Population |
Phenotype Frequency (%) |
Allele Frequency (in_decimals) |
Sample Size |
IMGT/HLA¹ Database |
Distribution² |
Haplotype³ Association |
Notesª |
| Malaysia Sarawak Bau Bidayuh | | 0.1800 | | 25 | See | | | |
| Australia Cape York Peninsula Aborigine | | 0.1350 | | 103 | See | | | |
| Australia Yuendumu Aborigine | | 0.1240 | | 191 | See | | | |
| Indonesia Java pop 2 | | 0.1110 | | 36 | See | | | |
| Singapore SGVP Malay MAS | | 0.1010 | | 89 | See | | |
|
| Indonesia Java Western | 14.0 | 0.0730 | | 236 | See | | | |
| Papua New Guinea Eastern Highlands Goroka Asaro | | 0.0710 | | 57 | See | | | |
| Indonesia Sundanese and Javanese | | 0.0620 | | 201 | See | | | |
| Australia Groote Eylandt Aborigine | | 0.0600 | | 75 | See | | | |
| New Caledonia | | 0.0580 | | 65 | See | | | |
| Singapore Riau Malay | | 0.0400 | | 132 | See | | | |
| Malaysia Peninsular Malay | 7.1 | 0.0373 | | 951 | See | | |
|
| Malaysia Champa | 6.9 | 0.0340 | | 29 | See | | |
|
| USA NMDP Hawaiian or other Pacific Islander | | 0.0332 | | 11499 | See | | | |
| USA NMDP Filipino | | 0.0325 | | 50614 | See | | | |
| American Samoa | | 0.0300 | | 51 | See | | | |
| Australia Kimberly Aborigine | | 0.0260 | | 41 | See | | | |
| Papua New Guinea Karimui Plateau Pawaia | | 0.0250 | | 80 | See | | | |
| Malaysia Patani | 4.0 | 0.0200 | | 25 | See | | |
|
| Singapore Javaneses | | 0.0200 | | 51 | See | | | |
| China Southwest Dai | | 0.0160 | | 124 | See | | | |
| Papua New Guinea Wanigela Keapara | | 0.0150 | | 66 | See | | | |
| USA Asian | | 0.0140 | | 358 | See | | | |
| Thailand pop 3 | | 0.0100 | | 49 | See | | | |
| Philippines Ivatan | 2.0 | 0.0100 | | 50 | See | | | |
| Taiwan Hakka | 1.8 | 0.0090 | | 55 | See | | | |
| Thailand Northeast pop 2 | | 0.0090 | | 400 | See | | | |
| China Beijing pop 2 | | 0.0074 | | 826 | See | | | |
| Thailand | | 0.0070 | | 142 | See | | | |
| Malaysia Peninsular Chinese | 1.0 | 0.0052 | | 194 | See | | |
|
| China Yunnan Bulang | | 0.0040 | | 116 | See | | | |
| USA NMDP Southeast Asian | | 0.0037 | | 27978 | See | | | |
| USA Asian pop 2 | | 0.0037 | | 1772 | See | | | |
| Saudi Arabia pop 5 | 0.6 | 0.0032 | | 158 | See | | | |
| Vietnam Hanoi Kinh pop 2 | | 0.0030 | | 170 | See | | | |
| South Africa Worcester | 1.0 | 0.0030 | | 159 | See | | |
|
| USA San Diego | 0.3 | 0.0020 | | 496 | See | | |
|
| Hong Kong Chinese | 0.4 | 0.0020 | | 569 | See | | | |
| China Beijing Shijiazhuang Tianjian Han | | 0.0020 | | 618 | See | | | |
| China South Han | | 0.0020 | | 284 | See | | | |
| USA NMDP Vietnamese | | 0.0012 | | 43540 | See | | | |
| Germany DKMS - China minority | | 0.0012 | | 1282 | See | | | |
| China Marrow Donor Registry | | 0.0010 | | 600 | See | | | |
| United Arab Emirates Pop 1 | | 0.0010 | | 570 | See | | |
|
| Taiwan Tzu Chi Cord Blood Bank | | 0.0010 | | 710 | See | | | |
| Hong Kong Chinese BMDR | | 0.0007 | | 7595 | See | | |
|
| Taiwan Tzu Chi Morrow Donor Registry | | 0.0005 | | 46682 | See | | | |
| Hong Kong Chinese cord blood registry | | 0.0004 | | 3892 | See | | |
