1.2000161
 9  A*02:05-B*18:01-C*07:04  Kenya Luo 1.1000265
 10  A*43:01-B*18:01-C*07:04-DRB1*15:01-DQA1*01:02-DQB1*06:02-DPB1*04:02  South Africa Worcester 0.6000159
 11  A*01:01-B*18:01-C*07:04-DRB1*11:01-DQA1*01:02-DQB1*02:02-DPB1*55:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 12  A*02:03:01-B*18:01:01-C*07:04:01  China Jingpo Minority 0.4950105
 13  B*18:01:01-C*07:04:01  China Jingpo Minority 0.4900105
 14  A*25:01-B*18:01-C*07:04-DRB1*07:01  Russia Bering Island Aleuts 0.4808104
 15  A*26:01-B*18:01-C*07:04-DRB1*11:04-DQB1*03:01-DPB1*11:01  Tanzania Maasai 0.4792336
 16  B*18:01-C*07:04  USA African American pop 4 0.45702,411
 17  A*36:01-B*18:01:01-C*07:04:01-DRB1*11:01:02  Costa Rica Guanacaste Mestizo (G) 0.4545110
 18  A*68:01:02-B*18:01:01-C*07:04:01-DRB1*13:02:01-DQA1*01:02:01-DQB1*06:09:01-DPA1*02:02:02-DPB1*04:01:01  Russian Federation Vologda Region 0.4202119
 19  A*36:01-B*18:01:01-C*07:04:01-DRB1*04:11:01  Costa Rica Amerindians (G) 0.4032125
 20  A*11:01-B*18:01-C*07:04-DRB1*15:02-DQB1*05:01  Malaysia Peninsular Malay 0.3994951
 21  A*30:01:01-B*18:01:01-C*07:04:01-DRB1*11:01:02-DQB1*06:02:01-DPB1*01:01:01  South African Black 0.3520142
 22  A*30:02:01-B*18:01:01-C*07:04:01-DRB1*03:01:01-DQB1*02:01:01-DPB1*01:01:01  South African Black 0.3520142
 23  A*30:02:01-B*18:01:01-C*07:04:01-DRB1*11:01:02-DQB1*06:02:01-DPB1*105:01:01  South African Black 0.3520142
 24  A*30:02:01-B*18:01:01-C*07:04:01-DRB1*15:03:01-DQB1*06:02:01-DPB1*665:01  South African Black 0.3520142
 25  A*24:02-B*18:01-C*07:04-DRB1*11:04-DQB1*03:01  Mexico Mexico City Mestizo population 0.3497143
 26  B*18:01-C*07:04  Mexico Mexico City Mestizo population 0.3497143
 27  B*18:01-C*07:04-DRB1*11:04-DQB1*03:01  Mexico Mexico City Mestizo population 0.3497143
 28  A*24:07-B*18:01-C*07:04-DRB1*15:02-DQB1*05:01  Malaysia Peninsular Malay 0.3347951
 29  A*01:03-B*18:01-C*07:04-DRB1*04:01-DQB1*03:02-DPB1*02:01  Tanzania Maasai 0.3195336
 30  A*24:02-B*18:01-C*07:04-DRB1*12:02-DQB1*03:01  Malaysia Peninsular Malay 0.3116951
 31  A*11:01-B*18:01-C*07:04-DRB1*15:02-DQA1*01:01-DQB1*05:01-DPB1*13:01  South Africa Worcester 0.3000159
 32  A*24:02-B*18:01-C*07:04-DRB1*12:02-DQA1*06:01-DQB1*03:01-DPB1*04:01  South Africa Worcester 0.3000159
 33  A*29:01-B*18:01-C*07:04-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  South Africa Worcester 0.3000159
 34  A*43:01-B*18:01-C*07:04-DRB1*15:03-DQA1*01:02-DQB1*06:02-DPB1*04:02  South Africa Worcester 0.3000159
 35  A*02:11:01-B*18:01:01-C*07:04:01-DRB1*15:01:01-DQB1*06:01:01  India Karnataka Kannada Speaking 0.2870174
 36  A*23:01-B*18:01-C*07:04-DRB1*15:03-DQA1*01:02-DQB1*06:02-DPB1*17:01  USA San Diego 0.2600496
 37  A*02:01-B*18:01-C*07:04-DRB1*12:01-DQB1*03:01  Malaysia Peninsular Malay 0.2567951
