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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 |
A*02:01:04 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
802 |
A*02:01:04 | | Saudi Arabia pop 5 | 0.6 | 0.0032 | | 158 | See | | | |
803 |
A*02:01:04 | | South Korea pop 3 | | 0 | | 485 | See | | | |
804 |
A*02:01:04 | | USA Mexican American Mestizo | | 0.0010 | | 553 | See | | | |
805 |
A*02:01:04 | | USA San Francisco Caucasian | | 0.0020 | | 220 | See | | | |
806 |
A*02:01:05 | | Bulgaria | | 0 | | 55 | See | | | |
807 |
A*02:01:05 | | China North Han | | 0 | | 105 | See | | | |
808 |
A*02:01:05 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
809 |
A*02:01:05 | | South Korea pop 3 | | 0 | | 485 | See | | | |
810 |
A*02:01:06 | | Bulgaria | | 0 | | 55 | See | | | |
811 |
A*02:01:06 | | China North Han | | 0 | | 105 | See | | | |
812 |
A*02:01:06 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
813 |
A*02:01:06 | | South Korea pop 3 | | 0 | | 485 | See | | | |
814 |
A*02:01:07 | | Bulgaria | | 0 | | 55 | See | | | |
815 |
A*02:01:07 | | China North Han | | 0 | | 105 | See | | | |
816 |
A*02:01:07 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
817 |
A*02:01:08 | | Bulgaria | | 0 | | 55 | See | | | |
818 |
A*02:01:08 | | China North Han | | 0 | | 105 | See | | | |
819 |
A*02:01:08 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
820 |
A*02:01:09 | | Bulgaria | | 0 | | 55 | See | | | |
821 |
A*02:01:09 | | China North Han | | 0 | | 105 | See | | | |
822 |
A*02:01:09 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
823 |
A*02:01:10 | | China North Han | | 0 | | 105 | See | | | |
824 |
A*02:01:10 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
825 |
A*02:01:11 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
826 |
A*02:01:12 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
827 |
A*02:01:13 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
828 |
A*02:01:14Q | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | |
|
829 |
A*02:01:15 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
830 |
A*02:01:17 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
831 |
A*02:01:18 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
832 |
A*02:01:19 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
833 |
A*02:01:21 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
834 |
A*02:01:22 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
835 |
A*02:01:23 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
836 |
A*02:01:24 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
837 |
A*02:01:25 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
838 |
A*02:01:26 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
839 |
A*02:01:27 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
840 |
A*02:01:28 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
841 |
A*02:01:29 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
842 |
A*02:01:30 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
843 |
A*02:01:31 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
844 |
A*02:01:32 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
845 |
A*02:01:33 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
846 |
A*02:01:34 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
847 |
A*02:01:35 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
848 |
A*02:01:36 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
849 |
A*02:01:36 | | Saudi Arabia pop 5 | 0.6 | 0.0032 | | 158 | See | | | |
850 |
A*02:01:37 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
851 |
A*02:01:38 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
852 |
A*02:01:39 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
