Allele Frequencies in World Populations

HLA > Haplotype Frequency Search

Please specify your search by selecting options from boxes. Then, click "Search" to find HLA Haplotype frequencies that match your criteria. Remember at least one option must be selected.
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 800) records   Pages: 1 2 3 4 5 6 7 8 of 8  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  DRB1*13:02-DQA1*01:02:01-DQB1*06:09  South Korea pop 5 3.6000467
 2  DRB1*13:02-DQB1*06:09  Tunisia 3.5000100
 3  DRB1*13:02-DQA1*01:02-DQB1*06:09  Congo Kinshasa Bantu 3.400090
 4  B*58:01-DRB1*13:02-DQB1*06:09  South Korea pop 3 3.3000485
 5  DRB1*13:02-DQB1*06:09  Taiwan pop 2 3.2000364
 6  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  South Korea pop 3 3.0000485
 7  DRB1*13:02-DQA1*01:02-DQB1*06:09  Tunisia 3.0000100
 8  DRB1*13:02-DQB1*06:09  USA African American pop 4 2.92702,411
 9  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Korean 2.716577,584
 10  DRB1*13:02-DQB1*06:09  Mexico Oaxaca Zapotec 2.300090
 11  DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  South Korea pop 11 2.1000149
 12  DRB1*13:02-DQB1*06:09  USA Asian pop 2 1.85301,772
 13  DRB1*13:02-DQA1*01:02-DQB1*06:09  Cameroon Yaounde 1.600092
 14  A*29:02:01-B*15:03:01-C*02:10:01-DRB1*13:02:01-DQB1*06:09:01-DPA1*01:03:01-DPB1*105:01:01  Brazil Rio de Janeiro Black 1.470668
 15  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01-DPA1*02:01:01-DPB1*30:01:01  Brazil Rio de Janeiro Black 1.470668
 16  DRB1*13:02-DQB1*06:09-DPB1*17:01  Gambia pop 3 1.4131939
 17  DRB1*13:02:01-DQB1*06:09  China Inner Mongolia Autonomous Region Northeast 1.4110496
 18  DRB1*13:02-DQA1*01:02-DQB1*06:09  USA San Francisco Caucasian 1.4000220
 19  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  USA Asian pop 2 1.37701,772
 20  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  China Zhejiang Han 1.35381,734
 21  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Vietnamese 1.304843,540
 22  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Chinese 1.262599,672
 23  A*68:02-B*53:01-C*04:01-DRB1*13:02-DQA1*01:02-DQB1*06:09  Kosovo 1.2100124
 24  A*03:01-B*14:02:01-C*08:02-DRB1*13:02:01-DQB1*06:09  England North West 1.2000298
 25  DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  South Korea pop 2 1.2000207
 26  DRB1*13:02-DQB1*06:09-DPB1*01:01  Gambia pop 3 1.1690939
 27  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  India Kerala Malayalam speaking 1.1240356
 28  DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*05:01  South Korea pop 11 1.1000149
 29  DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*09:01  China Canton Han 1.1000264
 30  DRB1*13:02-DQB1*06:09  Vietnam Hanoi Kinh 1.0000103
 31  A*03:01-B*14:11-C*08:02-DRB1*13:02-DQB1*06:09  Colombia North Wiwa El Encanto 0.961552
 32  DRB1*13:02-DQA1*01:02-DQB1*06:09-DPA1*01:03-DPB1*02:01  China Zhejiang Han pop 2 0.8394833
 33  A*02:01-B*47:03-C*07:01-DRB1*13:02-DQB1*06:09-DPB1*03:01  Tanzania Maasai 0.7987336
 34  DRB1*13:02-DQB1*06:09-DPB1*02:01  Gambia pop 3 0.7906939
 35  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*03:01  Sri Lanka Colombo 0.7703714
 36  A*11:01-B*08:01-DRB1*13:02-DQB1*06:09  Chile Mapuche 0.770066
