Population |
Phenotype Frequency (%) |
Allele Frequency (in_decimals) |
Sample Size |
IMGT/HLA¹ Database |
Distribution² |
Haplotype³ Association |
Notesª |
 | China Yunnan Province Han pop 2 | | 0.1790 |  | 129 | See |  |  | |
 | Taiwan Chinese immigrants from South China | | 0.1720 |  | 172 | See |  |  | |
 | Taiwan Hakka pop 2 | | 0.1560 |  | 714 | See |  |  | |
 | Taiwan Chinese immigrants from Middle China | | 0.1500 |  | 211 | See |  |  | |
 | Taiwan Minnan pop 2 | | 0.1460 |  | 7137 | See |  |  | |
 | Taiwan Minnan and Hakka | | 0.1360 |  | 190 | See |  |  | |
 | China Wuhan | 26.7 | 0.1350 |  | 121 | See |  |  | |
 | Thailand pop 4 | | 0.1320 |  | 16807 | See |  |  | |
 | China Guangdong Province | 24.6 | 0.1316 |  | 403 | See |  |  | |
 | China Shanghai | | 0.1120 |  | 26266 | See |  |  | |
 | Vietnam Hanoi | | 0.1100 |  | 50 | See |  |  | |
 | China Jiangsu Province | | 0.0940 |  | 20248 | See |  |  | |
 | Taiwan Chinese immigrants from North China | | 0.0860 |  | 152 | See |  |  | |
 | China Shaanxi Province Han | | 0.0790 |  | 10000 | See |  |  | |
 | Japan Aichi | 15.2 | 0.0760 |  | 50 | See |  |  | |
 | Myanmar Shan | 13.0 | 0.0648 |  | 54 | See |  |  |
|
 | Japan Kyoto and Osaka | | 0.0640 |  | 165 | See |  |  | |
 | USA OPTN Asian | | 0.0620 |  | 261 | See |  |  | |
 | China Yunnan Province Naxi | | 0.0610 |  | 118 | See |  |  | |
 | China Shandong Province | 10.9 | 0.0560 |  | 7418 | See |  |  | |
 | Brazil Parana Japanese | 10.0 | 0.0521 |  | 192 | See |  |  |
|
 | Japan Hyogo Osaka and Nagano | | 0.0510 |  | 195 | See |  |  | |
 | South Korea pop 8 | | 0.0490 |  | 7096 | See |  |  | |
 | Japan Hyogo | 9.4 | 0.0470 |  | 32 | See |  |  | |
 | Myanmar Mon | 9.4 | 0.0469 |  | 64 | See |  |  |
|
 | South Korea pop 1 | | 0.0460 |  | 324 | See |  |  | |
 | Myanmar Bamar | 8.7 | 0.0435 |  | 46 | See |  |  |
|
 | Japan pop 2 | | 0.0410 |  | 916 | See |  |  | |
 | China Harbin Manchu | | 0.0410 |  | 172 | See |  |  | |
 | Japan Tohoku Region | | 0.0390 |  | 322 | See |  |  | |
 | Japan pop 11 | 6.5 | 0.0330 |  | 62 | See |  |  | |
 | China Shandong Province Linqu County | 6.5 | 0.0330 |  | 139 | See |  |  | |
 | Russia, South Ural, Chelyabinsk region, Nagaybaks | 5.4 | 0.0270 |  | 112 | See |  |  |
|
 | Malaysia pop 2 | | 0.0260 |  | 62 | See |  |  | |
 | Malaysia Sabah Kadazan | | 0.0260 |  | 57 | See |  |  | |
 | Russia South Ural Bashkir | 4.8 | 0.0240 |  | 146 | See |  |  | |
 | Malaysia Perak Rawa | | 0.0200 |  | 23 | See |  |  | |
 | Malaysia pop 3 | | 0.0190 |  | 1445 | See |  |  | |
 | Russia Sakhalin Island Nivkhi | | 0.0190 |  | 53 | See |  |  | |
 | Mongolia Oold | | 0.0190 |  | 104 | See |  |  | |
