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Line |
Allele |
Population |
% of individuals
that have the allele |
Allele
Frequency
(in_decimals) |
Sample
Size |
IMGT/HLA¹
Database |
Distribution² |
Haplotype³
Association |
Notesª |
1,001 |
A*02:02 | | Israel Ashkenazi and Non Ashkenazi Jews | | 0.0090 | | 146 | See | | | |
1,002 |
A*02:02 | | Italy North pop 3 | 0.0 | 0 | | 97 | See | | | |
1,003 |
A*02:02 | | Kenya | | 0.0490 | | 144 | See | | | |
1,004 |
A*02:02 | | Kenya Luo | | 0.0300 | | 265 | See | | | |
1,005 |
A*02:02 | | Kenya Nandi | | 0.0660 | | 240 | See | | | |
1,006 |
A*02:02 | | Libya Cyrenaica | | 0.0170 | | 118 | See | | | |
1,007 |
A*02:02 | | Madeira | | 0.0080 | | 185 | See | | | |
1,008 |
A*02:02 | | Mali Bandiagara | | 0.0760 | | 138 | See | | | |
1,009 |
A*02:02 | | Mexico Guadalajara Mestizo pop 2 | | 0.0050 | | 103 | See | | | |
1,010 |
A*02:02 | | Mexico Mestizo | 0.0 | 0 | | 41 | See | | | |
1,011 |
A*02:02 | | Mexico Mexico City Mestizo pop 2 | | 0.0021 | | 234 | See | | | |
1,012 |
A*02:02 | | Morocco Atlantic Coast Chaouya | | 0.0070 | | 98 | See | | | |
1,013 |
A*02:02 | | Morocco Nador Metalsa pop 2 | | 0 | | 73 | See | | | |
1,014 |
A*02:02 | | Morocco Settat Chaouya | 1.4 | 0.0070 | | 98 | See | | | |
1,015 |
A*02:02 | | Nicaragua Mestizo (G) | 0.6 (*) | 0.0030 (*) | | 155 | See | | |
|
1,016 |
A*02:02 | | Pakistan Baloch | | 0 | | 66 | See | | | |
1,017 |
A*02:02 | | Pakistan Brahui | | 0.0230 | | 104 | See | | | |
1,018 |
A*02:02 | | Pakistan Karachi Parsi | | 0.0170 | | 91 | See | | | |
1,019 |
A*02:02 | | Philippines Ivatan | 0.0 | 0 | | 50 | See | | | |
1,020 |
A*02:02 | | Portugal Center | | 0 | | 50 | See | | | |
1,021 |
A*02:02 | | Portugal North | | 0.0110 | | 46 | See | | | |
1,022 |
A*02:02 | | Portugal South | | 0 | | 49 | See | | | |
1,023 |
A*02:02 | | Romania | 0.9 | 0.0040 | | 348 | See | | | |
1,024 |
A*02:02 | | Sao Tome Island Angolar | | 0.0630 | | 32 | See | | | |
1,025 |
A*02:02 | | Sao Tome Island Forro | | 0.0450 | | 66 | See | | | |
1,026 |
A*02:02 | | Saudi Arabia Guraiat and Hail | 4.2 | 0.0240 | | 213 | See | | | |
1,027 |
A*02:02 | | Saudi Arabia pop 5 | 2.5 | 0.0158 | | 158 | See | | | |
1,028 |
A*02:02 | | Scotland Orkney | 0.0 | 0 | | 99 | See | | | |
1,029 |
A*02:02 | | Senegal Niokholo Mandenka | | 0.0910 | | 165 | See | | | |
1,030 |
A*02:02 | | South Africa Caucasians | | 0.0100 | | 102 | See | | | |
1,031 |
A*02:02 | | South Africa Natal Zulu | 7.0 | 0.0350 | | 100 | See | | | |
1,032 |
A*02:02 | | South Korea pop 3 | | 0 | | 485 | See | | | |
1,033 |
A*02:02 | | Sudan Central Shaigiya Mixed | 2.7 | 0.0135 | | 36 | See | | | |
1,034 |
A*02:02 | | Taiwan Ami | 0.0 | 0 | | 98 | See | | | |
1,035 |
A*02:02 | | Taiwan Atayal | 0.0 | 0 | | 106 | See | | | |
1,036 |
A*02:02 | | Taiwan Bunun | 0.0 | 0 | | 101 | See | | | |
