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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 |
1,301 |
A*02:07 | | Brazil Belo Horizonte Caucasian | 0.0 | 0 | | 95 | See | | | |
1,302 |
A*02:07 | | Bulgaria | | 0 | | 55 | See | | | |
1,303 |
A*02:07 | | Burkina Faso Fulani | | 0.0100 | | 49 | See | | | |
1,304 |
A*02:07 | | Burkina Faso Rimaibe | | 0 | | 47 | See | | | |
1,305 |
A*02:07 | | China Beijing | | 0.0670 | | 67 | See | | | |
1,306 |
A*02:07 | | China Beijing Shijiazhuang Tianjian Han | | 0.0770 | | 618 | See | | | |
1,307 |
A*02:07 | | China Guangxi Region Maonan | | 0.1340 | | 108 | See | | | |
1,308 |
A*02:07 | | China Guangzhou | | 0.0930 | | 102 | See | | | |
1,309 |
A*02:07 | | China Guizhou Province Bouyei | | 0.2270 | | 109 | See | | | |
1,310 |
A*02:07 | | China Guizhou Province Miao pop 2 | | 0.1650 | | 85 | See | | | |
1,311 |
A*02:07 | | China Guizhou Province Shui | | 0.1750 | | 153 | See | | | |
1,312 |
A*02:07 | | China Inner Mongolia Region | | 0.0250 | | 102 | See | | | |
1,313 |
A*02:07 | | China North Han | | 0.0430 | | 105 | See | | | |
1,314 |
A*02:07 | | China Qinghai Province Hui | | 0.0360 | | 110 | See | | | |
1,315 |
A*02:07 | | China Southwest Dai | | 0.1850 | | 124 | See | | | |
1,316 |
A*02:07 | | China Tibet Region Tibetan | | 0.0160 | | 158 | See | | | |
1,317 |
A*02:07 | | China Yunnan Province Han | | 0.1830 | | 101 | See | | | |
1,318 |
A*02:07 | | China Yunnan Province Jinuo | | 0.1880 | | 109 | See | | | |
1,319 |
A*02:07 | | China Yunnan Province Lisu | | 0.0220 | | 111 | See | | | |
1,320 |
A*02:07 | | China Yunnan Province Nu | | 0.0820 | | 107 | See | | | |
1,321 |
A*02:07 | | China Yunnan Province Wa | | 0.0080 | | 119 | See | | | |
1,322 |
A*02:07 | | Cuba Caucasian | 1.4 | 0.0070 | | 70 | See | | | |
1,323 |
A*02:07 | | Cuba Mixed Race | 0.0 | 0 | | 42 | See | | | |
1,324 |
A*02:07 | | Germany DKMS - China minority | | 0.0827 | | 1,282 | See | | | |
1,325 |
A*02:07 | | Germany DKMS - France minority | | 0.0004 | | 1,406 | See | | | |
1,326 |
A*02:07 | | Germany DKMS - Greece minority | | 0.0016 | | 1,894 | See | | | |
1,327 |
A*02:07 | | Germany DKMS - Romania minority | | 0.0004 | | 1,234 | See | | | |
1,328 |
A*02:07 | | Germany DKMS - Turkey minority | | 0.0021 | | 4,856 | See | | | |
1,329 |
A*02:07 | | Germany pop 6 | | 0.0001 | | 8,862 | See | | | |
1,330 |
A*02:07 | | Ireland Northern | 0.0 | 0 | | 1,000 | See | | | |
1,331 |
A*02:07 | | Italy Bergamo | 0.0 | 0 | | 101 | See | | | |
1,332 |
A*02:07 | | Italy North pop 3 | 0.0 | 0 | | 97 | See | | | |
1,333 |
A*02:07 | | Italy pop 5 | | 0.0010 | | 975 | See | | | |
1,334 |
A*02:07 | | Japan Central | | 0.0220 | | 371 | See | | | |
1,335 |
A*02:07 | | Japan Hokkaido Ainu | | 0.0100 | | 50 | See | | | |
1,336 |
A*02:07 | | Japan pop 3 | | 0.0340 | | 1,018 | See | | | |
1,337 |
A*02:07 | | Japan pop 5 | | 0.0400 | | 117 | See | | | |
1,338 |
A*02:07 | | Malaysia Jelebu Temuan | | 0.0420 | | 25 | See | | | |
1,339 |
A*02:07 | | Malaysia Perak Grik Jehai | | 0.0400 | | 25 | See | | | |
1,340 |
A*02:07 | | Malaysia Sarawak Bau Bidayuh | | 0.0200 | | 25 | See | | | |
1,341 |
A*02:07 | | Mexico Mestizo | 0.0 | 0 | | 41 | See | | | |
1,342 |
A*02:07 | | Morocco Nador Metalsa pop 2 | | 0 | | 73 | See | | | |
1,343 |
A*02:07 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
1,344 |
A*02:07 | | Oman | 0.0 | 0 | | 118 | See | | | |
1,345 |
A*02:07 | | Pakistan Baloch | | 0 | | 66 | See | | | |
1,346 |
A*02:07 | | Pakistan Brahui | | 0 | | 104 | See | | | |
1,347 |
A*02:07 | | Pakistan Burusho | | 0 | | 92 | See | | | |
1,348 |
A*02:07 | | Pakistan Kalash | | 0 | | 69 | See | | | |
1,349 |
A*02:07 | | Pakistan Karachi Parsi | | 0 | | 91 | See | | | |
1,350 |