 | China Harbin Korean | | 0.0170 |  | 201 | See |  |  | |
 | Mexico Jalisco, Tonala | | 0.0143 |  | 35 | See |  |  |
|
 | Iraq Arabs | 2.7 | 0.0134 |  | 149 | See |  |  |
|
 | Macedonia MBMDR - Macedonian Muslims | 2.6 | 0.0132 |  | 76 | See |  |  |
|
 | Mexico Hidalgo, Pachuca | | 0.0122 |  | 41 | See |  |  |
|
 | Mongolia Ulaanbaatar Khalkha | | 0.0120 |  | 41 | See |  |  | |
 | Russia South Ural Tatar | 2.2 | 0.0110 |  | 135 | See |  |  | |
 | Malaysia Negeri Sembilan Minangkabau | | 0.0100 |  | 34 | See |  |  | |
 | Philippines National Capital Region | | 0.0100 |  | 51 | See |  |  |
|
 | Mexico Mexico City South | | 0.0096 |  | 52 | See |  |  |
|
 | Myanmar Kayah | 1.8 | 0.0091 |  | 55 | See |  |  |
|
 | Taiwan Aborigine | | 0.0090 |  | 111 | See |  |  | |
 | Brazil Curitiba-Parana Mixed | | 0.0082 |  | 264 | See |  |  | |
 | Myanmar Kachin | 1.6 | 0.0079 |  | 63 | See |  |  |
|
 | Russia Transbaikal Territory Buryats | 1.0 | 0.0070 |  | 150 | See |  |  |
|
 | Armenia Shirak | | 0.0070 |  | 76 | See |  |  | |
 | Russia Tatars | | 0.0056 |  | 355 | See |  |  | |
 | Mongolia Khalkha pop 2 | | 0.0050 |  | 202 | See |  |  | |
 | Mongolia Khalkha | | 0.0050 |  | 200 | See |  |  | |
 | Pakistan Brahui | | 0.0050 |  | 104 | See |  |  | |
 | Russia Northwest pop 3 | 1.0 | 0.0050 |  | 100 | See |  |  | |
 | Brazil Belem Mixed | 1.0 | 0.0050 |  | 100 | See |  |  | |
 | Bosnia and Herzegovina pop 2 | 0.8 | 0.0042 |  | 120 | See |  |  | |
 | Turkey pop 5 | | 0.0040 |  | 142 | See |  |  | |
 | Greece pop3 | 0.8 | 0.0040 |  | 246 | See |  |  | |
 | Mexico Mexico City Metropolitan Area Rural | | 0.0033 |  | 150 | See |  |  |
|
 | Mexico Mexico City Center | | 0.0032 |  | 152 | See |  |  |
|
 | Peru Arequipa Mestizo | 0.7 | 0.0030 |  | 168 | See |  |  | |
 | Russia Samara Region | | 0.0030 |  | 2500 | See |  |  | |
 | Saudi Arabia pop 2 | | 0.0030 |  | 383 | See |  |  | |
 | Bangladesh Dhaka Bangalee | | 0.0030 |  | 141 | See |  |  | |
 | India North Gujarat | 0.6 | 0.0030 |  | 338 | See |  |  | |
 | Italy pop 6 | 0.5 | 0.0027 |  | 184 | See |  |  | |
 | France Marseille | 0.5 | 0.0026 |  | 1000 | See |  |  | |
 | Sweden pop 4 | 0.3 | 0.0021 |  | 966 | See |  |  | |
 | Russia Moscow | | 0.0020 |  | 2650 | See |  |  | |
 | Iran Royan Cord Blood Bank | 0.4 | 0.0020 |  | 15600 | See |  |  | |
 | Brazil Parana Cafuzo | 0.3 | 0.0020 |  | 319 | See |  |  | |
 | Serbia | | 0.0020 |  | 386 | See |  |  | |
 | Russia Moscow Pop 2 | 0.4 | 0.0018 |  | 2000 | See |  |  | |
 | Mexico Jalisco Rural | | 0.0017 |  | 585 | See |  |  |
|
 | Mexico Puebla, Puebla city | | 0.0010 |  | 1994 | See |  |  |
|