1,037 |
A*02:02 | | Taiwan Hakka | 0.0 | 0 | | 55 | See | | | |
1,038 |
A*02:02 | | Taiwan Minnan pop 1 | 0.0 | 0 | | 102 | See | | | |
1,039 |
A*02:02 | | Taiwan Paiwan | 0.0 | 0 | | 51 | See | | | |
1,040 |
A*02:02 | | Taiwan Pazeh | 0.0 | 0 | | 55 | See | | | |
1,041 |
A*02:02 | | Taiwan Puyuma | 0.0 | 0 | | 50 | See | | | |
1,042 |
A*02:02 | | Taiwan Rukai | 0.0 | 0 | | 50 | See | | | |
1,043 |
A*02:02 | | Taiwan Saisiat | 0.0 | 0 | | 51 | See | | | |
1,044 |
A*02:02 | | Taiwan Siraya | 0.0 | 0 | | 51 | See | | | |
1,045 |
A*02:02 | | Taiwan Tao | 0.0 | 0 | | 50 | See | | | |
1,046 |
A*02:02 | | Taiwan Taroko | 0.0 | 0 | | 55 | See | | | |
1,047 |
A*02:02 | | Taiwan Thao | 0.0 | 0 | | 30 | See | | | |
1,048 |
A*02:02 | | Taiwan Tsou | 0.0 | 0 | | 51 | See | | | |
1,049 |
A*02:02 | | Tunisia | 2.0 | 0.0100 | | 100 | See | | | |
1,050 |
A*02:02 | | Turkey pop 5 | | 0 | | 142 | See | | | |
1,051 |
A*02:02 | | Uganda Kampala | | 0.0340 | | 161 | See | | | |
1,052 |
A*02:02 | | Uganda Kampala pop 2 | | 0.0370 | | 175 | See | | | |
1,053 |
A*02:02 | | USA Alaska Yupik | | 0 | | 252 | See | | | |
1,054 |
A*02:02 | | USA Caucasian pop 4 | | 0.0009 | | 1,070 | See | | | |
1,055 |
A*02:02 | | USA Philadelphia Caucasian | 0.0 | 0 | | 141 | See | | | |
1,056 |
A*02:02 | | USA San Antonio Caucasian | | 0 | | 222 | See | | | |
1,057 |
A*02:02 | | USA South Dakota Lakota Sioux | | 0.0020 | | 302 | See | | | |
1,058 |
A*02:02 | | USA South Texas Hispanic | | 0 | | 194 | See | | | |
1,059 |
A*02:02 | | Zambia Lusaka | | 0.0230 | | 44 | See | | | |
1,060 |
A*02:02 | | Zimbabwe Harare Shona | | 0.0360 | | 230 | See | | | |
1,061 |
A*02:02:01 | | Spain, Canary Islands, Gran canaria island | 1.4 | 0.0069 | | 215 | See | | |
|
1,062 |
A*02:03 | | Australia New South Wales Caucasian | | 0 | | 134 | See | | | |
1,063 |
A*02:03 | | Australia Yuendumu Aborigine | | 0 | | 191 | See | | | |
1,064 |
A*02:03 | | Brazil Belo Horizonte Caucasian | 0.0 | 0 | | 95 | See | | | |
1,065 |
A*02:03 | | Bulgaria | | 0 | | 55 | See | | | |
1,066 |
A*02:03 | | Burkina Faso Fulani | | 0 | | 49 | See | | | |
1,067 |
A*02:03 | | Burkina Faso Rimaibe | | 0.0110 | | 47 | See | | | |
1,068 |
A*02:03 | | China Beijing | | 0.0080 | | 67 | See | | | |
1,069 |
A*02:03 | | China Beijing Shijiazhuang Tianjian Han | | 0.0240 | | 618 | See | | | |
1,070 |
A*02:03 | | China Canton Han | | 0.1120 | | 264 | See | | | |
1,071 |
A*02:03 | | China Guangdong Province Meizhou Han | | 0.0100 | | 100 | See | | | |
1,072 |
A*02:03 | | China Guangxi Region Maonan | | 0.1760 | | 108 | See | | | |
1,073 |
A*02:03 | | China Guangzhou | | 0.0980 | | 102 | See | | | |
1,074 |
A*02:03 | | China Jiangsu Province Han | | 0.0279 | | 334 | See | | | |
1,075 |
A*02:03 | | China North Han | | 0.0240 | | 105 | See | | | |
1,076 |
A*02:03 | | China South Han | | 0.1080 | | 284 | See | | | |