 38  A*11:01-B*18:01-C*07:04-DRB1*12:02-DQB1*03:01  Malaysia Peninsular Malay 0.2492951
 39  A*02:01-B*18:01-C*07:04-DRB1*12:02-DQB1*03:01  Malaysia Peninsular Malay 0.2366951
 40  A*11:01-B*18:01-C*07:04-DRB1*12:01-DQB1*03:01  Malaysia Peninsular Malay 0.2315951
 41  A*24:02-B*18:01-C*07:04-DRB1*15:02-DQB1*05:01  Malaysia Peninsular Malay 0.2103951
 42  A*02:06-B*18:01-C*07:04-DRB1*11:01-DQB1*06:02-DPB1*105:01  Panama 0.1900462
 43  A*11:01-B*18:01-C*07:04-DRB1*12:02-DQB1*06:01  Malaysia Peninsular Indian 0.1845271
 44  B*18:01-C*07:04  USA Asian pop 2 0.17001,772
 45  A*68:02-B*18:01-C*07:04-DRB1*13:02-DQB1*06:09-DPB1*03:01  Tanzania Maasai 0.1597336
 46  A*74:01-B*18:01-C*07:04-DRB1*03:02-DQB1*04:02-DPB1*39:01  Tanzania Maasai 0.1597336
 47  A*74:01-B*18:01-C*07:04-DRB1*11:04-DQB1*03:01-DPB1*30:01  Tanzania Maasai 0.1597336
 48  A*11:01-B*18:01-C*07:04-DRB1*04:05-DQB1*04:02  Malaysia Peninsular Malay 0.1577951
 49  A*24:07-B*18:01-C*07:04-DRB1*12:02-DQB1*03:01  Malaysia Peninsular Malay 0.1457951
 50  B*18:01-C*07:04  Italy pop 5 0.1100975
 51  A*33:03-B*18:01-C*07:04-DRB1*15:01-DQB1*05:02  Malaysia Peninsular Malay 0.1052951
 52  A*24:03-B*18:01-C*07:04-DRB1*11:01  Italy pop 5 0.1000975
 53  A*02:06-B*18:01-C*07:04-DRB1*12:02-DQB1*03:01  USA Asian pop 2 0.08901,772
 54  A*02:01-B*18:01-C*07:04-DRB1*09:01-DQB1*03:03  Malaysia Peninsular Malay 0.0789951
 55  A*02:03-B*18:01-C*07:04-DRB1*14:04  Germany DKMS - China minority 0.07801,282
 56  A*11:01-B*18:01-C*07:04-DRB1*14:54  Hong Kong Chinese BMDR 0.07617,595
 57  B*18:01-C*07:04  USA Hispanic pop 2 0.07501,999
 58  A*02:11-B*18:01-C*07:04-DRB1*08:03-DQA1*01:03-DQB1*06:01-DPB1*10:01  Sri Lanka Colombo 0.0700714
 59  A*11:01-B*18:01-C*07:04-DRB1*11:04-DQB1*03:01  Colombia Bogotá Cord Blood 0.06841,463
 60  A*24:10-B*18:01-C*07:04-DRB1*12:02-DQB1*03:01  Malaysia Peninsular Malay 0.0630951
 61  A*02:01-B*18:01-C*07:04-DRB1*15:02-DQB1*05:01  Malaysia Peninsular Malay 0.0587951
 62  A*02:01-B*18:01-C*07:04-DRB1*08:03-DQB1*06:01  Malaysia Peninsular Malay 0.0526951
 63  A*02:03-B*18:01-C*07:04-DRB1*08:01-DQB1*06:01  Malaysia Peninsular Malay 0.0526951
 64  A*02:03-B*18:01-C*07:04-DRB1*15:01-DQB1*05:02  Malaysia Peninsular Malay 0.0526951
 65  A*11:01-B*18:01-C*07:04-DRB1*12:01-DQB1*06:01  Malaysia Peninsular Malay 0.0526951
 66  A*11:01-B*18:01-C*07:04-DRB1*12:02-DQB1*05:01  Malaysia Peninsular Malay 0.0526951
 67  A*11:01-B*18:01-C*07:04-DRB1*15:31-DQB1*06:01  Malaysia Peninsular Malay 0.0526951
 68  A*11:33-B*18:01-C*07:04-DRB1*15:02-DQB1*05:01  Malaysia Peninsular Malay 0.0526951
 69  A*24:02-B*18:01-C*07:04-DRB1*08:03-DQB1*06:01  Malaysia Peninsular Malay 0.0526951
 70  A*24:02-B*18:01-C*07:04-DRB1*14:04-DQB1*04:01  Malaysia Peninsular Malay 0.0526951
