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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 |
59,001 |
DRB1*15 | | Pakistan Mixed Sindhi | | 0.1970 | | 101 | See | | | |
59,002 |
DRB1*15 | | Paraguay Aché | | 0 | | 87 | See | | | |
59,003 |
DRB1*15 | | Peru Quechua | | 0.0230 | | 44 | See | | | |
59,004 |
DRB1*15 | | Poland Lodz | | 0.1460 | | 103 | See | | | |
59,005 |
DRB1*15 | | Portugal North pop 2 | | 0.0737 | | 1,801 | See | | | |
59,006 |
DRB1*15 | | Russia Arkhangelsk | | 0.1980 | | 81 | See | | | |
59,007 |
DRB1*15 | | Russia Arkhangelsk Pomor | | 0.1790 | | 63 | See | | | |
59,008 |
DRB1*15 | | Russia Kostroma Region | | 0.1350 | | 126 | See | | | |
59,009 |
DRB1*15 | | Russia Mari | | 0.1060 | | 202 | See | | | |
59,010 |
DRB1*15 | | Russia Murmansk Saomi Mixed | | 0.1170 | | 70 | See | | | |
59,011 |
DRB1*15 | | Russia Nenet Mixed | | 0.0450 | | 55 | See | | | |
59,012 |
DRB1*15 | | Russia Northwest pop 3 | 22.0 | 0.1250 | | 100 | See | | | |
59,013 |
DRB1*15 | | Russia Northwest pop 2 | 28.3 | 0.1530 | | 346 | See | | | |
59,014 |
DRB1*15 | | Russia Samara Region | | 0.1410 | | 2,500 | See | | | |
59,015 |
DRB1*15 | | Russia Smolensk | | 0.1540 | | 156 | See | | | |
59,016 |
DRB1*15 | | Russia Vologda | | 0.1440 | | 121 | See | | | |
59,017 |
DRB1*15 | | Saudi Arabia pop 2 | | 0.1310 | | 383 | See | | | |
59,018 |
DRB1*15 | | Serbia | | 0.0840 | | 386 | See | | | |
59,019 |
DRB1*15 | | Serbia pop 3 | 18.6 | 0.0984 | | 1,992 | See | | | |
59,020 |
DRB1*15 | | Slovakia | | 0.1230 | | 146 | See | | | |
59,021 |
DRB1*15 | | South Africa Limpopo Venda | | 0.0730 | | 117 | See | | | |
59,022 |
DRB1*15 | | South Korea pop 8 | | 0.1120 | | 7,096 | See | | | |
59,023 |
DRB1*15 | | Spain Catalonia Girona | | 0.1190 | | 88 | See | | | |
59,024 |
DRB1*15 | | Spain Gipuzkoa Basque | | 0.1300 | | 100 | See | | | |
59,025 |
DRB1*15 | | Spain Granada | | 0.1090 | | 280 | See | | | |
59,026 |
DRB1*15 | | Spain Ibiza | | 0.1230 | | 88 | See | | | |
59,027 |
DRB1*15 | | Spain Madrid | 26.0 | 0.1397 | | 504 | See | | | |
59,028 |
DRB1*15 | | Spain Majorca | | 0.1040 | | 407 | See | | | |
59,029 |
DRB1*15 | | Spain Majorcans Jews | | 0.0980 | | 103 | See | | | |
59,030 |
DRB1*15 | | Spain Minorca | | 0.1230 | | 94 | See | | | |
59,031 |
DRB1*15 | | Spain North | 27.0 | 0.1456 | | 156 | See | | | |
59,032 |
DRB1*15 | | Spain Northwest | 18.3 | 0.0961 | | 1,818 | See | | | |
59,033 |
DRB1*15 | | Spain Northwest Lugo | 26.2 | 0.1409 | | 145 | See | | | |
59,034 |
DRB1*15 | | Spain Valencia | 20.8 | 0.1100 | | 577 | See | | | |
59,035 |
DRB1*15 | | Sri Lanka Colombo Sinhalese | | 0.2130 | | 101 | See | | | |
