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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 |
2,701 |
A*03:01 | | Germany DKMS - Greece minority | | 0.0882 | | 1,894 | See | | | |
2,702 |
A*03:01 | | Germany DKMS - Italy minority | | 0.1123 | | 1,159 | See | | | |
2,703 |
A*03:01 | | Germany DKMS - Netherlands minority | | 0.1521 | | 1,374 | See | | | |
2,704 |
A*03:01 | | Germany DKMS - Portugal minority | | 0.1111 | | 1,176 | See | | | |
2,705 |
A*03:01 | | Germany DKMS - Romania minority | | 0.1175 | | 1,234 | See | | | |
2,706 |
A*03:01 | | Germany DKMS - Spain minority | | 0.1147 | | 1,107 | See | | | |
2,707 |
A*03:01 | | Germany DKMS - Turkey minority | | 0.0943 | | 4,856 | See | | | |
2,708 |
A*03:01 | | Germany DKMS - United Kingdom minority | | 0.1366 | | 1,043 | See | | | |
2,709 |
A*03:01 | | Germany pop 6 | | 0.1588 | | 8,862 | See | | | |
2,710 |
A*03:01 | | Ghana Ga-Adangbe | 19.1 | 0.0954 | | 131 | See | | | |
2,711 |
A*03:01 | | Greece pop 6 | | 0.0868 | | 242 | See | | | |
2,712 |
A*03:01 | | Guinea Bissau Balanta | | 0.0210 | | 48 | See | | | |
2,713 |
A*03:01 | | Guinea Bissau Bijago | | 0.0650 | | 23 | See | | | |
2,714 |
A*03:01 | | Guinea Bissau Fula | | 0.0160 | | 31 | See | | | |
2,715 |
A*03:01 | | Guinea Bissau Papel | | 0.0200 | | 25 | See | | | |
2,716 |
A*03:01 | | India Delhi pop 2 | 13.3 | 0.0720 | | 90 | See | | | |
2,717 |
A*03:01 | | India North pop 2 | | 0.0580 | | 72 | See | | | |
2,718 |
A*03:01 | | Indonesia Java Western | 4.7 | 0.0240 | | 236 | See | | | |
2,719 |
A*03:01 | | Ireland Northern | 26.3 | 0.1430 | | 1,000 | See | | | |
2,720 |
A*03:01 | | Italy North pop 3 | 19.2 | 0.0970 | | 97 | See | | | |
2,721 |
A*03:01 | | Italy pop 5 | | 0.1020 | | 975 | See | | | |
2,722 |
A*03:01 | | Japan Central | | 0.0040 | | 371 | See | | | |
2,723 |
A*03:01 | | Japan pop 3 | | 0.0020 | | 1,018 | See | | | |
2,724 |
A*03:01 | | Jordan Amman | | 0.0520 | | 146 | See | | | |
2,725 |
A*03:01 | | Kenya Luo | | 0.0360 | | 265 | See | | | |
2,726 |
A*03:01 | | Kenya Nandi | | 0.0310 | | 240 | See | | | |
2,727 |
A*03:01 | | Mali Bandiagara | | 0.0440 | | 138 | See | | | |
2,728 |
A*03:01 | | Mexico Mestizo | 4.9 | 0.0240 | | 41 | See | | | |
2,729 |
A*03:01 | | Mexico Mexico City Mestizo pop 2 | | 0.0321 | | 234 | See | | | |
2,730 |
A*03:01 | | Mexico Oaxaca Mixtec | | 0 | | 103 | See | | | |
2,731 |
A*03:01 | | Mexico Oaxaca Zapotec | | 0.0070 | | 90 | See | | | |
2,732 |
A*03:01 | | New Caledonia | | 0.0120 | | 65 | See | | | |
2,733 |
A*03:01 | | Oman | 9.3 | 0.0510 | | 118 | See | | | |
2,734 |
A*03:01 | | Pakistan Baloch | | 0.0630 | | 66 | See | | | |
2,735 |
A*03:01 | | Pakistan Brahui | | 0.0460 | | 104 | See | | | |
2,736 |
A*03:01 | | Pakistan Burusho | | 0.1300 | | 92 | See | | | |
2,737 |
A*03:01 | | Pakistan Kalash | | 0.0750 | | 69 | See | | | |
2,738 |
A*03:01 | | Pakistan Karachi Parsi | | 0.0110 | | 91 | See | | | |
2,739 |
A*03:01 | | Pakistan Mixed Pathan | | 0.0870 | | 100 | See | | | |
2,740 |
A*03:01 | | Pakistan Mixed Sindhi | | 0.0440 | | 101 | See | | | |
2,741 |
A*03:01 | | Papua New Guinea East New Britain Rabaul | | 0 | | 60 | See | | | |
2,742 |
A*03:01 | | Papua New Guinea Eastern Highlands Goroka Asaro | | 0 | | 57 | See | | | |
2,743 |
A*03:01 | | Papua New Guinea Karimui Plateau Pawaia | | 0 | | 80 | See | | | |
2,744 |
A*03:01 | | Papua New Guinea Madang | | 0 | | 65 | See | | | |
2,745 |
A*03:01 | | Papua New Guinea Wanigela Keapara | | 0 | | 66 | See | | | |
2,746 |
A*03:01 | | Papua New Guinea West Schrader Ranges Haruai | | 0 | | 55 | See | | | |
2,747 |
A*03:01 | | Papua New Guinea Wosera Abelam | | 0 | | 131 | See | | | |
2,748 |
A*03:01 | | Poland | | 0.1230 | | 200 | See | | | |
2,749 |
A*03:01 | | Poland DKMS | | 0.1315 | | 20,653 | See | | | |
2,750 |
A*03:01 | | Portugal Center | | 0.0900 | | 50 | See | | | |
2,751 |