 71  A*24:02-B*18:01-C*07:04-DRB1*15:01-DQB1*06:01  Malaysia Peninsular Malay 0.0526951
 72  A*24:02-B*18:01-C*07:04-DRB1*16:02-DQB1*05:02  Malaysia Peninsular Malay 0.0526951
 73  A*24:07-B*18:01-C*07:04-DRB1*04:05-DQB1*05:03  Malaysia Peninsular Malay 0.0526951
 74  A*24:07-B*18:01-C*07:04-DRB1*12:01-DQB1*06:01  Malaysia Peninsular Malay 0.0526951
 75  A*24:07-B*18:01-C*07:04-DRB1*15:01-DQB1*04:02  Malaysia Peninsular Malay 0.0526951
 76  A*24:07-B*18:01-C*07:04-DRB1*15:01-DQB1*06:01  Malaysia Peninsular Malay 0.0526951
 77  A*24:07-B*18:01-C*07:04-DRB1*15:01-DQB1*06:02  Malaysia Peninsular Malay 0.0526951
 78  A*24:07-B*18:01-C*07:04-DRB1*15:02-DQB1*06:01  Malaysia Peninsular Malay 0.0526951
 79  A*24:07-B*18:01-C*07:04-DRB1*16:02-DQB1*05:02  Malaysia Peninsular Malay 0.0526951
 80  A*24:10-B*18:01-C*07:04-DRB1*15:02-DQB1*05:01  Malaysia Peninsular Malay 0.0526951
 81  A*24:27-B*18:01-C*07:04-DRB1*12:02-DQB1*05:02  Malaysia Peninsular Malay 0.0526951
 82  A*33:01-B*18:01-C*07:04-DRB1*04:05-DQB1*05:02  Malaysia Peninsular Malay 0.0526951
 83  A*33:01-B*18:01-C*07:04-DRB1*07:01-DQB1*02:02  Malaysia Peninsular Malay 0.0526951
 84  A*33:01-B*18:01-C*07:04-DRB1*08:03-DQB1*03:01  Malaysia Peninsular Malay 0.0526951
 85  A*34:01-B*18:01-C*07:04-DRB1*07:01-DQB1*05:01  Malaysia Peninsular Malay 0.0526951
 86  A*34:01-B*18:01-C*07:04-DRB1*15:02-DQB1*06:01  Malaysia Peninsular Malay 0.0526951
 87  A*68:01-B*18:01-C*07:04-DRB1*15:01-DQB1*05:02  Malaysia Peninsular Malay 0.0526951
 88  A*74:01-B*18:01-C*07:04-DRB1*12:01-DQB1*03:01  Malaysia Peninsular Malay 0.0526951
 89  A*74:01-B*18:01-C*07:04-DRB1*12:02-DQB1*03:01  Malaysia Peninsular Malay 0.0526951
 90  A*24:07-B*18:01-C*07:04-DRB1*04:05-DQB1*04:02  Malaysia Peninsular Malay 0.0525951
 91  A*30:02-B*18:01-C*07:04-DRB1*11:01-DQB1*06:02  USA Hispanic pop 2 0.04701,999
 92  A*11:01:01-B*18:01:01-C*07:04:01-DRB1*14:54:01-DPB1*03:01:01  Hong Kong Chinese HKBMDR HLA 11 loci 0.04675,266
 93  A*24:02-B*18:01-C*07:04-DRB1*11:01  Germany DKMS - Spain minority 0.04501,107
 94  A*30:02-B*18:01-C*07:04-DRB1*13:02  Germany DKMS - Spain minority 0.04501,107
 95  A*02:01-B*18:01-C*07:04-DRB1*12:02-DQB1*05:02  USA Asian pop 2 0.04401,772
 96  A*02:02-B*18:01-C*07:04-DRB1*10:01-DQB1*05:01  USA African American pop 4 0.04402,411
 97  A*02:05-B*18:01-C*07:04-DRB1*13:03-DQB1*02:01  USA African American pop 4 0.04402,411
 98  A*11:01-B*18:01-C*07:04-DRB1*15:02-DQB1*05:01  USA Asian pop 2 0.04401,772
 99  A*23:01-B*18:01-C*07:04-DRB1*01:01-DQB1*05:01  USA African American pop 4 0.04402,411
 100  A*24:02-B*18:01-C*07:04-DRB1*11:01-DQB1*06:02  USA African American pop 4 0.04402,411

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 161) 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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