A*02:07 | | Pakistan Mixed Pathan | | 0 | | 100 | See | | | |
1,351 |
A*02:07 | | Pakistan Mixed Sindhi | | 0 | | 101 | See | | | |
1,352 |
A*02:07 | | Poland DKMS | | 0.0004 | | 20,653 | See | | | |
1,353 |
A*02:07 | | Russia Tuva pop 2 | | 0.0160 | | 169 | See | | | |
1,354 |
A*02:07 | | Scotland Orkney | 0.0 | 0 | | 99 | See | | | |
1,355 |
A*02:07 | | Singapore Chinese | 24.2 | 0.1310 | | 149 | See | | | |
1,356 |
A*02:07 | | South Africa Natal Zulu | 0.0 | 0 | | 100 | See | | | |
1,357 |
A*02:07 | | South Korea pop 3 | | 0.0300 | | 485 | See | | | |
1,358 |
A*02:07 | | Taiwan Han Chinese | | 0.1120 | | 504 | See | | | |
1,359 |
A*02:07 | | Taiwan pop 2 | | 0.1380 | | 364 | See | | | |
1,360 |
A*02:07 | | Taiwan pop 3 | | 0.1160 | | 212 | See | | | |
1,361 |
A*02:07 | | Taiwan Tzu Chi Cord Blood Bank | | 0.0990 | | 710 | See | | | |
1,362 |
A*02:07 | | Thailand | | 0.1090 | | 142 | See | | | |
1,363 |
A*02:07 | | Thailand Northeast | | 0.1570 | | 66 | See | | | |
1,364 |
A*02:07 | | Thailand Northeast pop 2 | | 0.1440 | | 400 | See | | | |
1,365 |
A*02:07 | | USA African American pop 4 | | 0 | | 2,411 | See | | | |
1,366 |
A*02:07 | | USA Alaska Yupik | | 0 | | 252 | See | | | |
1,367 |
A*02:07 | | USA Asian pop 2 | | 0.0438 | | 1,772 | See | | | |
1,368 |
A*02:07 | | USA Hispanic pop 2 | | 0 | | 1,999 | See | | | |
1,369 |
A*02:07 | | Vietnam Hanoi Kinh pop 2 | | 0.0850 | | 170 | See | | | |
1,370 |
A*02:08 | | Brazil Belo Horizonte Caucasian | 0.0 | 0 | | 95 | See | | | |
1,371 |
A*02:08 | | Bulgaria | | 0 | | 55 | See | | | |
1,372 |
A*02:08 | | China Beijing Shijiazhuang Tianjian Han | | 0.0010 | | 618 | See | | | |
1,373 |
A*02:08 | | China North Han | | 0 | | 105 | See | | | |
1,374 |
A*02:08 | | China Tibet Region Tibetan | | 0 | | 158 | See | | | |
1,375 |
A*02:08 | | Cuba Caucasian | 0.0 | 0 | | 70 | See | | | |
1,376 |
A*02:08 | | Cuba Mixed Race | 0.0 | 0 | | 42 | See | | | |
1,377 |
A*02:08 | | Georgia Svaneti Region Svan | | 0.0130 | | 80 | See | | | |
1,378 |
A*02:08 | | Germany DKMS - France minority | | 0.0004 | | 1,406 | See | | | |
1,379 |
A*02:08 | | Germany DKMS - Romania minority | | 0.0004 | | 1,234 | See | | | |
1,380 |
A*02:08 | | Germany DKMS - Turkey minority | | 0.0011 | | 4,856 | See | | | |
1,381 |
A*02:08 | | Germany DKMS - United Kingdom minority | | 0.0005 | | 1,043 | See | | | |
1,382 |
A*02:08 | | Germany pop 6 | | 0.0002 | | 8,862 | See | | | |
1,383 |
A*02:08 | | Ireland Northern | 0.0 | 0 | | 1,000 | See | | | |
1,384 |
A*02:08 | | Italy Bergamo | 0.0 | 0 | | 101 | See | | | |
1,385 |
A*02:08 | | Italy North pop 3 | 0.0 | 0 | | 97 | See | | | |
1,386 |
A*02:08 | | Madeira | | 0.0050 | | 185 | See | | | |
1,387 |
A*02:08 | | Mexico Mestizo | 0.0 | 0 | | 41 | See | | | |
1,388 |
A*02:08 | | Morocco Nador Metalsa pop 2 | | 0 | | 73 | See | | | |
1,389 |
A*02:08 | | Morocco Settat Chaouya | 0.0 | 0 | | 98 | See | | | |
1,390 |
A*02:08 | | Oman | 0.9 | 0.0040 | | 118 | See | | | |
1,391 |
A*02:08 | | Pakistan Baloch | | 0 | | 66 | See | | | |
1,392 |
A*02:08 | | Pakistan Brahui | | 0 | | 104 | See | | | |
1,393 |
A*02:08 | | Pakistan Burusho | | 0 | | 92 | See | | | |
1,394 |
A*02:08 | | Pakistan Kalash | | 0 | | 69 | See | | | |
1,395 |
A*02:08 | | Pakistan Karachi Parsi | | 0 | | 91 | See | | | |
1,396 |
A*02:08 | | Pakistan Mixed Pathan | | 0 | | 100 | See | | | |
1,397 |
A*02:08 | | Pakistan Mixed Sindhi | | 0.0130 | | 101 | See | | | |
1,398 |
A*02:08 | | Poland DKMS | | 0.0002 | | 20,653 | See | | | |
1,399 |
A*02:08 | | Scotland Orkney | 0.0 | 0 | | 99 | See | | | |
1,400 |
A*02:08 | | Singapore Chinese | 0.0 | 0 | | 149 | 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 1,301 to 1,400
(from 60,683) records |
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