Population |
Phenotype Frequency (%) |
Allele Frequency (in_decimals) |
Sample Size |
IMGT/HLA¹ Database |
Distribution² |
Haplotype³ Association |
Notesª |
 | India Northeast Shia | | 0.0450 |  | 190 | See |  |  | |
 | China Urumqi Han | | 0.0250 |  | 59 | See |  |  | |
 | China Urumqi Kazak | | 0.0240 |  | 42 | See |  |  | |
 | India Northeast Sunni | | 0.0210 |  | 188 | See |  |  | |
 | USA Philippines | | 0.0190 |  | 105 | See |  |  | |
 | India Northeast Vaish | | 0.0150 |  | 198 | See |  |  | |
 | Switzerland Graubunden | | 0.0137 |  | 759 | See |  |  | |
 | Russia, South Ural, Chelyabinsk region, Nagaybaks | 2.7 | 0.0130 |  | 112 | See |  |  |
|
 | Brazil Southeast Caucasian | 1.9 | 0.0100 |  | 103 | See |  |  | |
 | Brazil Rio de Janeiro Black | | 0.0082 |  | 68 | See |  |  |
|
 | Brazil Terena | 1.7 | 0.0080 |  | 60 | See |  |  | |
 | India North pop 2 | | 0.0080 |  | 72 | See |  |  | |
 | Russia Bashkortostan, Tatars | 1.6 | 0.0078 |  | 192 | See |  |  |
|
 | Switzerland Lausanne | | 0.0071 |  | 993 | See |  |  | |
 | Morocco Settat Chaouya | 1.2 | 0.0060 |  | 98 | See |  |  | |
 | Morocco Atlantic Coast Chaouya | | 0.0060 |  | 98 | See |  |  | |
 | Vietnam HoaBinh Muong | | 0.0060 |  | 83 | See |  |  | |
 | Switzerland Geneva pop 2 | | 0.0059 |  | 1267 | See |  |  | |
 | Switzerland Zurich | | 0.0058 |  | 4875 | See |  |  | |
 | India Uttar Pradesh | | 0.0050 |  | 202 | See |  |  | |
 | India Northeast Kayastha | | 0.0050 |  | 190 | See |  |  | |
 | India Northeast Rastogi | | 0.0050 |  | 196 | See |  |  | |
 | USA San Francisco Caucasian | | 0.0050 |  | 220 | See |  |  | |
 | Slovenia | 1.0 | 0.0050 |  | 100 | See |  |  | |
 | Poland | | 0.0050 |  | 200 | See |  |  | |
 | Germany pop 3 | 0.9 | 0.0045 |  | 111 | See |  |  | |
 | Switzerland St Gallen | | 0.0043 |  | 2113 | See |  |  | |
 | China Wuhan | 0.8 | 0.0040 |  | 121 | See |  |  | |
 | India Lucknow | 0.8 | 0.0040 |  | 123 | See |  |  | |
 | Ireland South | 0.8 | 0.0040 |  | 250 | See |  |  | |
 | Sweden Southern Sami | | 0.0040 |  | 130 | See |  |  | |
 | USA Philadelphia Caucasian | 0.7 | 0.0040 |  | 141 | See |  |  | |
 | Ireland Northern pop 2 | 0.8 | 0.0040 |  | 122 | See |  |  | |
 | Russia Karelia | | 0.0038 |  | 1075 | See |  |  |
|
 | Saudi Arabia pop 5 | 0.6 | 0.0032 |  | 158 | See |  |  | |
 | Italy Central | | 0.0030 |  | 380 | See |  |  | |
 | South Africa Worcester | 1.0 | 0.0030 |  | 159 | See |  |  |
|
 | England pop 6 | 0.6 | 0.0030 |  | 177 | See |  |  | |
 | India Karnataka Kannada Speaking | 0.6 | 0.0030 |  | 174 | See |  |  |
|
 | India Northeast Mathur | | 0.0030 |  | 155 | See |  |  | |
 | Poland BMR | 0.5 | 0.0027 |  | 23595 | See |  |  |
|
 | Russia Nizhny Novgorod, Russians | 0.5 | 0.0027 |  | 1510 | See |  |  |
|
 | Saudi Arabia pop 6 (G) | | 0.0026 |  | 28927 | See |  |  | |
 | Netherlands | 0.5 | 0.0025 |  | 447 | See |  |  | |
 | Netherlands Leiden | | 0.0020 |  | 1305 | See |  |  | |
 | USA Alaska Yupik | | 0.0020 |  | 252 | See |  |  | |
 | Turkey pop 1 | | 0.0020 |  | 250 | See |  |  | |
 | USA NMDP Caribean Indian | | 0.0020 |  | 14339 | See |  |  | |
 | England North West | 0.3 | 0.0020 |  | 298 | See |  |  | |
 | Austria | 0.5 | 0.0020 |  | 200 | See |  |  | |
 | Latvia | | 0.0019 |  | 266 | See |  |  |
|
 | Czech Republic NMDR | | 0.0016 |  | 5099 | See |  |  | |
 | Switzerland Bern | | 0.0015 |  | 3545 | See |  |  | |
 | Pakistan Mixed Punjabi | 0.2 | 0.0013 |  | 389 | See |  |  |
|
 | Germany DKMS - German donors | | 0.0013 |  | 3456066 | See |  |  |
|
 | Belgium | 0.2 | 0.0011 |  | 31412 | See |  |  |
|
 | India Tamil Nadu | | 0.0010 |  | 2492 | See |  |  |
|
 | China Marrow Donor Registry | | 0.0010 |  | 600 | See |  |  | |
 | China Inner Mongolia Autonomous Region Northeast | 0.2 | 0.0010 |  | 496 | See |  |  | |
 | Sri Lanka Colombo | 0.1 | 0.0010 |  | 714 | See |  |  |