59,036 |
DRB1*15 | | Sweden Stockholm | 29.5 | 0.1560 | | 1,347 | See | | | |
59,037 |
DRB1*15 | | Taiwan Aborigine | | 0.1510 | | 111 | See | | | |
59,038 |
DRB1*15 | | Taiwan Chinese immigrants from Middle China | | 0.1320 | | 211 | See | | | |
59,039 |
DRB1*15 | | Taiwan Chinese immigrants from North China | | 0.1770 | | 152 | See | | | |
59,040 |
DRB1*15 | | Taiwan Chinese immigrants from South China | | 0.1130 | | 172 | See | | | |
59,041 |
DRB1*15 | | Taiwan Hakka pop 2 | | 0.1010 | | 714 | See | | | |
59,042 |
DRB1*15 | | Taiwan Minnan pop 2 | | 0.0990 | | 7,137 | See | | | |
59,043 |
DRB1*15 | | Tanzania Dodoma Kongwa | | 0.1700 | | 212 | See | | | |
59,044 |
DRB1*15 | | Thailand pop 2 | | 0.1810 | | 124 | See | | | |
59,045 |
DRB1*15 | | Thailand pop 4 | | 0.1750 | | 16,807 | See | | | |
59,046 |
DRB1*15 | | Turkey Ankara | | 0.1100 | | 50 | See | | | |
59,047 |
DRB1*15 | | Turkey Istanbul | 12.4 | 0.0640 | | 250 | See | | | |
59,048 |
DRB1*15 | | Turkey pop 2 | | 0.0540 | | 228 | See | | | |
59,049 |
DRB1*15 | | Ukraine Khmelnytskyi | | 0.1010 | | 138 | See | | | |
59,050 |
DRB1*15 | | Ukraine Lvov | | 0.0980 | | 102 | See | | | |
59,051 |
DRB1*15 | | United Kingdom pop 2 | | 0.0990 | | 101 | See | | | |
59,052 |
DRB1*15 | | USA OPTN African American | | 0.1620 | | 1,510 | See | | | |
59,053 |
DRB1*15 | | USA OPTN Asian | | 0.2280 | | 261 | See | | | |
59,054 |
DRB1*15 | | USA OPTN Caucasian | | 0.1580 | | 8,525 | See | | | |
59,055 |
DRB1*15 | | USA OPTN Hispanic | | 0.1080 | | 1,580 | See | | | |
59,056 |
DRB1*15 | | USA Southeast African American | 23.2 | 0.1380 | | 112 | See | | | |
59,057 |
DRB1*15 | | Vietnam Hanoi | | 0.0900 | | 50 | See | | | |
59,058 |
DRB1*15 | | Wales | 26.3 | 0.1380 | | 1,798 | See | | | |
59,059 |
DRB1*15:01 | | Algeria pop 2 | 22.0 | 0.1168 | | 106 | See | | | |
59,060 |
DRB1*15:01 | | Argentina Gran Chaco Eastern Toba | | 0.0040 | | 135 | See | | | |
59,061 |
DRB1*15:01 | | Argentina Gran Chaco Mataco Wichi | | 0.0110 | | 49 | See | | | |
59,062 |
DRB1*15:01 | | Argentina Gran Chaco Western Toba Pilaga | | 0.0930 | | 19 | See | | | |
59,063 |
DRB1*15:01 | | Australia Cape York Peninsula Aborigine | | 0.0450 | | 103 | See | | | |
59,064 |
DRB1*15:01 | | Azores Central Islands | | 0.0800 | | 59 | See | | | |
59,065 |
DRB1*15:01 | | Azores Oriental Islands | | 0.0900 | | 43 | See | | | |
59,066 |
DRB1*15:01 | | Borneo Bandjarmasin | | 0.1670 | | 21 | See | | | |
59,067 |
DRB1*15:01 | | Brazil Central Plateau Xavante | | 0 | | 74 | See | | | |
59,068 |
DRB1*15:01 | | Brazil Guarani M bya | | 0 | | 93 | See | | | |
59,069 |
DRB1*15:01 | | Brazil Guarani Nandeva | | 0 | | 86 | See | | | |