1,077 |
A*02:03 | | China Southwest Dai | | 0.1090 | | 124 | See | | | |
1,078 |
A*02:03 | | China Tibet Region Tibetan | | 0 | | 158 | See | | | |
1,079 |
A*02:03 | | China Yunnan Bulang | | 0.0820 | | 116 | See | | | |
1,080 |
A*02:03 | | China Yunnan Hani | | 0.0430 | | 150 | See | | | |
1,081 |
A*02:03 | | China Yunnan Province Han | | 0.0050 | | 101 | See | | | |
1,082 |
A*02:03 | | Croatia | | 0 | | 150 | See | | | |
1,083 |
A*02:03 | | Czech Republic | | 0 | | 106 | See | | | |
1,084 |
A*02:03 | | India Delhi pop 2 | 1.1 | 0.0050 | | 90 | See | | | |
1,085 |
A*02:03 | | India Khandesh Region Pawra | | 0.0500 | | 50 | See | | | |
1,086 |
A*02:03 | | India Mumbai Maratha | | 0.0370 | | 91 | See | | | |
1,087 |
A*02:03 | | India West Bhil | | 0.0500 | | 50 | See | | | |
1,088 |
A*02:03 | | India West Coast Parsi | | 0 | | 50 | See | | | |
1,089 |
A*02:03 | | Italy North pop 3 | 0.0 | 0 | | 97 | See | | | |
1,090 |
A*02:03 | | Japan pop 16 | | 0.0006 | | 18,604 | See | | | |
1,091 |
A*02:03 | | Japan pop 3 | | 0.0010 | | 1,018 | See | | | |
1,092 |
A*02:03 | | Malaysia Champa | 13.8 | 0.0690 | | 29 | See | | |
|
1,093 |
A*02:03 | | Malaysia Jelebu Temuan | | 0.0210 | | 25 | See | | | |
1,094 |
A*02:03 | | Malaysia Kedah Baling Kensiu | | 0.0200 | | 25 | See | | | |
1,095 |
A*02:03 | | Malaysia Kedah Kensiu | 9.5 | 0.0480 | | 21 | See | | |
|
1,096 |
A*02:03 | | Malaysia Kelantan | 3.6 | 0.0180 | | 28 | See | | |
|
1,097 |
A*02:03 | | Malaysia Mandailing | 18.5 | 0.0930 | | 27 | See | | |
|
1,098 |
A*02:03 | | Malaysia Pahang Semai | 23.7 | 0.1180 | | 38 | See | | |
|
1,099 |
A*02:03 | | Malaysia Patani | 16.0 | 0.0800 | | 25 | See | | |
|
1,100 |
A*02:03 | | Malaysia Perak Grik Jehai | | 0.0400 | | 25 | See | | | |
Notes:
* Allele Frequency: Total number of copies of the allele in the population sample (Alleles / 2n) in decimal format.
Important: This field has been expanded to four decimals to better represent frequencies of large datasets (e.g. where sample size > 1000 individuals)
* % of individuals that have the allele: Percentage of individuals who have the allele in the population (Individuals / n).
* Allele Frequencies shown in
green were calculated from Phenotype Frequencies assuming Hardy-Weinberg proportions.
AF = 1-square_root(1-PF)
PF = 1-(1-AF)
2
AF = Allele Frequency; PF = Phenotype Frequency, i.e. (%) of the individuals carrying the allele.
* Allele Frequencies marked with (*) were calculated from all alleles in the corresponding
G group.
¹ IMGT/HLA Database - For more details of the allele.
² Distribution - Graphical distribution of the allele.
³ Haplotype Association - Find HLA haplotypes with this allele.
ª Notes - See notes for ambiguous combinations of alleles.
Displaying 1,001 to 1,100
(from 64,836) records |
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