 | Brazil South East Cord Blood | | 0.0010 |  | 11409 | See |  |  |
|
 | Mexico Oaxaca Rural | | 0.0010 |  | 485 | See |  |  |
|
 | Romania | 0.3 | 0.0010 |  | 348 | See |  |  | |
 | Australia West Caucasian | 0.1 | 0.0010 |  | 891 | See |  |  | |
 | Brazil Rio Grande do Norte Mestizo | | 0.0010 |  | 12973 | See |  |  | |
 | Wales pop 2 | 0.1 | 0.0010 |  | 39979 | See |  |  | |
 | France Bordeaux | 0.2 | 0.0010 |  | 990 | See |  |  | |
 | USA OPTN Hispanic | | 0.0010 |  | 1580 | See |  |  | |
 | Portugal Portalegre | | 0.0010 |  | 1254 | See |  |  | |
 | Brazil REDOME Parana | | 0.0008 |  | 341639 | See |  |  | |
 | Brazil REDOME Sao Paulo | | 0.0007 |  | 800809 | See |  |  | |
 | Norway ethnic Norwegians | 0.1 | 0.0006 |  | 4510 | See |  |  |
|
 | Mexico Tlaxcala Rural | | 0.0006 |  | 830 | See |  |  |
|
 | Iran pop 4 | | 0.0006 |  | 855 | See |  |  |
|
 | Brazil REDOME Mato Grosso do Sul | | 0.0005 |  | 95667 | See |  |  | |
 | France Rennes pop 4 | 0.1 | 0.0005 |  | 1000 | See |  |  | |
 | France Lyon | 0.1 | 0.0005 |  | 4813 | See |  |  | |
 | Germany | 0.1 | 0.0005 |  | 11407 | See |  |  | |
 | Brazil REDOME Alagoas | | 0.0004 |  | 25349 | See |  |  | |
 | Brazil REDOME Sergipe | | 0.0004 |  | 7321 | See |  |  | |
 | Macedonia MBMDR - Macedonian | 0.1 | 0.0004 |  | 1283 | See |  |  |
|
 | Brazil REDOME Tocantins | | 0.0003 |  | 20692 | See |  |  | |
 | Brazil REDOME Rio Grande do Norte | | 0.0003 |  | 46603 | See |  |  | |
 | Brazil REDOME Federal District | | 0.0003 |  | 29549 | See |  |  | |
 | Brazil REDOME Maranhao | | 0.0003 |  | 10180 | See |  |  | |
 | Brazil REDOME Mato Grosso | | 0.0003 |  | 34649 | See |  |  | |
 | Romania pop 3 | 0.1 | 0.0003 |  | 1469 | See |  |  | |
 | Serbia pop 3 | 0.1 | 0.0003 |  | 1992 | See |  |  | |
 | Slovakia pop 2 | | 0.0003 |  | 4234 | See |  |  | |
 | Poland pop 3 | 0.0 | 0.0002 |  | 2907 | See |  |  | |
 | Brazil REDOME Bahia | | 0.0002 |  | 47399 | See |  |  | |
 | Brazil REDOME Minas Gerais | | 0.0002 |  | 211275 | See |  |  | |
 | Brazil REDOME Para | | 0.0002 |  | 72637 | See |  |  | |
 | Brazil REDOME Paraiba | | 0.0002 |  | 43868 | See |  |  | |
 | Brazil REDOME Pernambuco | | 0.0002 |  | 92332 | See |  |  | |
 | Brazil REDOME Rio de Janeiro | | 0.0002 |  | 139322 | See |  |  | |
 | Brazil REDOME Roraima | | 0.0002 |  | 4140 | See |  |  | |
 | Brazil REDOME Rondonia | | 0.0002 |  | 54396 | See |  |  | |
 | Brazil REDOME Santa Catarina | | 0.0002 |  | 106673 | See |  |  | |
 | Brazil REDOME Goias | | 0.0002 |  | 88574 | See |  |  | |
 | Brazil Para State | 0.0 | 0.0002 |  | 5000 | See |  |  |
|
 | Brazil REDOME Rio Grande do Sul | | 0.0001 |  | 241329 | See |  |  | |
