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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 |
23,101 |
A*33:01 | | India Delhi pop 2 | 1.1 | 0.0050 | | 90 | See | | | |
23,102 |
A*33:01 | | India East UCBB | 0.0400 | 0.0002 | | 2,403 | See | | |
|
23,103 |
A*33:01 | | India Khandesh Region Pawra | | 0 | | 50 | See | | | |
23,104 |
A*33:01 | | India Mumbai Maratha | | 0 | | 91 | See | | | |
23,105 |
A*33:01 | | India North UCBB | 0.1 | 0.0005 | | 5,849 | See | | |
|
23,106 |
A*33:01 | | India South UCBB | 0.0300 | 0.0002 | | 11,446 | See | | |
|
23,107 |
A*33:01 | | India Tamil Nadu | | 0.0011 | | 2,492 | See | | |
|
23,108 |
A*33:01 | | India West Bhil | | 0 | | 50 | See | | | |
23,109 |
A*33:01 | | India West Coast Parsi | | 0.0300 | | 50 | See | | | |
23,110 |
A*33:01 | | India West UCBB | 0.2 | 0.0009 | | 5,829 | See | | |
|
23,111 |
A*33:01 | | Iran Baloch | | 0.0280 | | 100 | See | | | |
23,112 |
A*33:01 | | Iran Gorgan | | 0.0310 | | 64 | See | | |
|
23,113 |
A*33:01 | | Iran Kurd pop 2 | | 0.0170 | | 60 | See | | |
|
23,114 |
A*33:01 | | Iran Saqqez-Baneh Kurds | | 0.0167 | | 60 | See | | |
|
23,115 |
A*33:01 | | Iran Tabriz Azeris | | 0.0567 | | 97 | See | | |
|
23,116 |
A*33:01 | | Iran Yazd | | 0.0089 | | 56 | See | | |
|
23,117 |
A*33:01 | | Ireland Northern | 1.3 | 0.0070 | | 1,000 | See | | | |
23,118 |
A*33:01 | | Ireland South | 0.8 | 0.0040 | | 250 | See | | | |
23,119 |
A*33:01 | | Israel Arab pop 2 | | 0.0325 | | 12,301 | See | | |
|
23,120 |
A*33:01 | | Israel Argentina Jews | | 0.0374 | | 4,307 | See | | |
|
23,121 |
A*33:01 | | Israel Ashkenazi and Non Ashkenazi Jews | | 0.0130 | | 146 | See | | | |
23,122 |
A*33:01 | | Israel Ashkenazi Jews pop 3 | | 0.0361 | | 4,625 | See | | |
|
23,123 |
A*33:01 | | Israel Bukhara Jews | | 0.0161 | | 2,317 | See | | |
|
23,124 |
A*33:01 | | Israel Druze | | 0.0483 | | 5,914 | See | | |
|
23,125 |
A*33:01 | | Israel Ethiopia Jews | | 0.0261 | | 5,928 | See | | |
|
23,126 |
A*33:01 | | Israel Georgia Jews | | 0.0244 | | 4,471 | See | | |
|
23,127 |
A*33:01 | | Israel Iran Jews | | 0.0177 | | 8,153 | See | | |
|
23,128 |
A*33:01 | | Israel Iraq Jews | | 0.0124 | | 13,270 | See | | |
|
23,129 |
A*33:01 | | Israel Kavkazi Jews | | 0.0826 | | 2,840 | See | | |
|
23,130 |
A*33:01 | | Israel Libya Jews | | 0.0253 | | 3,739 | See | | |
|
23,131 |
A*33:01 | | Israel Morocco Jews | | 0.0293 | | 36,718 | See | | |
|
23,132 |
A*33:01 | | Israel Poland Jews | | 0.0339 | | 13,871 | See | | |
|
23,133 |
A*33:01 | | Israel Tunisia Jews | | 0.0284 | | 9,070 | See | | |