59,070 |
DRB1*15:01 | | Brazil Kaingang | | 0 | | 235 | See | | | |
59,071 |
DRB1*15:01 | | Brazil North East Mixed | | 0.0370 | | 205 | See | | | |
59,072 |
DRB1*15:01 | | Canada British Columbia Athabaskan | | 0.0080 | | 62 | See | | | |
59,073 |
DRB1*15:01 | | Canada British Columbia Penutian | | 0.0770 | | 26 | See | | | |
59,074 |
DRB1*15:01 | | Central African Republic Aka Pygmy | 0.0 | 0 | | 93 | See | | | |
59,075 |
DRB1*15:01 | | China Beijing and Xian | | 0.1080 | | 171 | See | | | |
59,076 |
DRB1*15:01 | | China Beijing Shijiazhuang Tianjian Han | | 0.0760 | | 618 | See | | | |
59,077 |
DRB1*15:01 | | China Canton Han | | 0.1080 | | 264 | See | | | |
59,078 |
DRB1*15:01 | | China Guangxi Region Maonan | | 0.1060 | | 108 | See | | | |
59,079 |
DRB1*15:01 | | China Harbin Manchu pop 2 | | 0.1100 | | 50 | See | | | |
59,080 |
DRB1*15:01 | | China Hong Kong and Singapore | | 0.1220 | | 135 | See | | | |
59,081 |
DRB1*15:01 | | China Southwest Dai | | 0.0930 | | 124 | See | | | |
59,082 |
DRB1*15:01 | | China Urumqi Han | | 0.1100 | | 59 | See | | | |
59,083 |
DRB1*15:01 | | China Urumqi Kazak | | 0.0360 | | 42 | See | | | |
59,084 |
DRB1*15:01 | | China Urumqi Uyghur | 17.5 | 0.0960 | | 57 | See | | | |
59,085 |
DRB1*15:01 | | China Wuhan | 26.5 | 0.1360 | | 121 | See | | | |
59,086 |
DRB1*15:01 | | China Xinjiang Province Uyghur | | 0.0540 | | 92 | See | | | |
59,087 |
DRB1*15:01 | | China Yunnan Province Han | | 0.0560 | | 101 | See | | | |
59,088 |
DRB1*15:01 | | China Yunnan Province Han pop 2 | | 0.1240 | | 129 | See | | | |
59,089 |
DRB1*15:01 | | China Yunnan Province Naxi | | 0.0890 | | 118 | See | | | |
59,090 |
DRB1*15:01 | | Colombia Bogota and Medellin Mestizo | | 0.0920 | | 65 | See | | | |
59,091 |
DRB1*15:01 | | Colombia Guajira Peninsula Wayuu | | 0.0540 | | 88 | See | | | |
59,092 |
DRB1*15:01 | | Colombia Providencia Island African | | 0.0170 | | 30 | See | | | |
59,093 |
DRB1*15:01 | | Colombia Sierra Nevada de Santa Marta Arhuaco | | 0.0330 | | 107 | See | | | |
59,094 |
DRB1*15:01 | | Colombia Sierra Nevada de Santa Marta Ijka pop 2 | | 0.0170 | | 30 | See | | | |
59,095 |
DRB1*15:01 | | Cook Islands Rarotonga | | 0.0130 | | 78 | See | | | |
59,096 |
DRB1*15:01 | | Croatia Krk Island | | 0.0240 | | 212 | See | | | |
59,097 |
DRB1*15:01 | | Croatia Krk Island Dubasnica | | 0.0430 | | 23 | See | | | |
59,098 |
DRB1*15:01 | | Croatia Krk Island Vrbnik | | 0.0180 | | 28 | See | | | |
59,099 |
DRB1*15:01 | | Cuba Mixed | | 0.0920 | | 78 | See | | | |
59,100 |
DRB1*15:01 | | Czech Republic pop 2 | 20.2 | 0.1066 | | 99 | 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.