 | Brazil REDOME Piaui | | 0.0001 |  | 46140 | See |  |  | |
 | Brazil Rio Grande do Sul Caucasoid | | 0.0001 |  | 4428 | See |  |  | |
 | Brazil REDOME Espirito Santo | | 0.0001 |  | 88485 | See |  |  | |
 | Brazil REDOME Ceara | | 0.0001 |  | 101217 | See |  |  | |
 | Brazil REDOME Amazonas | | 0.0001 |  | 24129 | See |  |  | |
 | Brazil REDOME Amapa | | 0.0001 |  | 17864 | See |  |  | |
 | Greece pop 7 | | 0.0001 |  | 11250 | See |  |  | |
 | Italy | | 0.0001 |  | 159311 | See |  |  | |
 | Russia Nenet Mixed | | 0.0000 |  | 55 | See |  |  | |
 | Russia Arkhangelsk Pomor | | 0.0000 |  | 63 | See |  |  | |
 | Russia Murmansk Saomi Mixed | | 0.0000 |  | 70 | See |  |  | |
 | Portugal North | | 0.0000 |  | 46 | See |  |  | |
 | Argentina La Plata | 0.0 | 0.0000 |  | 100 | See |  |  | |
 | Argentina Chiriguano | 0.0 | 0.0000 |  | 54 | See |  |  | |
 | Argentina Salta Wichi pop 2 | 0.0 | 0.0000 |  | 19 | See |  |  | |
 | Spain Majorca | | 0.0000 |  | 407 | See |  |  | |
 | Spain Minorca | | 0.0000 |  | 94 | See |  |  | |
 | Spain Ibiza | | 0.0000 |  | 88 | See |  |  | |
 | Spain Majorcans Jews | | 0.0000 |  | 103 | See |  |  | |
 | Spain Murcia | | 0.0000 |  | 173 | See |  |  | |
 | Croatia | | 0.0000 |  | 150 | See |  |  | |
 | South Africa Natal Zulu | 0.0 | 0.0000 |  | 100 | See |  |  | |
 | Italy Rome | 0.0 | 0.0000 |  | 100 | See |  |  | |
 | Italy North pop 3 | 0.0 | 0.0000 |  | 97 | See |  |  | |
 | Italy Bergamo | 0.0 | 0.0000 |  | 101 | See |  |  | |
 | Brazil Sao Paulo Mixed | 0.0 | 0.0000 |  | 239 | See |  |  | |
 | Greece North | | 0.0000 |  | 500 | See |  |  | |
 | Wales | 0.0 | 0.0000 |  | 1798 | See |  |  | |
 | Mongolia Tsaatan | | 0.0000 |  | 144 | See |  |  | |
 | France Southeast | 0.0 | 0.0000 |  | 130 | See |  |  | |
 | USA Caucasian Bethesda | 0.0 | 0.0000 |  | 307 | See |  |  | |
 | USA African American Bethesda | 0.0 | 0.0000 |  | 187 | See |  |  | |
 | Macedonia pop 4 | | 0.0000 |  | 216 | See |  |  | |
 | Pakistan Burusho | | 0.0000 |  | 92 | See |  |  | |
 | Pakistan Kalash | | 0.0000 |  | 69 | See |  |  | |
 | Pakistan Mixed Pathan | | 0.0000 |  | 100 | See |  |  | |
 | Pakistan Mixed Sindhi | | 0.0000 |  | 101 | See |  |  | |
 | Pakistan Baloch | | 0.0000 |  | 66 | See |  |  | |
 | Argentina Cuyo Region | 0.0 | 0.0000 |  | 420 | See |  |  | |
 | USA OPTN African American | | 0.0000 |  | 1510 | See |  |  | |
 | Brazil Parana Mixed race | 0.0 | 0.0000 |  | 186 | See |  |  | |
 | Brazil Parana Afro Brazilian | 0.0 | 0.0000 |  | 77 | See |  |  | |
 | Brazil Parana Oriental | 0.0 | 0.0000 |  | 33 | See |  |  | |
 | China North Han | | 0.0000 |  | 105 | See |  |  | |