|
| China Zhejiang Han | | 0.0003 | | 1734 | See | | |
|
| India Tamil Nadu | | 0.0003 | | 2492 | See | | |
|
| Saudi Arabia pop 6 (G) | | 0.0002 | | 28927 | See | | | |
| USA NMDP Chinese | | 0.0002 | | 99672 | See | | | |
| Germany DKMS - Turkey minority | | 0.0001 | | 4856 | See | | | |
| China Hubei Han | 0.0 | 0.0001 | | 3732 | See | | |
|
| India West UCBB | 0.0 | 0.0001 | | 5829 | See | | |
|
| USA NMDP Mexican or Chicano | | 0.0000 | | 261235 | See | | | |
| USA NMDP South Asian Indian | | 0.0000 | | 185391 | See | | | |
| USA NMDP Hispanic South or Central American | | 0.0000 | | 146714 | See | | | |
| Germany DKMS - German donors | | 0.0000 | | 3456066 | See | | |
|
| USA NMDP Middle Eastern or North Coast of Africa | | 0.0000 | | 70890 | See | | | |
| USA NMDP Caribean Hispanic | | 0.0000 | | 115374 | See | | | |
| USA NMDP African American pop 2 | | 0.0000 | | 416581 | See | | | |
| USA NMDP Korean | | 0.0000 | | 77584 | See | | | |
| USA NMDP European Caucasian | | 0.0000 | | 1242890 | See | | | |
| USA North American Native | | 0.0000 | | 187 | See | | | |
| USA Hispanic pop 2 | | 0.0000 | | 1999 | See | | | |
| South Africa Natal Zulu | 0.0 | 0.0000 | | 100 | See | | | |
| USA Caucasian Bethesda | 0.0 | 0.0000 | | 307 | See | | | |
| USA African American Bethesda | 0.0 | 0.0000 | | 187 | See | | | |
| USA Philadelphia Caucasian | 0.0 | 0.0000 | | 141 | See | | | |
| USA African American pop 4 | | 0.0000 | | 2411 | See | | | |
| Taiwan Minnan pop 1 | 0.0 | 0.0000 | | 102 | See | | | |
| Singapore SGVP Chinese CHS | | 0.0000 | | 96 | See | | |
|
| Singapore SGVP. Indian INS | | 0.0000 | | 86 | See | | |
|
| Papua New Guinea Wosera Abelam | | 0.0000 | | 131 | See | | | |
| Singapore Chinese | 0.0 | 0.0000 | | 149 | See | | | |
| Romania | 0.0 | 0.0000 | | 348 | See | | | |
| Ireland Northern | 0.0 | 0.0000 | | 1000 | See | | | |
| Netherlands Leiden | | 0.0000 | | 1305 | See | | | |
| Oman | 0.0 | 0.0000 | | 118 | See | | | |
| Papua New Guinea Madang | | 0.0000 | | 65 | See | | | |
| Papua New Guinea East New Britain Rabaul | | 0.0000 | | 60 | See | | | |
| Papua New Guinea West Schrader Ranges Haruai | | 0.0000 | | 55 | See | | | |
| Taiwan Tzu Chi Morrow Donor Registry Aborigine | | 0.0000 | | 233 | See | | | |
| Taiwan Tsou | 0.0 | 0.0000 | | 51 | See | | | |
| Taiwan Rukai | 0.0 | 0.0000 | | 50 | See | | | |
| Taiwan Paiwan | 0.0 | 0.0000 | | 51 | See | | | |
| Taiwan Ami | 0.0 | 0.0000 | | 98 | See | | | |
| Taiwan Puyuma | 0.0 | 0.0000 | | 50 | See | | | |
| Taiwan Tao | 0.0 | 0.0000 | | 50 | See | | | |
| USA San Antonio Caucasian | | 0.0000 | | 222 | See | | | |
| USA South Texas Hispanic | | 0.0000 | | 194 | See | | | |
| USA Alaska Yupik | | 0.0000 | | 252 | See | | | |
| USA Caucasian pop 2 | | 0.0000 | | 265 | See | | | |
| USA African American | | 0.0000 | | 252 | See | | | |
| USA Hispanic | | 0.0000 | | 234 | See | | | |
| Taiwan Atayal | 0.0 | 0.0000 | | 106 | See | | | |
| Taiwan Taroko | 0.0 | 0.0000 | | 55 | See | | | |