|
 | Japan pop 2 | | 0.0010 |  | 916 | See |  |  | |
 | USA San Diego | 0.2 | 0.0010 |  | 496 | See |  |  |
|
 | USA NMDP American Indian South or Central America | | 0.0010 |  | 5926 | See |  |  | |
 | USA NMDP Alaska Native or Aleut | | 0.0010 |  | 1376 | See |  |  | |
 | Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, | 0.2 | 0.0009 |  | 4335 | See |  |  |
|
 | Germany DKMS - Turkey minority | | 0.0007 |  | 4856 | See |  |  | |
 | China Zhejiang Han | | 0.0006 |  | 1734 | See |  |  |
|
 | Germany DKMS - Italy minority | | 0.0004 |  | 1159 | See |  |  | |
 | USA Hispanic pop 2 | | 0.0005 |  | 1999 | See |  |  | |
 | Colombia Bogotá Cord Blood | 0.1 | 0.0003 |  | 1463 | See |  |  | |
 | USA NMDP Hispanic South or Central American | | 0.0003 |  | 146714 | See |  |  | |
 | India North UCBB | 0.0 | 0.0002 |  | 5849 | See |  |  |
|
 | India South UCBB | 0.0 | 0.0002 |  | 11446 | See |  |  |
|
 | Spain Murcia | | 0.0000 |  | 173 | See |  |  | |
 | Israel Moroccan Jews | | 0.0000 |  | 113 | See |  |  | |
 | Israel Ashkenazi Jews pop 2 | | 0.0000 |  | 132 | 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 |  |  | |
 | India Northeast Lachung | | 0.0000 |  | 58 | See |  |  | |
 | India Northeast Mech | | 0.0000 |  | 63 | See |  |  | |
 | Denmark | | 0.0000 |  | 55 | See |  |  | |
 | Algeria pop 2 | 0.0 | 0.0000 |  | 106 | See |  |  | |
 | Ecuador African | | 0.0000 |  | 58 | See |  |  | |
 | France Ceph | | 0.0000 |  | 124 | See |  |  | |
 | France West | 0.0 | 0.0000 |  | 100 | See |  |  | |
 | Gambia | | 0.0000 |  | 146 | See |  |  | |
 | India Bombay | | 0.0000 |  | 59 | See |  |  | |
 | India Northeast Rajbanshi | | 0.0000 |  | 98 | See |  |  | |
 | China Urumqi Uyghur | 0.0 | 0.0000 |  | 57 | See |  |  | |
 | Cameroon Saa | | 0.0000 |  | 172 | See |  |  | |
 | Congo Kinshasa Bantu | 0.0 | 0.0000 |  | 90 | See |  |  | |
 | Colombia Bogota and Medellin Mestizo | | 0.0000 |  | 65 | See |  |  | |
 | Switzerland Sion | | 0.0000 |  | 832 | See |  |  | |
 | Switzerland Luzern | | 0.0000 |  | 1553 | See |  |  | |
 | Switzerland Lugano | | 0.0000 |  | 1169 | See |  |  | |
 | Brazil Guarani Nandeva | | 0.0000 |  | 86 | See |  |  | |
 | Brazil North East Mixed | | 0.0000 |  | 205 | See |  |  | |
 | Brazil Kaingang | | 0.0000 |  | 235 | See |  |  | |
 | Brazil Guarani M bya | | 0.0000 |  | 93 | See |  |  | |
 | Brazil Southeast Mixed Race | 0.0 | 0.0000 |  | 42 | See |  |  | |
 | Argentina Gran Chaco Eastern Toba | | 0.0000 |  | 135 | See |  |  | |
 | Argentina Gran Chaco Mataco Wichi | | 0.0000 |  | 49 | See |  |  | |
 | Argentina Gran Chaco Western Toba Pilaga | | 0.0000 |  | 19 | See |  |  | |
 | Switzerland Basel | | 0.0000 |  | 1888 | See |  |  | |
 | Brazil Central Plateau Xavante | | 0.0000 |  | 74 | See |  |  | |
 | Central African Republic Aka Pygmy | 0.0 | 0.0000 |  | 93 | See |  |  | |
 | Canada British Columbia Athabaskan | | 0.0000 |  | 62 | See |  |  | |
 | Switzerland Aargau-Solothurn | | 0.0000 |  | 1838 | See |  |  | |
 | USA African American pop 4 | | 0.0000 |  | 2411 | See |  |  | |
 | USA Asian pop 2 | | 0.0000 |  | 1772 | See |  |  | |
 | Uganda Baganda | | 0.0000 |  | 47 | See |  |  | |
 | USA San Antonio Caucasian | | 0.0000 |  | 222 | See |  |  | |
 | USA South Texas Hispanic | | 0.0000 |  | 194 | See |  |  | |
 | Sweden | | 0.0000 |  | 99 | See |  |  | |
 | Russia Tuva pop 2 | | 0.0000 |  | 169 | See |  |  | |
 | South Korea pop 3 | | 0.0000 |  | 485 | See |  |  | |
 | Italy pop 3 | | 0.0000 |  | 179 | See |  |  | |
 | Italy pop 5 | | 0.0000 |  | 975 | See |  |  | |
 | Japan Fukuoka | | 0.0000 |  | 86 | See |  |  | |
 | Papua New Guinea Highland pop2 | | 0.0000 |  | 28 | See |  |  | |
 | Mexico Highlands Mestizos | 0.0 | 0.0000 |  | 160 | See |  |  | |
 | Mexico Nuevo Leon Mestizo | 0.0 | 0.0000 |  | 40 | 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.