 | Portugal South pop 2 | | 0.0000 |  | 1021 | See |  |  | |
 | Pakistan Karachi Parsi | | 0.0000 |  | 91 | See |  |  | |
 | England Leeds | 0.0 | 0.0000 |  | 5024 | See |  |  | |
 | Croatia pop 2 | | 0.0000 |  | 100 | See |  |  | |
 | Argentina Buenos Aires pop 2 | 0.1 | 0.0000 |  | 1216 | See |  |  | |
 | Mongolia Tarialan Khoton | | 0.0000 |  | 85 | See |  |  | |
 | Italy South Campania Region | 0.0 | 0.0000 |  | 1089 | See |  |  | |
 | Brazil Parana Caucasian | 0.0 | 0.0000 |  | 2775 | See |  |  | |
 | Ireland South pop 2 | | 0.0000 |  | 17624 | See |  |  | |
 | Morocco pop 2 | | 0.0000 |  | 110 | See |  |  | |
 | Argentina Corrientes | 0.0 | 0.0000 |  | 155 | See |  |  | |
 | Brazil Piaui Mixed | | 0.0000 |  | 21943 | See |  |  | |
 | Jordan | | 0.0000 |  | 15141 | See |  |  | |
 | Mexico Mexico City Mestizo | | 0.0000 |  | 121 | See |  |  | |
 | Mexico Puebla Mestizo | | 0.0000 |  | 99 | See |  |  | |
 | Mexico Sinaloa Mestizo | | 0.0000 |  | 56 | See |  |  | |
 | Russia Northwest pop 2 | 0.0 | 0.0000 |  | 346 | See |  |  | |
 | Russia South Ural Russian | 0.0 | 0.0000 |  | 207 | See |  |  | |
 | United Arab Emirates pop 2 | 0.0 | 0.0000 |  | 373 | See |  |  | |
 | Portugal Porto | | 0.0000 |  | 7937 | See |  |  | |
 | Portugal Santarem | | 0.0000 |  | 3865 | See |  |  | |
 | Portugal Setubal | | 0.0000 |  | 5268 | See |  |  | |
 | Portugal Viana do Castelo | | 0.0000 |  | 706 | See |  |  | |
 | Portugal Vila Real | | 0.0000 |  | 1167 | See |  |  | |
 | Portugal Viseu | | 0.0000 |  | 2915 | See |  |  | |
 | Azores | | 0.0000 |  | 1050 | See |  |  | |
 | Madeira pop 3 | | 0.0000 |  | 538 | See |  |  | |
 | Malaysia Perak and Johor Banjar Bugis Jawa | | 0.0000 |  | 94 | See |  |  | |
 | Tanzania Dodoma Kongwa | | 0.0000 |  | 212 | See |  |  | |
 | Bosnia and Herzegovina | | 0.0000 |  | 134 | See |  |  | |
 | USA OPTN Caucasian | | 0.0000 |  | 8525 | See |  |  | |
 | Portugal Aveiro | | 0.0000 |  | 5933 | See |  |  | |
 | Portugal Beja | | 0.0000 |  | 699 | See |  |  | |
 | Portugal Braga | | 0.0000 |  | 1971 | See |  |  | |
 | Portugal Bragança | | 0.0000 |  | 301 | See |  |  | |
 | Portugal Castelo Branco | | 0.0000 |  | 327 | See |  |  | |
 | Portugal Coimbra | | 0.0000 |  | 5057 | See |  |  | |
 | Portugal Evora | | 0.0000 |  | 737 | See |  |  | |
 | Portugal Faro | | 0.0000 |  | 1242 | See |  |  | |
 | Portugal Guarda | | 0.0000 |  | 797 | See |  |  | |
 | Portugal Leiria | | 0.0000 |  | 1847 | See |  |  | |
 | Portugal Lisbon | | 0.0000 |  | 17420 | See |  |  | |
 | Brazil Sao Paulo Bauru Mixed | | 0.0000 |  | 3542 | See |  |  | |
 | United Kingdom South West | | 0.0000 |  | 163 | See |  |  | |