| Taiwan Saisiat | 0.0 | 0.0000 | | 51 | See | | | |
| Taiwan Bunun | 0.0 | 0.0000 | | 101 | See | | | |
| Taiwan Pazeh | 0.0 | 0.0000 | | 55 | See | | | |
| Taiwan Siraya | 0.0 | 0.0000 | | 51 | See | | | |
| Taiwan Thao | 0.0 | 0.0000 | | 30 | See | | | |
| Australia New South Wales Caucasian | | 0.0000 | | 134 | See | | | |
| Burkina Faso Fulani | | 0.0000 | | 49 | See | | | |
| Burkina Faso Mossi | | 0.0000 | | 53 | See | | | |
| Burkina Faso Rimaibe | | 0.0000 | | 47 | See | | | |
| Bulgaria | | 0.0000 | | 55 | See | | | |
| Brazil Belo Horizonte Caucasian | 0.0 | 0.0000 | | 95 | See | | | |
| China North Han | | 0.0000 | | 105 | See | | | |
| Germany pop 8 | | 0.0000 | | 39689 | See | | | |
| China Tibet Region Tibetan | | 0.0000 | | 158 | See | | | |
| Cuba Mixed Race | 0.0 | 0.0000 | | 42 | See | | | |
| Cuba Caucasian | 0.0 | 0.0000 | | 70 | See | | | |
| Czech Republic | | 0.0000 | | 106 | See | | | |
| Italy Bergamo | 0.0 | 0.0000 | | 101 | See | | | |
| South Korea pop 3 | | 0.0000 | | 485 | See | | | |
| Morocco Settat Chaouya | 0.0 | 0.0000 | | 98 | See | | | |
| Morocco Nador Metalsa pop 2 | | 0.0000 | | 73 | See | | | |
| Mexico Mestizo | 0.0 | 0.0000 | | 41 | 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 Baja California, Tijuana | | 0.0000 | | 25 | 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 | | |
|
| Mexico Veracruz Rural | | 0.0000 | | 539 | See | | |
|
| Mexico Hidalgo Rural | | 0.0000 | | 81 | See | | |
|
| Mexico Mexico City Metropolitan Area Rural | | 0.0000 | | 150 | See | | |
|
| Mexico Tlaxcala Rural | | 0.0000 | | 830 | See | | |
|
| Mexico Puebla Rural | | 0.0000 | | 833 | See | | |
|
| Mexico Oaxaca Rural | | 0.0000 | | 485 | 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 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 Jalisco Rural | | 0.0000 | | 585 | See | | |
|
| Mexico Michoacan Rural | | 0.0000 | | 348 | 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, 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 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 Guanajuato, Guanajuato city | | 0.0000 | | 22 | See | | |
|
| Mexico Michoacan, Morelia | | 0.0000 | | 150 | See | | |
|
| Mexico Jalisco, Zapopan | | 0.0000 | | 168 | See | | |
|
| Mexico Jalisco, Tonala | | 0.0000 | | 35 | See | | |
|
| Mexico Jalisco, Tlaquepaque | | 0.0000 | | 39 | See | | |
|
| Mexico Jalisco, Tlajomulco | | 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 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 Mexico City South | | 0.0000 | | 52 | See | | |
|
| Mexico Mexico City North | | 0.0000 | | 751 | See | | |
|
| Mexico Mexico City East | | 0.0000 | | 79 | See | | |
|
| Mexico Mexico City Center | | 0.0000 | | 152 | See | | |
|
| Mexico Hidalgo, Pachuca | | 0.0000 | | 41 | See | | |
|
| Mexico Veracruz, Xalapa | | 0.0000 | | 187 | 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 Puebla, Puebla city | | 0.0000 | | 1994 | See | | |
|
| Mexico Tlaxcala, Tlaxcala city | | 0.0000 | | 181 | 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.