 37  A*31:01-B*58:01-DRB1*13:02-DQB1*06:09  Chile Mapuche 0.770066
 38  A*80:01-B*44:03-DRB1*13:02-DQB1*06:09  Chile Mapuche 0.770066
 39  DRB1*13:02-DQA1*01:02-DQB1*06:09  USA European American 0.71001,899
 40  DRB1*13:02-DQB1*06:09-DMB*01:02  Ecuadorean Amerindians 0.666775
 41  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Southeast Asian 0.658827,978
 42  DRB1*13:02-DQB1*06:09  USA Hispanic pop 2 0.64901,999
 43  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP South Asian Indian 0.6448185,391
 44  A*02:01-B*51:01-C*16:01-DRB1*13:02-DQB1*06:09-DPB1*04:01  Tanzania Maasai 0.6390336
 45  A*02:05:01-B*50:01:01-C*06:02:01-DRB1*13:02:01-DQB1*06:09:01-DPA1*02:01:01-DPB1*13:01:01  Brazil Rio de Janeiro Parda 0.5882170
 46  A*33:03:01-B*51:01:01-C*15:02:01-DRB1*13:02:01-DQB1*06:09:01-DPA1*01:03:01-DPB1*104:01:01  Brazil Rio de Janeiro Parda 0.5882170
 47  A*68:01:02-B*51:01:01-C*12:03:01-DRB1*13:02:01-DQB1*06:09:01-DPA1*01:03:01-DPB1*03:01:01  Brazil Rio de Janeiro Parda 0.5882170
 48  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India West UCBB 0.57935,829
 49  A*33:03:01-B*58:01:01-C*03:02:01-DRB1*13:02:01-DQB1*06:09:01  India Kerala Malayalam speaking 0.5620356
 50  A*30:02:01-B*53:01:01-C*04:01:01-DRB1*13:02:01-DQB1*06:09:01-DPB1*04:01:01  Saudi Arabia pop 6 (G) 0.547128,927
 51  A*03:01-B*14:02-C*08:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*05:01  USA San Diego 0.5210496
 52  DRB1*13:02-DQB1*06:09-DPB1*03:01  Gambia pop 3 0.5210939
 53  A*33:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Chinese 0.5155194
 54  A*01:01-B*81:01-C*18:01-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*01:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 55  A*23:01-B*57:02-C*07:01-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*34:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 56  A*29:02-B*15:03-C*02:10-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*01:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 57  A*32:01-B*07:02-C*07:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 58  A*32:01-B*15:31-C*04:07-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*39:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 59  A*66:01-B*58:02-C*06:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 60  A*68:02-B*15:31-C*04:07-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*39:01  Kenya, Nyanza Province, Luo tribe 0.5000100
 61  A*01:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01  Vietnam Kinh 0.4950101
 62  A*26:01:01-B*38:02:01-C*07:02:01-DRB1*13:02:01-DQB1*06:09:01  Vietnam Kinh 0.4950101
 63  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India South UCBB 0.490211,446
 64  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  Sri Lanka Colombo 0.4902714
 65  A*33:03-B*58:01-C*03:02-DRB1*13:02-DRB3*03:01-DQB1*06:09  USA NMDP Filipino 0.486850,614
 66  A*01:01-B*08:01-C*07:04-DRB1*13:02-DQB1*06:09-DPB1*02:01  Tanzania Maasai 0.4792336
 67  A*01:01-B*08:01-C*07:04-DRB1*13:02-DQB1*06:09-DPB1*03:01  Tanzania Maasai 0.4792336
 68  A*30:01:01-B*44:03:01-C*04:01:01-DRB1*13:02:01-DQB1*06:09:01  Costa Rica Central Valley Mestizo (G) 0.4525221
 69  A*02:01-B*15:03-C*02:02-E*01:01:01-F*01:01:01-G*01:01-DRB1*13:02:01-DQA1*01:02-DQB1*06:09  Portugal Azores Terceira Island 0.4386130
