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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 |
60,001 |
DRB1*16 | | China Jiangsu Province | | 0.0150 | | 20,248 | See | | | |
60,002 |
DRB1*16 | | China Shaanxi Province Han | | 0.0240 | | 10,000 | See | | | |
60,003 |
DRB1*16 | | China Shandong Province Linqu County | 5.0 | 0.0253 | | 139 | See | | | |
60,004 |
DRB1*16 | | Colombia Northwest Tule | | 0.1550 | | 29 | See | | | |
60,005 |
DRB1*16 | | Croatia Gorski Kotar Region | | 0.0390 | | 63 | See | | | |
60,006 |
DRB1*16 | | Cuba Mixed pop 2 | | 0.0210 | | 189 | See | | | |
60,007 |
DRB1*16 | | England | 2.4 | 0.0120 | | 537 | See | | | |
60,008 |
DRB1*16 | | France Grenoble, Nantes and Rennes | | 0.0270 | | 6,094 | See | | | |
60,009 |
DRB1*16 | | France West Breton | | 0.0030 | | 150 | See | | | |
60,010 |
DRB1*16 | | Greece pop 5 | | 0.1310 | | 500 | See | | | |
60,011 |
DRB1*16 | | Greece pop 7 | | 0.1337 | | 11,250 | See | | | |
60,012 |
DRB1*16 | | India Andhra Pradesh Brahmin | 0.0 | 0 | | 98 | See | | | |
60,013 |
DRB1*16 | | India Andhra Pradesh Sunni | 0.8 | 0.0150 | | 100 | See | | | |
60,014 |
DRB1*16 | | India Uttar Pradesh | | 0.0050 | | 202 | See | | | |
60,015 |
DRB1*16 | | Iran | | 0.0430 | | 58 | See | | | |
60,016 |
DRB1*16 | | Iran Royan Cord Blood Bank | 7.3 | 0.0370 | | 15,600 | See | | | |
60,017 |
DRB1*16 | | Ireland Donegal | 0.5 | 0.0030 | | 200 | See | | | |
60,018 |
DRB1*16 | | Ireland Wexford | 1.5 | 0.0080 | | 200 | See | | | |
60,019 |
DRB1*16 | | Italy Central | | 0.0220 | | 380 | See | | | |
60,020 |
DRB1*16 | | Italy North Pavia pop 2 | 13.9 | 0.0680 | | 2,416 | See | | | |
60,021 |
DRB1*16 | | Italy North pop 2 | 4.6 | 0.0240 | | 2,054 | See | | | |
60,022 |
DRB1*16 | | Italy pop 2 | | 0.0470 | | 53 | See | | | |
60,023 |
DRB1*16 | | Italy pop 4 | 8.8 | 0.0450 | | 4,575 | See | | | |
60,024 |
DRB1*16 | | Jamaica | | 0.0340 | | 132 | See | | | |
60,025 |
DRB1*16 | | Japan pop 10 | | 0.0030 | | 332 | See | | | |
60,026 |
DRB1*16 | | Jordan | | 0.0080 | | 15,141 | See | | | |
60,027 |
DRB1*16 | | Malaysia pop 3 | | 0.0370 | | 1,445 | See | | | |
60,028 |
DRB1*16 | | Mexico Guadalajara Mestizo | | 0.0090 | | 54 | See | | | |
60,029 |
DRB1*16 | | Mexico Mestizo pop 4 | | 0.0539 | | 269 | See | | | |
60,030 |
DRB1*16 | | Mexico Mexico City Mestizo | | 0.0460 | | 121 | See | | | |
60,031 |
DRB1*16 | | Mexico Puebla Mestizo | | 0.0810 | | 99 | See | | | |
60,032 |
DRB1*16 | | Mexico Sinaloa Mestizo | | 0.0180 | | 56 | See | | | |
60,033 |
DRB1*16 | | Morocco pop 2 | | 0 | | 110 | See | | | |
60,034 |
