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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 |
24,001 |
A*34 | | Cameroon Uldeme | | 0 | | 35 | See | | | |
24,002 |
A*34 | | China Guangdong Province | 0.0 | 0 | | 403 | See | | | |
24,003 |
A*34 | | China Jiangsu Province | | 0 | | 20,248 | See | | | |
24,004 |
A*34 | | China North Han | | 0 | | 105 | See | | | |
24,005 |
A*34 | | China Shaanxi Province Han | | 0.0020 | | 10,000 | See | | | |
24,006 |
A*34 | | China Shandong Province | 0.1 | 0 | | 7,418 | See | | | |
24,007 |
A*34 | | China Shanghai | | 0.0005 | | 26,266 | See | | | |
24,008 |
A*34 | | China Yunnan Province Han pop 2 | | 0.0740 | | 129 | See | | | |
24,009 |
A*34 | | China Yunnan Province Naxi | | 0 | | 118 | See | | | |
24,010 |
A*34 | | Colombia Barranquilla | | 0.0215 | | 188 | See | | |
|
24,011 |
A*34 | | Croatia | | 0 | | 150 | See | | | |
24,012 |
A*34 | | Croatia pop 2 | | 0 | | 100 | See | | | |
24,013 |
A*34 | | Cuba Mixed | | 0.0080 | | 78 | See | | | |
24,014 |
A*34 | | Cuba Mixed pop 2 | | 0.0150 | | 189 | See | | | |
24,015 |
A*34 | | Cuba Mixed Race | 4.8 | 0.0240 | | 42 | See | | | |
24,016 |
A*34 | | Czech Republic Kurd | 1.4 | 0.0068 | | 74 | See | | | |
24,017 |
A*34 | | Ecuador Amazonia Mixed Ancestry | | 0.0128 | | 39 | See | | |
|
24,018 |
A*34 | | Ecuador Andes Mixed Ancestry | | 0.0018 | | 824 | See | | |
|
24,019 |
A*34 | | Ecuador Coast Mixed Ancestry | | 0.0021 | | 238 | See | | |
|
24,020 |
A*34 | | Ecuador Mixed Ancestry | | 0.0021 | | 1,173 | See | | |
|
24,021 |
A*34 | | England Leeds | 0.2 | 0.0010 | | 5,024 | See | | | |
24,022 |
A*34 | | England Liverpool | 0.2 | 0.0010 | | 1,343 | See | | | |
24,023 |
A*34 | | England Newcastle | 0.2 | 0.0010 | | 2,739 | See | | | |
24,024 |
A*34 | | England Sheffield | 0.1 | 0.0005 | | 4,755 | See | | | |
24,025 |
A*34 | | France Bordeaux | 0.1 | 0.0005 | | 990 | See | | | |
24,026 |
A*34 | | France Corsica Island | | 0.0100 | | 100 | See | | | |
24,027 |
A*34 | | France Grenoble | 0.2 | 0.0011 | | 1,000 | See | | | |
24,028 |
A*34 | | France Grenoble, Nantes and Rennes | | 0.0010 | | 6,094 | See | | | |
24,029 |
A*34 | | France Lyon | 0.3 | 0.0017 | | 4,813 | See | | | |
24,030 |
A*34 | | France Marseille | 0.5 | 0.0027 | | 1,000 | See | | | |
24,031 |
A*34 | | France Rennes pop 4 | 0.1 | 0.0005 | | 1,000 | See | | | |
24,032 |
A*34 | | France Southeast | 0.8 | 0.0040 | | 130 | See | | | |
24,033 |
A*34 | | Germany | 0.2 | 0.0010 | | 11,407 | See | | | |
24,034 |
A*34 | | Ghana Accre Asutuare Akan | | 0.0220 | | 429 | See | | | |
24,035 |
A*34 | | Greece North | | 0 | | 500 | See | | | |
24,036 |
A*34 | | Greece pop 7 | | 0.0006 | | 11,250 | See | | | |
24,037 |
A*34 | | Guatemala, Guatemala City Mixed Ancestry | 1.6 | 0.0079 | | 127 | See | | |
|
24,038 |
A*34 | | India Jalpaiguri Toto | 5.0 | 0.0253 | | 40 | See | | | |
24,039 |
A*34 | | India North pop 3 | | 0.0009 | | 587 | See | | | |
24,040 |
A*34 | | Iran Royan Cord Blood Bank | 0.1 | 0.0010 | | 15,600 | See | | | |
24,041 |
A*34 | | Iraq Arabs | 2.0 | 0.0101 | | 149 | See | | |
|
24,042 |
A*34 | | Ireland South pop 2 | | 0.0003 | | 17,624 | See | | | |
24,043 |
A*34 | | Israel Ashkenazi Jews pop 2 | | 0 | | 132 | See | | | |
24,044 |
A*34 | | Israel Jews pop 2 | 0.2 | 0.0880 | | 23,000 | See | | | |
24,045 |
A*34 | | Israel Moroccan Jews | | 0.0040 | | 113 | See | | | |
24,046 |
A*34 | | Italy | | 0.0010 | | 159,311 | See | | | |
24,047 |
A*34 | | Italy Bergamo | 0.0 | 0 | | 101 | See | | | |
24,048 |
A*34 | | Italy Lombardy | 0.2 | 0.0010 | | 674 | See | | |
|
24,049 |
A*34 | | Italy North Pavia pop 2 | 0.2 | 0.0010 | | 2,416 | See | | | |
24,050 |
A*34 | | Italy North Pavia pop 3 | | 0.0050 | | 685 | See | | | |