 70  A*02:01-B*58:01-C*03:04-E*01:03:02-F*01:03:01-G*01:01-DRB1*13:02-DQA1*01:02-DQB1*06:09  Portugal Azores Terceira Island 0.4386130
 71  A*24:02-B*15:01-C*03:03-E*01:01:01-F*01:01:01-G*01:04-DRB1*13:02:01-DQA1*01:02-DQB1*06:09  Portugal Azores Terceira Island 0.4386130
 72  A*02:01:01-B*15:18:01-C*07:04:01-DRB1*13:02:01-DQB1*06:09:01  India Kerala Malayalam speaking 0.4210356
 73  A*02:01:01-B*14:02:01-C*08:02:01-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
 74  A*33:03:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQA1*01:02:01-DQB1*06:09:01-DPA1*01:03:01-DPB1*02:01  Russian Federation Vologda Region 0.4202119
 75  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
 76  DRB1*13:02:01-DQB1*06:09-DPB1*05:01:01  China Inner Mongolia Autonomous Region Northeast 0.4120496
 77  DRB1*13:02-DQB1*06:09  Italy pop 5 0.4100975
 78  DRB1*13:02-DQB1*06:09  Cretan Islanders 0.4032124
 79  A*24:02-B*53:01-C*04:01-DRB1*13:02-DQA1*01:02-DQB1*06:09  Kosovo 0.4030124
 80  A*74:01-B*15:03-C*02:02-DRB1*13:02-DQB1*06:09  USA African American pop 4 0.37602,411
 81  A*33:01-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  Malaysia Peninsular Malay 0.3680951
 82  DRB1*13:02-DQB1*06:09-DPB1*131:01  Gambia pop 3 0.3628939
 83  DRB1*13:02-DQB1*06:09-DPB1*30:01  Gambia pop 3 0.3628939
 84  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India North UCBB 0.36155,849
 85  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India Central UCBB 0.35904,204
 86  A*30:01:01-B*15:10:01-C*03:04:02-DRB1*13:02:01-DQB1*06:09:01-DPB1*105:01:01  South African Black 0.3520142
 87  A*30:02:01-B*15:220-C*03:02:01-DRB1*13:02:01-DQB1*06:09:01-DPB1*584:01  South African Black 0.3520142
 88  A*30:02:01-B*42:02:01-C*17:01:01-DRB1*13:02:01-DQB1*06:09:01-DPB1*13:01:01  South African Black 0.3520142
 89  A*30:04:01-B*15:10:01-C*04:01:01-DRB1*13:02:01-DQB1*06:09:01-DPB1*02:01:19  South African Black 0.3520142
 90  A*36:01-B*44:03:02-C*07:06:01-DRB1*13:02:01-DQB1*06:09:01-DPB1*01:01:01  South African Black 0.3520142
 91  A*68:02:01-B*15:03:01-C*02:10:01-DRB1*13:02:01-DQB1*06:09:01-DPB1*105:01:01  South African Black 0.3520142
 92  A*74:01-B*15:03-C*02:10-DRB1*13:02-DQB1*06:09  Mexico Mexico City Mestizo population 0.3497143
 93  B*15:03-C*02:10-DRB1*13:02-DQB1*06:09  Mexico Mexico City Mestizo population 0.3497143
 94  DRB1*13:02-DQB1*06:09  Mexico Mexico City Mestizo population 0.3497143
 95  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09  India Tamil Nadu 0.33182,492
 96  DRB1*13:02:01-DQB1*06:09-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 0.3230496
 97  A*03:01-B*51:01-C*14:02-DRB1*13:02-DQB1*06:09-DPB1*02:01  Tanzania Maasai 0.3195336
 98  A*34:02-B*44:03-C*07:01-DRB1*13:02-DQB1*06:09-DPB1*105:01  Tanzania Maasai 0.3195336
 99  A*01:01:01-B*07:05:01-C*07:01:01-DRB1*13:02:01-DQB1*06:09:01-DPA1*02:01:01-DPB1*17:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405
 100  A*02:01:01-B*51:32-C*16:01:01-DRB1*13:02:01-DQB1*06:09:01-DPA1*01:03:01-DPB1*104:01:01  Brazil Barra Mansa Rio State Caucasian 0.3125405

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 800) records   Pages: 1 2 3 4 5 6 7 8 of 8  


   

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.

support@allelefrequencies.net

Valid XHTML 1.0 Transitional