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 1,001 to 1,100 (from 15,275) records   Pages: 11 12 13 14 15 16 17 18 19 20 of 153  

Line Haplotype Population Frequency (%) Sample Size Distribution¹
 1,001  A*24-B*40:02-DRB1*04-DQB1*03:02  Mexico Quintana Roo, Cancun 1.041748
 1,002  A*31-B*40:02-DRB1*04-DQB1*03:02  Mexico Quintana Roo, Cancun 1.041748
 1,003  A*02-B*40-C*15  Brazil Parana Japanese 1.0400192
 1,004  A*02-B*40-DRB1*04:07-DQB1*03:02  Colombia Wayu from Guajira Peninsula 1.040048
 1,005  A*02-B*40-DRB1*16:02-DQB1*03:01  Colombia Wayu from Guajira Peninsula 1.040048
 1,006  A*24-B*40-DRB1*09:01-DQB1*03:01  Colombia Wayu from Guajira Peninsula 1.040048
 1,007  A*24-B*40-DRB1*16:02-DQB1*03:01  Colombia Wayu from Guajira Peninsula 1.040048
 1,008  A*26-B*40-C*08  Brazil Parana Japanese 1.0400192
 1,009  A*29-B*40-DRB1*01:03-DQB1*05:01  Colombia Wayu from Guajira Peninsula 1.040048
 1,010  A*68-B*40-DRB1*04:07-DQB1*03:02  Colombia Wayu from Guajira Peninsula 1.040048
 1,011  A*24:02-B*40:01-C*04:01-DRB1*04:03-DRB4*01:01-DQB1*03:02  USA NMDP Filipino 1.031050,614
 1,012  A*02-B*40:02-DRB1*04-DQB1*03:02  Mexico Nayarit, Tepic 1.030997
 1,013  A*11:01-B*40:01-C*07:02-DRB1*14:01-DQB1*05:02  Malaysia Peninsular Chinese 1.0309194
 1,014  A*68-B*40:02-DRB1*04-DQB1*03:02  Mexico Puebla, Puebla city 1.02711,994
 1,015  A*02-B*40:02-DRB1*08-DQB1*04  Mexico Jalisco Rural 1.0239585
 1,016  A*11:01:01-B*40:01:02-C*07:02:01-DRB1*11:01:01-DQB1*03:01:01  China Zhejiang Han 1.01061,734
 1,017  A*02-B*40:02-DRB1*08-DQB1*04  Mexico Sonora, Hermosillo 1.010199
 1,018  A*02:01:01-B*40:02  Mexico Guadalajara Mestizo pop 2 1.0000103
 1,019  A*02:01:01-B*40:06:01-C*15:02:01  South African Indian population 1.000050
 1,020  A*02:01-B*40:01  Taiwan Rukai 1.000050
 1,021  A*02:01-B*40:01  Taiwan Puyuma 1.000050
 1,022  A*02:06:01-B*40:06:01-C*15:07  South African Indian population 1.000050
 1,023  A*02:07-B*40:02  Taiwan Siraya 1.000051
 1,024  A*02-B*40:02-DRB1*04-DQB1*03:02  Mexico Baja Californa, Mexicali 1.0000100
 1,025  A*02-B*40:02-DRB1*08-DQB1*04  Mexico Baja California Rural 1.000050
 1,026  A*02-B*40-C*03:03  South Korea pop 1 1.0000324
 1,027  A*02-B*40-C*07  Brazil Parana Japanese 1.0000192
 1,028  A*02-B*40-DRB1*04  Philippines National Capital Region 1.000051
 1,029  A*02-B*40-DRB1*04  Russia South Ural Bashkir 1.0000146
 1,030  A*02-B*40-DRB1*09  China Shaanxi Province Han 1.000010,000
 1,031  A*02-B*40-DRB1*15  Philippines National Capital Region 1.000051
 1,032  A*03:01:01-B*40:01:02-C*03:04:01  South African Mixed ancestry 1.000050
 1,033  A*11:01:01-B*40:01:02-C*03:04:01  South African Indian population 1.000050
 1,034  A*11:01:01-B*40:01:02-C*07:04:01  South African Mixed ancestry 1.000050
 1,035  A*11:01-B*40:02  Philippines Ivatan 1.000050
 1,036  A*11:02-B*40:02  Philippines Ivatan 1.000050
 1,037  A*11-B*40-DRB1*04  Philippines National Capital Region 1.000051
 1,038  A*11-B*40-DRB1*09  China Shaanxi Province Han 1.000010,000
 1,039  A*23:01:01-B*40:02:01-C*04:01:01  South African Mixed ancestry 1.000050
 1,040  A*23:01:01-B*40:02:01-C*07:04:01  South African Mixed ancestry 1.000050
 1,041  A*24:02:01-B*40:01:01-DRB1*13:01:01  Portugal South 1.000049
 1,042  A*24:02:01-B*40:01:02-C*03:04:01  South African Mixed ancestry 1.000050
 1,043  A*24:02:01-B*40:06:01-C*01:02:01  South African Indian population 1.000050
 1,044  A*24:02-B*40:01  USA Alaska Yupik 1.0000252
 1,045  A*24:02-B*40:02-C*02:02-DRB1*11:01-DQB1*03:01  Poland 1.0000200
 1,046  A*24:02-B*40:02-C*03:04-DRB1*04:11-DQA1*03:01-DQB1*03:02  Brazil Puyanawa 1.0000150
 1,047  A*24:02-B*40:02-DRB1*04:01  Sweden Northern Sami 1.0000154
