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 41 (from 41) records   Pages: 1 of 1  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1  DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  South Korea pop 11 2.1000149
 2  DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  South Korea pop 2 1.2000207
 3  DRB1*13:02-DQA1*01:02-DQB1*06:09-DPA1*01:03-DPB1*02:01  China Zhejiang Han pop 2 0.8394833
 4  DRB1*13:02-DQB1*06:09-DPB1*02:01  Gambia pop 3 0.7906939
 5  A*24:02:01-B*15:03:01-C*02:10:01-DRB1*11:01:01-DQB1*06:09:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Parda 0.5882170
 6  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
 7  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
 8  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
 9  A*01:01-B*08:01-C*07:04-DRB1*13:02-DQB1*06:09-DPB1*02:01  Tanzania Maasai 0.4792336
 10  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
 11  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
 12  A*74:01:01-B*15:03:01-C*02:10:01-DRB1*13:01:01-DQB1*06:09:01-DPB1*02:01:19  South African Black 0.3520142
 13  DQA1*01:02-DQB1*06:09-DPA1*01:03-DPB1*02:01  Hong Kong Chinese HKBMDR. DQ and DP 0.34231,064
 14  DRB1*13:02:01-DQB1*06:09-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 0.3230496
 15  A*03:01-B*51:01-C*14:02-DRB1*13:02-DQB1*06:09-DPB1*02:01  Tanzania Maasai 0.3195336
 16  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
 17  A*30:01-B*15:03-C*02:10-DRB1*11:01-DQA1*05:05-DQB1*06:09-DPB1*02:01  South Africa Worcester 0.3000159
 18  A*68:02-B*42:01-C*17:01-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  South Africa Worcester 0.3000159
 19  A*68:02-B*58:02-C*06:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  South Africa Worcester 0.3000159
 20  DQB1*06:09-DPB1*02:01:02  China Inner Mongolia Autonomous Region Northeast 0.2690496
 21  A*33:03-B*35:01-C*04:01-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  USA San Diego 0.2600496
 22  A*23:01-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  Nicaragua Managua 0.2165339
 23  A*29:02-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  Nicaragua Managua 0.2165339
 24  A*31:01:02-B*39:01:01-C*12:03:01-DRB1*13:02:01-DQB1*06:09:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 25  A*68:01:01-B*58:01:01-C*03:02:02-DRB1*13:02:01-DQB1*06:09:01-DPA1*01:03:01-DPB1*02:01:02  Brazil Rio de Janeiro Caucasian 0.1946521
 26  A*33:01-B*39:11-C*16:01-DRB1*14:02-DQB1*06:09-DPB1*02:01  Panama 0.1900462
 27  A*33:01-B*52:01-C*15:05-DRB1*04:11-DQB1*06:09-DPB1*02:01  Panama 0.1900462
 28  A*03:01-B*58:01-C*07:136-DRB1*13:02-DQB1*06:09-DPB1*02:01  Tanzania Maasai 0.1597336
 29  A*24:02-B*53:01-C*07:328-DRB1*13:02-DQB1*06:09-DPB1*02:01  Tanzania Maasai 0.1597336
 30  A*34:02-B*40:12-C*04:04-DRB1*13:02-DQB1*06:09-DPB1*02:01  Tanzania Maasai 0.1597336
 31  A*74:01-B*15:03-C*02:10-DRB1*13:02-DQB1*06:09-DPB1*02:01  Tanzania Maasai 0.1597336
 32  A*74:01-B*44:03-C*04:01-DRB1*15:03-DQB1*06:09-DPB1*02:01  Tanzania Maasai 0.1597336
 33  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPA1*01:03-DPB1*02:01  Japan pop 17 0.13003,078
 34  A*24:17-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  Sri Lanka Colombo 0.0700714
 35  A*32:01-B*35:01-C*04:01-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  Sri Lanka Colombo 0.0700714
 36  A*33:03-B*40:01-C*03:04-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPB1*02:01  Sri Lanka Colombo 0.0700714
 37  A*33:03-B*44:02-C*05:01-DRB1*13:02-DQB1*06:09-DPB1*02:01  Russia Karelia 0.05651,075
 38  A*29:02-B*51:08-C*16:02-DRB1*13:02-DQB1*06:09-DPB1*02:01  Russia Karelia 0.05651,075
 39  A*02:01-B*52:01-C*12:02-DRB1*13:02-DQB1*06:09-DPB1*02:01  Russia Karelia 0.05631,075
 40  A*24:02-B*58:01-C*03:02-DRB1*13:02-DQA1*01:02-DQB1*06:09-DPA1*01:03-DPB1*02:01  Japan pop 17 0.03003,078
 41  A*33:03-B*58:01-C*03:02-DRB1*13:02-DQB1*06:09-DPB1*02:01  Germany DKMS - German donors 0.01173,456,066

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).




   

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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