A*03:01 | | Portugal North | | 0.0650 | | 46 | See | | | |
2,752 |
A*03:01 | | Portugal South | | 0.0820 | | 49 | See | | | |
2,753 |
A*03:01 | | Russia Tuva pop 2 | | 0.0690 | | 169 | See | | | |
2,754 |
A*03:01 | | Sao Tome Island Angolar | | 0.0310 | | 32 | See | | | |
2,755 |
A*03:01 | | Sao Tome Island Forro | | 0.0600 | | 66 | See | | | |
2,756 |
A*03:01 | | Senegal Niokholo Mandenka | | 0.0380 | | 165 | See | | | |
2,757 |
A*03:01 | | Singapore Chinese | 1.3 | 0.0070 | | 149 | See | | | |
2,758 |
A*03:01 | | South Africa Natal Zulu | 12.0 | 0.0600 | | 100 | See | | | |
2,759 |
A*03:01 | | South Korea pop 3 | | 0.0180 | | 485 | See | | | |
2,760 |
A*03:01 | | Sweden Northern Sami | | 0.3130 | | 154 | See | | | |
2,761 |
A*03:01 | | Sweden Southern Sami | | 0.2480 | | 130 | See | | | |
2,762 |
A*03:01 | | Taiwan Han Chinese | | 0.0060 | | 504 | See | | | |
2,763 |
A*03:01 | | Taiwan pop 2 | | 0.0020 | | 364 | See | | | |
2,764 |
A*03:01 | | Taiwan Tzu Chi Cord Blood Bank | | 0.0050 | | 710 | See | | | |
2,765 |
A*03:01 | | Thailand | | 0.0070 | | 142 | See | | | |
2,766 |
A*03:01 | | Tunisia | 13.0 | 0.0670 | | 100 | See | | | |
2,767 |
A*03:01 | | Uganda Kampala | | 0.0550 | | 161 | See | | | |
2,768 |
A*03:01 | | Uganda Kampala pop 2 | | 0.0430 | | 175 | See | | | |
2,769 |
A*03:01 | | USA African American pop 2 | | 0.0940 | | 149 | See | | | |
2,770 |
A*03:01 | | USA African American pop 4 | | 0.0813 | | 2,411 | See | | | |
2,771 |
A*03:01 | | USA Alaska Yupik | | 0.0060 | | 252 | See | | | |
2,772 |
A*03:01 | | USA Arizona Gila River Amerindian | | 0.0020 | | 492 | See | | | |
2,773 |
A*03:01 | | USA Asian pop 2 | | 0.0260 | | 1,772 | See | | | |
2,774 |
A*03:01 | | USA Caucasian pop 3 | | 0.1080 | | 88 | See | | | |
2,775 |
A*03:01 | | USA Caucasian pop 4 | | 0.1383 | | 1,070 | See | | | |
2,776 |
A*03:01 | | USA Hispanic pop 2 | | 0.0791 | | 1,999 | See | | | |
2,777 |
A*03:01 | | USA San Francisco Caucasian | | 0.1480 | | 220 | See | | | |
2,778 |
A*03:01 | | USA South Dakota Lakota Sioux | | 0.0170 | | 302 | See | | | |
2,779 |
A*03:01 | | Zambia Lusaka | | 0.0580 | | 44 | See | | | |
2,780 |
A*03:01:01 | | Bulgaria | | 0.0460 | | 55 | See | | | |
2,781 |
A*03:01:01 | | Cameroon Yaounde | | 0.0770 | | 92 | See | | | |
2,782 |
A*03:01:01 | | Cape Verde Northwestern Islands | | 0.1130 | | 62 | See | | | |
2,783 |
A*03:01:01 | | Cape Verde Southeastern Islands | | 0.0650 | | 62 | See | | | |
2,784 |
A*03:01:01 | | China Guizhou Province Bouyei | | 0 | | 109 | See | | | |
2,785 |
A*03:01:01 | | China Guizhou Province Miao pop 2 | | 0.0060 | | 85 | See | | | |
2,786 |
A*03:01:01 | | China Guizhou Province Shui | | 0 | | 153 | See | | | |
2,787 |
A*03:01:01 | | China Inner Mongolia Region | | 0.0440 | | 102 | See | | | |
2,788 |
A*03:01:01 | | China North Han | | 0.0290 | | 105 | See | | | |
2,789 |
A*03:01:01 | | China Qinghai Province Hui | | 0.0410 | | 110 | See | | | |
2,790 |
A*03:01:01 | | China Tibet Region Tibetan | | 0.0250 | | 158 | See | | | |
2,791 |
A*03:01:01 | | Guinea Bissau | | 0.0620 | | 65 | See | | | |
2,792 |
A*03:01:01 | | India Khandesh Region Pawra | | 0 | | 50 | See | | | |
2,793 |
A*03:01:01 | | India Mumbai Maratha | | 0.0930 | | 91 | See | | | |
2,794 |
A*03:01:01 | | India Tamil Nadu Nadar | | 0.2050 | | 61 | See | | | |
2,795 |
A*03:01:01 | | India West Bhil | | 0.0400 | | 50 | See | | | |
2,796 |
A*03:01:01 | | India West Coast Parsi | | 0 | | 50 | See | | | |
2,797 |
A*03:01:01 | | Iran Baloch | | 0.0560 | | 100 | See | | | |
2,798 |
A*03:01:01 | | Madeira | | 0.0700 | | 185 | See | | | |
2,799 |
A*03:01:01 | | Mexico Chihuahua Tarahumara | | 0.0110 | | 44 | See | | | |
2,800 |
A*03:01:01 | | Morocco Nador Metalsa pop 2 | | 0.0340 | | 73 | 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 2,701 to 2,800
(from 60,683) records |
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