 | Ecuador Coast Mixed Ancestry | | 0.0000 |  | 238 | See |  |  |
|
 | Ecuador Amazonia Mixed Ancestry | | 0.0000 |  | 39 | See |  |  |
|
 | Mexico Quintana Roo, Cancun | | 0.0000 |  | 48 | See |  |  |
|
 | Mexico Mexico City West | | 0.0000 |  | 33 | See |  |  |
|
 | Mexico Yucatan, Merida | | 0.0000 |  | 192 | See |  |  |
|
 | Mexico Campeche, Campeche city | | 0.0000 |  | 34 | See |  |  |
|
 | Mexico Chiapas, Tuxtla Gutierrez | | 0.0000 |  | 52 | See |  |  |
|
 | Mexico Tabasco, Villahermosa | | 0.0000 |  | 82 | See |  |  |
|
 | Mexico Morelos, Cuernavaca | | 0.0000 |  | 82 | See |  |  |
|
 | Mexico Oaxaca, Oaxaca city | | 0.0000 |  | 151 | See |  |  |
|
 | Mexico Guerrero state | | 0.0000 |  | 144 | See |  |  |
|
 | Mexico Veracruz, Xalapa | | 0.0000 |  | 187 | See |  |  |
|
 | Mexico Veracruz, Veracruz city | | 0.0000 |  | 171 | See |  |  |
|
 | Mexico Veracruz, Poza Rica | | 0.0000 |  | 45 | See |  |  |
|
 | Mexico Veracruz, Cordoba | | 0.0000 |  | 56 | See |  |  |
|
 | Mexico Veracruz, Orizaba | | 0.0000 |  | 60 | See |  |  |
|
 | Mexico Veracruz, Coatzacoalcos | | 0.0000 |  | 55 | See |  |  |
|
 | Mexico San Luis Potosi, San Luis Potosi city | | 0.0000 |  | 30 | See |  |  |
|
 | Mexico Tamaulipas, Ciudad Victoria | | 0.0000 |  | 23 | See |  |  |
|
 | Mexico Queretaro, Queretaro city | | 0.0000 |  | 45 | See |  |  |
|
 | Mexico Aguascalientes state | | 0.0000 |  | 95 | See |  |  | |
 | Mexico Nuevo Leon, Monterrey city | | 0.0000 |  | 226 | See |  |  |
|
 | Mexico Colima, Colima city | | 0.0000 |  | 61 | See |  |  |
|
 | Mexico Guanajuato, Leon | | 0.0000 |  | 78 | See |  |  |
|
 | Mexico Guanajuato, Guanajuato city | | 0.0000 |  | 22 | See |  |  |
|
 | Mexico Michoacan, Morelia | | 0.0000 |  | 150 | See |  |  |
|
 | Mexico Jalisco, Zapopan | | 0.0000 |  | 168 | See |  |  |
|
 | Mexico Jalisco, Tlaquepaque | | 0.0000 |  | 39 | See |  |  |
|
 | Mexico Jalisco, Tlajomulco | | 0.0000 |  | 30 | See |  |  |
|
 | Mexico Jalisco, Guadalajara city | | 0.0000 |  | 1189 | See |  |  |
|
 | Mexico Nayarit, Tepic | | 0.0000 |  | 97 | See |  |  |
|
 | Mexico Zacatecas, Fresnillo | | 0.0000 |  | 103 | See |  |  |
|
 | Mexico Zacatecas, Zacatecas city | | 0.0000 |  | 84 | See |  |  |
|
 | Mexico Coahuila, Torreon | | 0.0000 |  | 396 | See |  |  |
|
 | Mexico Coahuila, Saltillo | | 0.0000 |  | 72 | See |  |  |
|
 | Mexico Durango, Durango city | | 0.0000 |  | 153 | See |  |  |
|
 | Mexico Chihuahua, Ciudad Juarez | | 0.0000 |  | 106 | See |  |  |
|
 | Mexico Chihuahua Chihuahua City | | 0.0000 |  | 119 | See |  |  |
|
 | Mexico Sinaloa, Culiacán | | 0.0000 |  | 103 | See |  |  |
|
 | Mexico Sonora, Hermosillo | | 0.0000 |  | 99 | See |  |  |