|
23,134 |
A*33:01 | | Israel USA Jews | | 0.0336 | | 6,058 | See | | |
|
23,135 |
A*33:01 | | Israel USSR Jews | | 0.0330 | | 45,681 | See | | |
|
23,136 |
A*33:01 | | Israel YemenJews | | 0.0698 | | 15,542 | See | | |
|
23,137 |
A*33:01 | | Italy North pop 3 | 7.7 | 0.0380 | | 97 | See | | | |
23,138 |
A*33:01 | | Italy pop 5 | | 0.0200 | | 975 | See | | | |
23,139 |
A*33:01 | | Japan Okinawa Ryukyuan | | 0.0180 | | 143 | See | | | |
23,140 |
A*33:01 | | Japan pop 16 | | 0.0001 | | 18,604 | See | | | |
23,141 |
A*33:01 | | Jordan Amman | | 0.0350 | | 146 | See | | | |
23,142 |
A*33:01 | | Kenya | | 0.0070 | | 144 | See | | | |
23,143 |
A*33:01 | | Kenya Luo | | 0.0130 | | 265 | See | | | |
23,144 |
A*33:01 | | Kenya Nandi | | 0.0020 | | 240 | See | | | |
23,145 |
A*33:01 | | Kenya, Nyanza Province, Luo tribe | 2.0 | 0.0100 | | 100 | See | | |
|
23,146 |
A*33:01 | | Kosovo | 1.6 | 0.0081 | | 124 | See | | |
|
23,147 |
A*33:01 | | Madeira | | 0.0300 | | 185 | See | | | |
23,148 |
A*33:01 | | Malaysia Kelantan | 3.6 | 0.0180 | | 28 | See | | |
|
23,149 |
A*33:01 | | Malaysia Peninsular Chinese | 18.0 | 0.0979 | | 194 | See | | |
|
23,150 |
A*33:01 | | Malaysia Peninsular Indian | 9.2 | 0.0480 | | 271 | See | | |
|
23,151 |
A*33:01 | | Malaysia Peninsular Malay | 15.5 | 0.0841 | | 951 | See | | |
|
23,152 |
A*33:01 | | Mali Bandiagara | | 0.0180 | | 138 | See | | | |
23,153 |
A*33:01 | | Mexico Chiapas Lacandon Mayans | | 0.0046 | | 218 | See | | |
|
23,154 |
A*33:01 | | Mexico Chihuahua Chihuahua City Pop 2 | 3.4 | 0.0170 | | 88 | See | | |
|
23,155 |
A*33:01 | | Mexico Guadalajara Mestizo pop 2 | | 0.0050 | | 103 | See | | | |
23,156 |
A*33:01 | | Mexico Mestizo | 2.4 | 0.0120 | | 41 | See | | | |
23,157 |
A*33:01 | | Mexico Mexico City Mestizo pop 2 | | 0.0128 | | 234 | See | | | |
23,158 |
A*33:01 | | Mexico Mexico City Mestizo population | | 0.0070 | | 143 | See | | |
|
23,159 |
A*33:01 | | Mexico Mexico City Tlalpan | 3.9 | 0.0197 | | 330 | See | | |
|
23,160 |
A*33:01 | | Mexico Mixtec | | 0.0210 | | 97 | See | | | |
23,161 |
A*33:01 | | Mexico Oaxaca Jamiltepec Mixtec | | 0.0210 | | 96 | See | | |
|
23,162 |
A*33:01 | | Mexico Oaxaca Mixtec | | 0.0100 | | 103 | See | | | |
23,163 |
A*33:01 | | Mexico Oaxaca Zapotec | | 0 | | 90 | See | | | |
23,164 |
A*33:01 | | Mexico Veracruz Xalapa | 3.6 | 0.0179 | | 84 | See | | |
|
23,165 |
A*33:01 | | Mongolia Buryat | | 0.0460 | | 141 | See | | | |
23,166 |
A*33:01 | | Morocco Atlantic Coast Chaouya | | 0.0200 | | 98 | See | | | |
23,167 |