DRB1*16 | | Pakistan Baloch | | 0.1320 | | 66 | See | | | |
60,035 |
DRB1*16 | | Pakistan Brahui | | 0.1700 | | 104 | See | | | |
60,036 |
DRB1*16 | | Pakistan Burusho | | 0 | | 92 | See | | | |
60,037 |
DRB1*16 | | Pakistan Kalash | | 0 | | 69 | See | | | |
60,038 |
DRB1*16 | | Pakistan Karachi Parsi | | 0.0170 | | 91 | See | | | |
60,039 |
DRB1*16 | | Pakistan Mixed Pathan | | 0.0200 | | 100 | See | | | |
60,040 |
DRB1*16 | | Pakistan Mixed Sindhi | | 0.0150 | | 101 | See | | | |
60,041 |
DRB1*16 | | Poland Lodz | | 0.0280 | | 103 | See | | | |
60,042 |
DRB1*16 | | Portugal North pop 2 | | 0.0155 | | 1,801 | See | | | |
60,043 |
DRB1*16 | | Russia Arkhangelsk | | 0.0190 | | 81 | See | | | |
60,044 |
DRB1*16 | | Russia Arkhangelsk Pomor | | 0.0260 | | 63 | See | | | |
60,045 |
DRB1*16 | | Russia Kostroma Region | | 0.0280 | | 126 | See | | | |
60,046 |
DRB1*16 | | Russia Mari | | 0.0220 | | 202 | See | | | |
60,047 |
DRB1*16 | | Russia Murmansk Saomi Mixed | | 0.0060 | | 70 | See | | | |
60,048 |
DRB1*16 | | Russia Nenet Mixed | | 0.0090 | | 55 | See | | | |
60,049 |
DRB1*16 | | Russia Northwest pop 3 | 7.0 | 0.0350 | | 100 | See | | | |
60,050 |
DRB1*16 | | Russia Northwest pop 2 | 7.2 | 0.0370 | | 346 | See | | | |
60,051 |
DRB1*16 | | Russia Samara Region | | 0.0430 | | 2,500 | See | | | |
60,052 |
DRB1*16 | | Russia Smolensk | | 0.0350 | | 156 | See | | | |
60,053 |
DRB1*16 | | Russia Vologda | | 0.0170 | | 121 | See | | | |
60,054 |
DRB1*16 | | Saudi Arabia pop 2 | | 0.0310 | | 383 | See | | | |
60,055 |
DRB1*16 | | Serbia | | 0.1050 | | 386 | See | | | |
60,056 |
DRB1*16 | | Serbia pop 3 | 20.4 | 0.1087 | | 1,992 | See | | | |
60,057 |
DRB1*16 | | Slovakia | | 0.0540 | | 146 | See | | | |
60,058 |
DRB1*16 | | South Africa Limpopo Venda | | 0.0340 | | 117 | See | | | |
60,059 |
DRB1*16 | | South Korea pop 8 | | 0.0110 | | 7,096 | See | | | |
60,060 |
DRB1*16 | | Spain Catalonia Girona | | 0 | | 88 | See | | | |
60,061 |
DRB1*16 | | Spain Gipuzkoa Basque | | 0 | | 100 | See | | | |
60,062 |
DRB1*16 | | Spain Granada | | 0.0130 | | 280 | See | | | |
60,063 |
DRB1*16 | | Spain Malaga | 3.8 | 0.0191 | | 160 | See | | | |
60,064 |
DRB1*16 | | Spain Malaga Romani | 12.0 | 0.0619 | | 80 | See | | | |
60,065 |
DRB1*16 | | Spain North | 3.0 | 0.0151 | | 156 | See | | | |
60,066 |
DRB1*16 | | Spain Northwest | 3.0 | 0.0151 | | 1,818 | See | | | |
60,067 |
DRB1*16 | | Spain Valencia | 3.5 | 0.0176 | | 577 | See | | | |
60,068 |
DRB1*16 | | Sri Lanka Colombo Sinhalese | | 0.0090 | | 101 | See | | | |
60,069 |
DRB1*16 | | Sweden Stockholm | 1.3 | 0.0070 | | 1,347 | See | | | |
