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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 |
801 |
B*52:01:02 | | Taiwan Tsou | 0.0 | 0 | | 51 | See | | | |
802 |
B*52:01:03 | | China Guangdong Province Meizhou Han | | 0.0050 | | 100 | See | | | |
803 |
B*52:01:03 | | Bulgaria | | 0 | | 55 | See | | | |
804 |
B*52:01:03 | | China North Han | | 0 | | 105 | See | | | |
805 |
B*52:01:03 | | Italy Bergamo | 0.0 | 0 | | 101 | See | | | |
806 |
B*52:01:03 | | Morocco Nador Metalsa pop 2 | | 0 | | 73 | See | | | |
807 |
B*52:01:03 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
808 |
B*52:01:03 | | South Korea pop 3 | | 0 | | 485 | See | | | |
809 |
B*52:01:04 | | Bulgaria | | 0 | | 55 | See | | | |
810 |
B*52:01:04 | | China North Han | | 0 | | 105 | See | | | |
811 |
B*52:01:04 | | Italy Bergamo | 0.0 | 0 | | 101 | See | | | |
812 |
B*52:01:04 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
813 |
B*52:01:05 | | Saudi Arabia pop 5 | 0.6 | 0.0032 | | 158 | See | | | |
814 |
B*52:01:05 | | USA NMDP Black South or Central American | | 0.0026 | | 4,889 | See | | | |
815 |
B*52:01:05 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
816 |
B*52:01:06 | | USA NMDP Black South or Central American | | 0.0001 | | 4,889 | See | | | |
817 |
B*52:01:11 | | USA NMDP Black South or Central American | | 0.0254 | | 4,889 | See | | | |
818 |
B*52:02 | | Greece pop 8 | 1.2 | 0.0060 | | 83 | See | | | |
819 |
B*52:02 | | Mexico Chihuahua Chihuahua City Pop 2 | 1.1 | 0.0057 | | 88 | See | | |
|
820 |
B*52:02 | | USA South Dakota Lakota Sioux | | 0.0020 | | 302 | See | | | |
821 |
B*52:02 | | Mexico Mexico City Tlalpan | 0.3 | 0.0015 | | 330 | See | | |
|
822 |
B*52:02 | | USA NMDP Hispanic South or Central American | | 0.0001 | | 146,714 | See | | | |
823 |
B*52:02 | | Israel YemenJews | | 0.0000320 | | 15,542 | See | | |
|
824 |
B*52:02 | | USA NMDP Caribean Hispanic | | 0.0000090 | | 115,374 | See | | | |
825 |
B*52:02 | | USA NMDP Mexican or Chicano | | 0.0000020 | | 261,235 | See | | | |
826 |
B*52:02 | | USA NMDP African American pop 2 | | 0.0000010 | | 416,581 | See | | | |
827 |
B*52:02 | | USA NMDP European Caucasian | | 0.0000008 | | 1,242,890 | See | | | |
828 |
B*52:02 | | Bulgaria | | 0 | | 55 | See | | | |
829 |
B*52:02 | | China North Han | | 0 | | 105 | See | | | |
830 |
B*52:02 | | China Tibet Region Tibetan | | 0 | | 158 | See | | | |
831 |
B*52:02 | | Croatia | | 0 | | 150 | See | | | |
832 |
B*52:02 | | Germany DKMS - German donors | | 0 | | 3,456,066 | See | | |
|
833 |
B*52:02 | | Italy Bergamo | 0.0 | 0 | | 101 | See | | | |
834 |
B*52:02 | | Italy North pop 3 | 0.0 | 0 | | 97 | See | | | |
835 |
B*52:02 | | Morocco Nador Metalsa pop 2 | | 0 | | 73 | See | | | |
836 |
B*52:02 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
837 |
B*52:02 | | Netherlands Leiden | | 0 | | 1,305 | See | | | |
838 |
B*52:02 | | South Korea pop 3 | | 0 | | 485 | See | | | |
839 |
B*52:02 | | USA African American Bethesda | 0.0 | 0 | | 187 | See | | | |
840 |
B*52:02 | | USA Alaska Yupik | | 0 | | 252 | See | | | |
841 |
B*52:02 | | USA Caucasian Bethesda | 0.0 | 0 | | 307 | See | | | |
842 |
B*52:02 | | USA Philadelphia Caucasian | 0.0 | 0 | | 141 | See | | | |
843 |
B*52:02 | | USA San Antonio Caucasian | | 0 | | 222 | See | | | |
844 |
B*52:02 | | USA South Texas Hispanic | | 0 | | 194 | See | | | |
845 |
B*52:03 | | USA NMDP Mexican or Chicano | | 0.0000340 | | 261,235 | See | | | |
846 |
B*52:03 | | USA NMDP Hispanic South or Central American | | 0.0000240 | | 146,714 | See | | | |
847 |
B*52:03 | | USA NMDP Southeast Asian | | 0.0000100 | | 27,978 | See | | | |
848 |
B*52:03 | | Bulgaria | | 0 | | 55 | See | | | |
849 |
B*52:03 | | China North Han | | 0 | | 105 | See | | | |
850 |