 1,048  A*24:02-B*40:06-C*08:01-DRB1*09:01-DQB1*03:03  South Korea pop 3 1.0000485
 1,049  A*24:02-B*40:06-C*08:01-DRB1*09:01-DQB1*03:03-DPB1*05:01  Japan Central 1.0000371
 1,050  A*24:02-B*40:06-DRB1*09:01  South Korea pop 3 1.0000485
 1,051  A*24:07-B*40:06:01-C*15:02:01  South African Indian population 1.000050
 1,052  A*24-B*40:02-DRB1*11-DQB1*03:01  Mexico Baja California Rural 1.000050
 1,053  A*24-B*40-C*03:04  South Korea pop 1 1.0000324
 1,054  A*24-B*40-C*03:04-DRB1*08:02-DQB1*04  Russia Transbaikal Territory Buryats 1.0000150
 1,055  A*24-B*40-DRB1*08  Philippines National Capital Region 1.000051
 1,056  A*26:01-B*40:01:01-DRB1*03:01:01  Portugal Center 1.000050
 1,057  A*26:01-B*40:02  Taiwan Puyuma 1.000050
 1,058  A*26-B*40-C*15:02-DRB1*12:01-DQB1*03  Russia Transbaikal Territory Buryats 1.0000150
 1,059  A*30:02:01-B*40:01:02-C*12:03:01  South African Mixed ancestry 1.000050
 1,060  A*31:01:02-B*40:01:01-DRB1*03:01:01  Portugal Center 1.000050
 1,061  A*31:01:02-B*40:01-C*03:04  Ireland South 1.0000250
 1,062  A*31:01:02-B*40:06:01-C*06:02:01  South African Indian population 1.000050
 1,063  A*31-B*40:02-DRB1*08-DQB1*04  Mexico Quintana Roo Rural 1.000050
 1,064  A*32-B*40:02-DRB1*15-DQB1*06  Mexico Baja Californa, Mexicali 1.0000100
 1,065  A*32-B*40-C*02  Italy East Sicily 1.000050
 1,066  A*32-B*40-C*02-DRB1*16-DQB1*05  Albania 1.0000160
 1,067  A*33-B*40-DRB1*14  Philippines National Capital Region 1.000051
 1,068  A*33-B*40-DRB1*15  Philippines National Capital Region 1.000051
 1,069  A*34:01-B*40:01  Philippines Ivatan 1.000050
 1,070  A*68:01:02-B*40:06:01-C*07:04:01  South African Indian population 1.000050
 1,071  A*68:02-B*40:02-DRB1*13:03  Portugal Center 1.000050
 1,072  A*68-B*40:02-DRB1*04-DQB1*03:02  Mexico Coahuila, Torreon 1.0000396
 1,073  A*68-B*40:02-DRB1*04-DQB1*04  Mexico Quintana Roo Rural 1.000050
 1,074  A*68-B*40:02-DRB1*08-DQB1*04  Mexico Quintana Roo Rural 1.000050
 1,075  B*40:01-C*01:02  Taiwan Rukai 1.000050
 1,076  B*40:01-C*03:04-DRB1*04:04-DQB1*03:02  Ireland South 1.0000250
 1,077  B*40:01-C*04:01  Taiwan Tao 1.000050
 1,078  B*40:01-C*07:02  Taiwan Rukai 1.000050
 1,079  B*40:01-DRB1*04:05:01  Philippines Ivatan 1.000050
 1,080  B*40:01-DRB1*09:01:02  Philippines Ivatan 1.000050
 1,081  B*40:01-DRB1*11:01:01  Philippines Ivatan 1.000050
 1,082  B*40:01-DRB1*12:02:01  Taiwan Pazeh 1.000055
 1,083  B*40:01-DRB1*12:02:01  Taiwan Taroko 1.000055
 1,084  B*40:01-DRB1*15:01:01  Taiwan Tao 1.000050
 1,085  B*40:01-DRB1*15:02:01  Philippines Ivatan 1.000050
 1,086  B*40:02-C*03:04:01  Philippines Ivatan 1.000050
 1,087  B*40:02-C*07:02  Philippines Ivatan 1.000050
 1,088  B*40:02-DRB1*09:01:02  Taiwan Siraya 1.000051
 1,089  B*40:02-DRB1*11:01:01  Philippines Ivatan 1.000050
 1,090  B*40:02-DRB1*14:01  Taiwan Rukai 1.000050
 1,091  B*40:02-DRB1*14:05  Philippines Ivatan 1.000050
 1,092  B*40:02-DRB1*15:01:01  Taiwan Rukai 1.000050
 1,093  B*40:02-DRB1*15:02:01  Taiwan Tao 1.000050
 1,094  A*02:11-B*40:06-C*15:02-DRB1*15:01-DQB1*06:01  India South UCBB 0.998611,446
 1,095  A*02-B*40:05-DRB1*04-DQB1*03:02  Mexico Mexico City North 0.9960751
 1,096  A*02:01-B*40:01-C*03:04-DRB1*13:02  Germany DKMS - United Kingdom minority 0.99201,043
 1,097  A*11:01:01-B*40:01:02-C*03:04:01  China Jingpo Minority 0.9900105
 1,098  A*31:01:02-B*40:06:01  China Jingpo Minority 0.9900105
 1,099  A*68:01:02-B*40:06:01-C*15:02:01  China Jingpo Minority 0.9900105
 1,100  A*68-B*40:02-DRB1*08-DQB1*04  Mexico Mexico City Metropolitan Area Rural 0.9868150

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 1,001 to 1,100 (from 15,275) records   Pages: 11 12 13 14 15 16 17 18 19 20 of 153  


   

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