60,070 |
DRB1*16 | | Switzerland Aargau-Solothurn | | 0.0287 | | 1,838 | See | | | |
60,071 |
DRB1*16 | | Taiwan Aborigine | | 0.0230 | | 111 | See | | | |
60,072 |
DRB1*16 | | Taiwan Chinese immigrants from Middle China | | 0.0240 | | 211 | See | | | |
60,073 |
DRB1*16 | | Taiwan Chinese immigrants from North China | | 0.0130 | | 152 | See | | | |
60,074 |
DRB1*16 | | Taiwan Chinese immigrants from South China | | 0.0540 | | 172 | See | | | |
60,075 |
DRB1*16 | | Taiwan Hakka pop 2 | | 0.0390 | | 714 | See | | | |
60,076 |
DRB1*16 | | Taiwan Minnan pop 2 | | 0.0390 | | 7,137 | See | | | |
60,077 |
DRB1*16 | | Tanzania Dodoma Kongwa | | 0.0090 | | 212 | See | | | |
60,078 |
DRB1*16 | | Thailand pop 2 | | 0.0400 | | 124 | See | | | |
60,079 |
DRB1*16 | | Thailand pop 4 | | 0.0470 | | 16,807 | See | | | |
60,080 |
DRB1*16 | | Turkey Ankara | | 0.0700 | | 50 | See | | | |
60,081 |
DRB1*16 | | Turkey Istanbul | 15.6 | 0.0813 | | 250 | See | | | |
60,082 |
DRB1*16 | | Turkey pop 2 | | 0.0270 | | 228 | See | | | |
60,083 |
DRB1*16 | | Ukraine Khmelnytskyi | | 0.0870 | | 138 | See | | | |
60,084 |
DRB1*16 | | Ukraine Lvov | | 0.0590 | | 102 | See | | | |
60,085 |
DRB1*16 | | United Kingdom pop 2 | | 0.0200 | | 101 | See | | | |
60,086 |
DRB1*16 | | USA Southeast African American | 5.4 | 0.0270 | | 112 | See | | | |
60,087 |
DRB1*16 | | Vietnam Hanoi | | 0.0400 | | 50 | See | | | |
60,088 |
DRB1*16 | | Wales | 1.1 | 0.0050 | | 1,798 | See | | | |
60,089 |
DRB1*16:01 | | Algeria pop 2 | 6.0 | 0.0304 | | 106 | See | | | |
60,090 |
DRB1*16:01 | | Argentina Chubut Tehuelche | | 0 | | 23 | See | | | |
60,091 |
DRB1*16:01 | | Argentina Gran Chaco Eastern Toba | | 0 | | 135 | See | | | |
60,092 |
DRB1*16:01 | | Argentina Gran Chaco Mataco Wichi | | 0 | | 49 | See | | | |
60,093 |
DRB1*16:01 | | Argentina Gran Chaco Western Toba Pilaga | | 0 | | 19 | See | | | |
60,094 |
DRB1*16:01 | | Argentina Rio Negro Mapuche | | 0.0150 | | 34 | See | | | |
60,095 |
DRB1*16:01 | | Argentina Salta Wichi | | 0 | | 24 | See | | | |
60,096 |
DRB1*16:01 | | Azores Central Islands | | 0.0180 | | 59 | See | | | |
60,097 |
DRB1*16:01 | | Azores Oriental Islands | | 0.0130 | | 43 | See | | | |
60,098 |
DRB1*16:01 | | Belgium | 5.1 | 0.0250 | | 99 | See | | | |
60,099 |
DRB1*16:01 | | Borneo Bandjarmasin | | 0.0470 | | 21 | See | | | |
60,100 |
DRB1*16:01 | | Brazil Central Plateau Xavante | | 0 | | 74 | 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 60,001 to 60,100
(from 60,683) records |
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