A*33:01 | | Morocco Nador Metalsa pop 2 | | 0.0550 | | 73 | See | | | |
23,168 |
A*33:01 | | Morocco Settat Chaouya | 4.0 | 0.0200 | | 98 | See | | | |
23,169 |
A*33:01 | | Netherlands Leiden | | 0.0030 | | 1,305 | See | | | |
23,170 |
A*33:01 | | Netherlands UMCU | 3.1 | 0.0156 | | 64 | See | | | |
23,171 |
A*33:01 | | Nicaragua Managua | 3.6 | 0.0195 | | 339 | See | | |
|
23,172 |
A*33:01 | | Oman | 2.5 | 0.0130 | | 118 | See | | | |
23,173 |
A*33:01 | | Pakistan Baloch | | 0.0240 | | 66 | See | | | |
23,174 |
A*33:01 | | Pakistan Brahui | | 0 | | 104 | See | | | |
23,175 |
A*33:01 | | Pakistan Burusho | | 0 | | 92 | See | | | |
23,176 |
A*33:01 | | Pakistan Kalash | | 0.0170 | | 69 | See | | | |
23,177 |
A*33:01 | | Pakistan Karachi Parsi | | 0.1220 | | 91 | See | | | |
23,178 |
A*33:01 | | Pakistan Mixed Pathan | | 0 | | 100 | See | | | |
23,179 |
A*33:01 | | Pakistan Mixed Sindhi | | 0 | | 101 | See | | | |
23,180 |
A*33:01 | | Panama | | 0.0362 | | 462 | See | | |
|
23,181 |
A*33:01 | | Philippines Ivatan | 0.0 | 0 | | 50 | See | | | |
23,182 |
A*33:01 | | Poland | | 0.0100 | | 200 | See | | | |
23,183 |
A*33:01 | | Poland DKMS | | 0.0056 | | 20,653 | See | | | |
23,184 |
A*33:01 | | Portugal Azores Terceira Island | 0.9 | 0.0044 | | 130 | See | | |
|
23,185 |
A*33:01 | | Portugal Center | | 0.0300 | | 50 | See | | | |
23,186 |
A*33:01 | | Portugal North | | 0.0760 | | 46 | See | | | |
23,187 |
A*33:01 | | Portugal South | | 0.0410 | | 49 | See | | | |
23,188 |
A*33:01 | | Romania | 2.0 | 0.0100 | | 348 | See | | | |
23,189 |
A*33:01 | | Russia Bering Island Aleuts | | 0.0144 | | 104 | See | | |
|
23,190 |
A*33:01 | | Russia Karelia | | 0.0094 | | 1,075 | See | | |
|
23,191 |
A*33:01 | | Russia Tundra Nentsi NA-DHS_1 (G) | 6.3 (*) | 0.0313 (*) | | 16 | See | | |
|
23,192 |
A*33:01 | | Sao Tome Island Angolar | | 0.0470 | | 32 | See | | | |
23,193 |
A*33:01 | | Sao Tome Island Forro | | 0.0230 | | 66 | See | | | |
23,194 |
A*33:01 | | Saudi Arabia Guraiat and Hail | 2.3 | 0.0120 | | 213 | See | | | |
23,195 |
A*33:01 | | Senegal Niokholo Mandenka | | 0.0270 | | 165 | See | | | |
23,196 |
A*33:01 | | Singapore Chinese | 0.0 | 0 | | 149 | See | | | |
23,197 |
A*33:01 | | Singapore Chinese Han | | 0.0060 | | 94 | See | | | |
23,198 |
A*33:01 | | South Africa Caucasians | | 0.0100 | | 102 | See | | | |
23,199 |
A*33:01 | | South Africa Natal Zulu | 0.0 | 0 | | 100 | See | | | |
23,200 |
A*33:01 | | South Africa Worcester | 1.0 | 0.0060 | | 159 | 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.