|
 | Mexico Sonora, Ciudad Obregón | | 0.0000 |  | 143 | See |  |  |
|
 | Mexico Baja California, La Paz | | 0.0000 |  | 75 | See |  |  |
|
 | Mexico Baja Californa, Mexicali | | 0.0000 |  | 100 | See |  |  |
|
 | Mexico Baja California Rural | | 0.0000 |  | 50 | See |  |  |
|
 | Mexico Sonora Rural | | 0.0000 |  | 197 | See |  |  |
|
 | Mexico Sinaloa Rural | | 0.0000 |  | 183 | See |  |  |
|
 | Mexico Chihuahua Rural | | 0.0000 |  | 236 | See |  |  |
|
 | Mexico Durango Rural | | 0.0000 |  | 326 | See |  |  |
|
 | Mexico Coahuila Rural | | 0.0000 |  | 216 | See |  |  |
|
 | Mexico Zacatecas Rural | | 0.0000 |  | 266 | See |  |  |
|
 | Mexico Nayarit Rural | | 0.0000 |  | 64 | See |  |  |
|
 | Mexico Tlaxcala, Tlaxcala city | | 0.0000 |  | 181 | See |  |  |
|
 | Ecuador Andes Mixed Ancestry | | 0.0000 |  | 824 | See |  |  |
|
 | Ecuador Mixed Ancestry | | 0.0000 |  | 1173 | See |  |  |
|
 | Mexico Michoacan Rural | | 0.0000 |  | 348 | See |  |  |
|
 | Mexico Guanajuato Rural | | 0.0000 |  | 162 | See |  |  |
|
 | Mexico Colima Rural | | 0.0000 |  | 43 | See |  |  |
|
 | Mexico Nuevo Leon Rural | | 0.0000 |  | 439 | See |  |  |
|
 | Mexico Queretaro Rural | | 0.0000 |  | 43 | See |  |  |
|
 | Mexico Tamaulipas Rural | | 0.0000 |  | 125 | See |  |  |
|
 | Mexico San Luis Potosi Rural | | 0.0000 |  | 87 | See |  |  |
|
 | Mexico Veracruz Rural | | 0.0000 |  | 539 | See |  |  |
|
 | Mexico Hidalgo Rural | | 0.0000 |  | 81 | See |  |  |
|
 | Mexico Baja California, Tijuana | | 0.0000 |  | 25 | See |  |  |
|
 | Spain, Castilla y Leon, Northwest, | 0.0 | 0.0000 |  | 1743 | See |  |  |
|
 | Mexico Puebla Rural | | 0.0000 |  | 833 | See |  |  |
|
 | Mexico Mexico City North | | 0.0000 |  | 751 | See |  |  |
|
 | Mexico Mexico City East | | 0.0000 |  | 79 | See |  |  |
|
 | Mexico Morelos Rural | | 0.0000 |  | 30 | See |  |  |
|
 | Mexico Tabasco Rural | | 0.0000 |  | 142 | See |  |  |
|
 | Mexico Chiapas Rural | | 0.0000 |  | 121 | See |  |  |
|
 | Mexico Campeche Rural | | 0.0000 |  | 47 | See |  |  |
|
 | Mexico Yucatan Rural | | 0.0000 |  | 132 | See |  |  |
|
 | Mexico Quintana Roo Rural | | 0.0000 |  | 50 | See |  |  |
|
* Allele Frequency: Total number of copies of the allele in the population sample (Alleles / 2n) in decimal format.
: This field has been expanded to four decimals to better represent frequencies of large datasets (e.g. where sample size > 1000 individuals)
* Phenotype Frequency: Percentage of individuals who have the allele or gene (Individuals / n).
were calculated from Phenotype Frequencies assuming Hardy-Weinberg proportions.
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.