853 |
A*02:01:40 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
854 |
A*02:01:41 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
855 |
A*02:01:42 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
856 |
A*02:02 | | Azores Central Islands | | 0.0180 | | 59 | See | | | |
857 |
A*02:02 | | Azores Oriental Islands | | 0.0130 | | 43 | See | | | |
858 |
A*02:02 | | Belgium | 1.0 | 0.0050 | | 99 | See | | | |
859 |
A*02:02 | | Brazil Belo Horizonte Caucasian | 0.0 | 0 | | 95 | See | | | |
860 |
A*02:02 | | Bulgaria | | 0 | | 55 | See | | | |
861 |
A*02:02 | | Burkina Faso Fulani | | 0 | | 49 | See | | | |
862 |
A*02:02 | | Burkina Faso Rimaibe | | 0.0530 | | 47 | See | | | |
863 |
A*02:02 | | Cameroon Baka Pygmy | | 0 | | 10 | See | | | |
864 |
A*02:02 | | Cameroon Bamileke | | 0.1040 | | 77 | See | | | |
865 |
A*02:02 | | Cameroon Beti | | 0.0600 | | 174 | See | | | |
866 |
A*02:02 | | Cameroon Sawa | | 0 | | 13 | See | | | |
867 |
A*02:02 | | Cameroon Yaounde | | 0.0820 | | 92 | See | | | |
868 |
A*02:02 | | Cape Verde Northwestern Islands | | 0.0080 | | 62 | See | | | |
869 |
A*02:02 | | Cape Verde Southeastern Islands | | 0.0240 | | 62 | See | | | |
870 |
A*02:02 | | China Inner Mongolia Region | | 0 | | 102 | See | | | |
871 |
A*02:02 | | China North Han | | 0 | | 105 | See | | | |
872 |
A*02:02 | | China Qinghai Province Hui | | 0.0140 | | 110 | See | | | |
873 |
A*02:02 | | China Tibet Region Tibetan | | 0 | | 158 | See | | | |
874 |
A*02:02 | | Cuba Caucasian | 0.0 | 0 | | 70 | See | | | |
875 |
A*02:02 | | Cuba Mixed Race | 2.4 | 0.0120 | | 42 | See | | | |
876 |
A*02:02 | | Georgia Svaneti Region Svan | | 0.0380 | | 80 | See | | | |
877 |
A*02:02 | | Germany DKMS - Austria minority | | 0.0006 | | 1,698 | See | | | |
878 |
A*02:02 | | Germany DKMS - Bosnia and Herzegovina minority | | 0.0015 | | 1,028 | See | | | |
879 |
A*02:02 | | Germany DKMS - Croatia minority | | 0.0002 | | 2,057 | See | | | |
880 |
A*02:02 | | Germany DKMS - France minority | | 0.0008 | | 1,406 | See | | | |
881 |
A*02:02 | | Germany DKMS - Greece minority | | 0.0013 | | 1,894 | See | | | |
882 |
A*02:02 | | Germany DKMS - Italy minority | | 0.0030 | | 1,159 | See | | | |
883 |
A*02:02 | | Germany DKMS - Netherlands minority | | 0.0004 | | 1,374 | See | | | |
884 |
A*02:02 | | Germany DKMS - Portugal minority | | 0.0051 | | 1,176 | See | | | |
885 |
A*02:02 | | Germany DKMS - Romania minority | | 0.0016 | | 1,234 | See | | | |
886 |
A*02:02 | | Germany DKMS - Spain minority | | 0.0014 | | 1,107 | See | | | |
887 |
A*02:02 | | Germany DKMS - Turkey minority | | 0.0019 | | 4,856 | See | | | |
888 |
A*02:02 | | Germany DKMS - United Kingdom minority | | 0.0010 | | 1,043 | See | | | |
889 |
A*02:02 | | Germany pop 6 | | 0.0005 | | 8,862 | See | | | |
890 |
A*02:02 | | Ghana Ga-Adangbe | 12.2 | 0.0649 | | 131 | See | | | |
891 |
A*02:02 | | Greece pop 6 | | 0.0021 | | 242 | See | | | |
892 |
A*02:02 | | Guinea Bissau | | 0.0620 | | 65 | See | | | |
893 |
A*02:02 | | Guinea Bissau Balanta | | 0.0630 | | 48 | See | | | |
894 |
A*02:02 | | Guinea Bissau Bijago | | 0.0870 | | 23 | See | | | |
895 |
A*02:02 | | Guinea Bissau Fula | | 0.0650 | | 31 | See | | | |
896 |
A*02:02 | | Guinea Bissau Papel | | 0.0800 | | 25 | See | | | |
897 |
A*02:02 | | India Delhi pop 2 | 3.3 | 0.0170 | | 90 | See | | | |
898 |
A*02:02 | | Ireland Northern | 0.0 | 0 | | 1,000 | See | | | |
899 |
A*02:02 | | Italy Bergamo | 0.0 | 0 | | 101 | See | | | |
900 |
A*02:02 | | Italy North pop 3 | 0.0 | 0 | | 97 | 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 60,683) records |
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