B*52:03 | | China Tibet Region Tibetan | | 0 | | 158 | See | | | |
851 |
B*52:03 | | Croatia | | 0 | | 150 | See | | | |
852 |
B*52:03 | | Italy Bergamo | 0.0 | 0 | | 101 | See | | | |
853 |
B*52:03 | | Italy North pop 3 | 0.0 | 0 | | 97 | See | | | |
854 |
B*52:03 | | Morocco Nador Metalsa pop 2 | | 0 | | 73 | See | | | |
855 |
B*52:03 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
856 |
B*52:03 | | Netherlands Leiden | | 0 | | 1,305 | See | | | |
857 |
B*52:03 | | South Korea pop 3 | | 0 | | 485 | See | | | |
858 |
B*52:03 | | USA African American Bethesda | 0.0 | 0 | | 187 | See | | | |
859 |
B*52:03 | | USA Caucasian Bethesda | 0.0 | 0 | | 307 | See | | | |
860 |
B*52:03 | | USA Philadelphia Caucasian | 0.0 | 0 | | 141 | See | | | |
861 |
B*52:03 | | USA San Antonio Caucasian | | 0 | | 222 | See | | | |
862 |
B*52:03 | | USA South Texas Hispanic | | 0 | | 194 | See | | | |
863 |
B*52:04 | | Switzerland Luzern | | 0.0056 | | 1,553 | See | | | |
864 |
B*52:04 | | India East UCBB | 1.0 | 0.0052 | | 2,403 | See | | |
|
865 |
B*52:04 | | India Central UCBB | 0.9 | 0.0044 | | 4,204 | See | | |
|
866 |
B*52:04 | | India West UCBB | 0.8 | 0.0039 | | 5,829 | See | | |
|
867 |
B*52:04 | | India North UCBB | 0.7 | 0.0037 | | 5,849 | See | | |
|
868 |
B*52:04 | | India Northeast UCBB | 0.7 | 0.0034 | | 296 | See | | |
|
869 |
B*52:04 | | India South UCBB | 0.2 | 0.0011 | | 11,446 | See | | |
|
870 |
B*52:04 | | USA NMDP South Asian Indian | | 0.0003 | | 185,391 | See | | | |
871 |
B*52:04 | | USA NMDP Southeast Asian | | 0.0003 | | 27,978 | See | | | |
872 |
B*52:04 | | India Tamil Nadu | | 0.0002 | | 2,492 | See | | |
|
873 |
B*52:04 | | USA NMDP Hawaiian or other Pacific Islander | | 0.0000430 | | 11,499 | See | | | |
874 |
B*52:04 | | Saudi Arabia pop 6 (G) | | 0.0000170 (*) | | 28,927 | See | | | |
875 |
B*52:04 | | USA NMDP European Caucasian | | 0.0000004 | | 1,242,890 | See | | | |
876 |
B*52:04 | | Bulgaria | | 0 | | 55 | See | | | |
877 |
B*52:04 | | China North Han | | 0 | | 105 | See | | | |
878 |
B*52:04 | | China Tibet Region Tibetan | | 0 | | 158 | See | | | |
879 |
B*52:04 | | Croatia | | 0 | | 150 | See | | | |
880 |
B*52:04 | | Germany DKMS - German donors | | 0 | | 3,456,066 | See | | |
|
881 |
B*52:04 | | Italy Bergamo | 0.0 | 0 | | 101 | See | | | |
882 |
B*52:04 | | Italy North pop 3 | 0.0 | 0 | | 97 | See | | | |
883 |
B*52:04 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
884 |
B*52:04 | | Netherlands Leiden | | 0 | | 1,305 | See | | | |
885 |
B*52:04 | | Switzerland Aargau-Solothurn | | 0 | | 1,838 | See | | | |
886 |
B*52:04 | | Switzerland Basel | | 0 | | 1,888 | See | | | |
887 |
B*52:04 | | Switzerland Bern | | 0 | | 3,545 | See | | | |
888 |
B*52:04 | | Switzerland Geneva pop 2 | | 0 | | 1,267 | See | | | |
889 |
B*52:04 | | Switzerland Graubunden | | 0 | | 759 | See | | | |
890 |
B*52:04 | | Switzerland Lausanne | | 0 | | 993 | See | | | |
891 |
B*52:04 | | Switzerland Lugano | | 0 | | 1,169 | See | | | |
892 |
B*52:04 | | Switzerland Sion | | 0 | | 832 | See | | | |
893 |
B*52:04 | | Switzerland St Gallen | | 0 | | 2,113 | See | | | |
894 |
B*52:04 | | Switzerland Zurich | | 0 | | 4,875 | See | | | |
895 |
B*52:04 | | USA African American Bethesda | 0.0 | 0 | | 187 | See | | | |
896 |
B*52:04 | | USA Caucasian Bethesda | 0.0 | 0 | | 307 | See | | | |
897 |
B*52:04 | | USA Philadelphia Caucasian | 0.0 | 0 | | 141 | See | | | |
898 |
B*52:05 | | Switzerland Sion | | 0.0024 | | 832 | See | | | |
899 |
B*52:05 | | Japan pop 16 | | 0.0000500 | | 18,604 | See | | | |
900 |
B*52:05 | | USA NMDP Mexican or Chicano | | 0.0000020 | | 261,235 | 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 801 to 900
(from 995) records |
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