24,051 |
A*34 | | Italy North pop 3 | 0.0 | 0 | | 97 | See | | | |
24,052 |
A*34 | | Italy Rome | 0.0 | 0 | | 100 | See | | | |
24,053 |
A*34 | | Italy Sardinia pop3 | | 0 | | 100 | See | | | |
24,054 |
A*34 | | Italy South Campania Region | 0.2 | 0.0010 | | 1,089 | See | | | |
24,055 |
A*34 | | Jordan | | 0.0030 | | 15,141 | See | | | |
24,056 |
A*34 | | Macedonia pop 4 | | 0 | | 216 | See | | | |
24,057 |
A*34 | | Madeira pop 2 | | 0.0090 | | 173 | See | | | |
24,058 |
A*34 | | Madeira pop 3 | | 0.0070 | | 538 | See | | | |
24,059 |
A*34 | | Malaysia Negeri Sembilan Minangkabau | | 0.0100 | | 34 | See | | | |
24,060 |
A*34 | | Malaysia Perak and Johor Banjar Bugis Jawa | | 0.0590 | | 94 | See | | | |
24,061 |
A*34 | | Malaysia Perak Rawa | | 0.0900 | | 23 | See | | | |
24,062 |
A*34 | | Malaysia pop 2 | | 0.0570 | | 62 | See | | | |
24,063 |
A*34 | | Malaysia pop 3 | | 0.0590 | | 1,445 | See | | | |
24,064 |
A*34 | | Malaysia Sabah Kadazan | | 0.2460 | | 57 | See | | | |
24,065 |
A*34 | | Malaysia Sarawak Bidayuh | | 0.1400 | | 50 | See | | | |
24,066 |
A*34 | | Malaysia Sarawak Iban | | 0.1570 | | 51 | See | | | |
24,067 |
A*34 | | Mexico Aguascalientes state | | 0.0053 | | 95 | See | | | |
24,068 |
A*34 | | Mexico Baja Californa, Mexicali | | 0 | | 100 | See | | |
|
24,069 |
A*34 | | Mexico Baja California Rural | | 0 | | 50 | See | | |
|
24,070 |
A*34 | | Mexico Baja California, La Paz | | 0.0200 | | 75 | See | | |
|
24,071 |
A*34 | | Mexico Baja California, Tijuana | | 0 | | 25 | See | | |
|
24,072 |
A*34 | | Mexico Campeche Rural | | 0 | | 47 | See | | |
|
24,073 |
A*34 | | Mexico Campeche, Campeche city | | 0 | | 34 | See | | |
|
24,074 |
A*34 | | Mexico Chiapas Rural | | 0.0041 | | 121 | See | | |
|
24,075 |
A*34 | | Mexico Chiapas, Tuxtla Gutierrez | | 0 | | 52 | See | | |
|
24,076 |
A*34 | | Mexico Chihuahua Chihuahua City | | 0 | | 119 | See | | |
|
24,077 |
A*34 | | Mexico Chihuahua Rural | | 0.0042 | | 236 | See | | |
|
24,078 |
A*34 | | Mexico Chihuahua, Ciudad Juarez | | 0.0046 | | 106 | See | | |
|
24,079 |
A*34 | | Mexico Coahuila Rural | | 0 | | 216 | See | | |
|
24,080 |
A*34 | | Mexico Coahuila, Saltillo | | 0.0137 | | 72 | See | | |
|
24,081 |
A*34 | | Mexico Coahuila, Torreon | | 0.0063 | | 396 | See | | |
|
24,082 |
A*34 | | Mexico Colima Rural | | 0 | | 43 | See | | |
|
24,083 |
A*34 | | Mexico Colima, Colima city | | 0 | | 61 | See | | |
|
24,084 |
A*34 | | Mexico Durango Rural | | 0.0031 | | 326 | See | | |
|
24,085 |
A*34 | | Mexico Durango, Durango city | | 0.0032 | | 153 | See | | |
|
24,086 |
A*34 | | Mexico Guanajuato Rural | | 0.0031 | | 162 | See | | |
|
24,087 |
A*34 | | Mexico Guanajuato, Guanajuato city | | 0 | | 22 | See | | |
|
24,088 |
A*34 | | Mexico Guanajuato, Leon | | 0 | | 78 | See | | |
|
24,089 |
A*34 | | Mexico Guerrero state | | 0.0035 | | 144 | See | | |
|
24,090 |
A*34 | | Mexico Hidalgo Rural | | 0 | | 81 | See | | |
|
24,091 |
A*34 | | Mexico Hidalgo, Pachuca | | 0 | | 41 | See | | |
|
24,092 |
A*34 | | Mexico Huasteca Region Teenek | | 0 | | 55 | See | | | |
24,093 |
A*34 | | Mexico Jalisco Rural | | 0.0043 | | 585 | See | | |
|
24,094 |
A*34 | | Mexico Jalisco, Guadalajara city | | 0.0021 | | 1,189 | See | | |
|
24,095 |
A*34 | | Mexico Jalisco, Tlajomulco | | 0.0333 | | 30 | See | | |
|
24,096 |
A*34 | | Mexico Jalisco, Tlaquepaque | | 0 | | 39 | See | | |
|
24,097 |
A*34 | | Mexico Jalisco, Tonala | | 0 | | 35 | See | | |
|
24,098 |
A*34 | | Mexico Jalisco, Zapopan | | 0.0030 | | 168 | See | | |
|
24,099 |
A*34 | | Mexico Mestizo | 0.0 | 0 | | 41 | See | | | |
24,100 |
A*34 | | Mexico Mestizo pop 4 | | 0.0037 | | 269 | 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.