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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 |
301 |
A*01:01 | | Zimbabwe Harare Shona | | 0.0040 | | 230 | See | | | |
302 |
A*01:02 | | Argentina Rosario Toba | 1.2 | 0.0060 | | 86 | See | | | |
303 |
A*01:02 | | Belgium | 0.1 | 0.0006 | | 31,412 | See | | |
|
304 |
A*01:02 | | Brazil Barra Mansa Rio State Caucasian | | 0.0012 | | 405 | See | | |
|
305 |
A*01:02 | | Brazil Belo Horizonte Caucasian | 0.0 | 0 | | 95 | See | | | |
306 |
A*01:02 | | Brazil Rio de Janeiro Caucasian | | 0.0010 | | 521 | See | | |
|
307 |
A*01:02 | | Brazil Vale do Ribeira Quilombos | 0.0030 | 0 | | 144 | See | | | |
308 |
A*01:02 | | Bulgaria | | 0 | | 55 | See | | | |
309 |
A*01:02 | | Cameroon Baka Pygmy | | 0 | | 10 | See | | | |
310 |
A*01:02 | | Cameroon Bamileke | | 0 | | 77 | See | | | |
311 |
A*01:02 | | Cameroon Beti | | 0.0030 | | 174 | See | | | |
312 |
A*01:02 | | Cameroon Sawa | | 0 | | 13 | See | | | |
313 |
A*01:02 | | Cape Verde Northwestern Islands | | 0 | | 62 | See | | | |
314 |
A*01:02 | | Cape Verde Southeastern Islands | | 0.0160 | | 62 | See | | | |
315 |
A*01:02 | | Central African Republic Mbenzele Pygmy | 0.0 | 0 | | 36 | See | | | |
316 |
A*01:02 | | China Jiangsu Province Han | | 0.0018 | | 334 | See | | | |
317 |
A*01:02 | | China North Han | | 0 | | 105 | See | | | |
318 |
A*01:02 | | China Tibet Region Tibetan | | 0 | | 158 | See | | | |
319 |
A*01:02 | | Colombia Bogotá Cord Blood | 0.5 | 0.0027 | | 1,463 | See | | | |
320 |
A*01:02 | | Costa Rica African -Caribbean (G) | 2.0 (*) | 0.0100 (*) | | 102 | See | | |
|
321 |
A*01:02 | | Costa Rica Amerindians (G) | 1.6 (*) | 0.0080 (*) | | 125 | See | | |
|
322 |
A*01:02 | | Croatia | | 0 | | 150 | See | | | |
323 |
A*01:02 | | Croatia pop 4 | | 0.0001 | | 4,000 | See | | | |
324 |
A*01:02 | | Cuba Caucasian | 0.0 | 0 | | 70 | See | | | |
325 |
A*01:02 | | Cuba Mixed Race | 0.0 | 0 | | 42 | See | | | |
326 |
A*01:02 | | Czech Republic | | 0 | | 106 | See | | | |
327 |
A*01:02 | | Czech Republic NMDR | | 0.0001 | | 5,099 | See | | | |
328 |
A*01:02 | | France French Bone Marrow Donor Registry | | 0.0073 | | 42,623 | See | | | |
329 |
A*01:02 | | Germany DKMS - Croatia minority | | 0.0002 | | 2,057 | See | | | |
330 |
A*01:02 | | Germany DKMS - German donors | | 0.0000980 | | 3,456,066 | See | | |
|
331 |
A*01:02 | | Germany DKMS - Greece minority | | 0.0003 | | 1,894 | See | | | |
332 |
A*01:02 | | Germany DKMS - Italy minority | | 0.0022 | | 1,159 | See | | | |
333 |
A*01:02 | | Germany DKMS - Portugal minority | | 0.0013 | | 1,176 | See | | | |
334 |
A*01:02 | | Germany DKMS - Spain minority | | 0.0027 | | 1,107 | See | | | |
335 |
A*01:02 | | Germany DKMS - Turkey minority | | 0.0002 | | 4,856 | See | | | |
336 |
A*01:02 | | Germany DKMS - United Kingdom minority | | 0.0010 | | 1,043 | See | | | |
337 |
A*01:02 | | Germany pop 6 | | 0.0002 | | 8,862 | See | | | |
338 |
A*01:02 | | Germany pop 8 | | 0.0000900 | | 39,689 | See | | | |
339 |
A*01:02 | | Guinea Bissau | | 0.0080 | | 65 | See | | | |
340 |
A*01:02 | | Guinea Bissau Balanta | | 0.0210 | | 48 | See | | | |
341 |
A*01:02 | | Guinea Bissau Bijago | | 0 | | 23 | See | | | |
342 |
A*01:02 | | Guinea Bissau Fula | | 0 | | 31 | See | | | |
343 |
A*01:02 | | Guinea Bissau Papel | | 0.0200 | | 25 | See | | | |
344 |
A*01:02 | | Hong Kong Chinese | 0.0 | 0 | | 569 | See | | | |
345 |
A*01:02 | | India Delhi pop 2 | 6.7 | 0.0330 | | 90 | See | | | |
346 |
A*01:02 | | Iran Gorgan | | 0.0470 | | 64 | See | | |
|
347 |
A*01:02 | | Iran Kurd pop 2 | | 0.0250 | | 60 | See | | |
|
348 |
A*01:02 | | Iran Saqqez-Baneh Kurds | | 0.0250 | | 60 | See | | |
|
349 |
A*01:02 | | Iran Tabriz Azeris | | 0.0619 | | 97 | See | | |
|
350 |
A*01:02 | | Ireland Northern | 0.0 | 0 | | 1,000 | See | | | |
351 |
A*01:02 | | Israel Arab pop 2 | | 0.0000410 | | 12,301 | See | | |
|
352 |
A*01:02 | | Israel Argentina Jews | | 0.0000580 | | 4,307 | See | | |
|
353 |
A*01:02 | | Israel Bukhara Jews | | 0.0001 | | 2,317 | See | | |
|
354 |
A*01:02 | | Israel Georgia Jews | | 0.0000560 | | 4,471 | See | | |
|
355 |
A*01:02 | | Israel Iran Jews | | 0.0000200 | | 8,153 | See | | |
|
356 |
A*01:02 | | Israel Iraq Jews | | 0.0000190 | | 13,270 | See | | |
|
357 |
A*01:02 | | Israel Morocco Jews | | 0.0001 | | 36,718 | See | | |
|
358 |
A*01:02 | | Israel Poland Jews | | 0.0002 | | 13,871 | See | | |
|
359 |
A*01:02 | | Israel Tunisia Jews | | 0.0000140 | | 9,070 | See | | |
|
360 |
A*01:02 | | Israel USA Jews | | 0.0002 | | 6,058 | See | | |
|
361 |
A*01:02 | | Israel USSR Jews | | 0.0000770 | | 45,681 | See | | |
|
362 |
A*01:02 | | Israel YemenJews | | 0.0000640 | | 15,542 | See | | |
|
363 |
A*01:02 | | Italy North pop 3 | 0.0 | 0 | | 97 | See | | | |
364 |
A*01:02 | | Italy pop 5 | | 0.0030 | | 975 | See | | | |
365 |
A*01:02 | | Kenya Luo | | 0.0040 | | 265 | See | | | |
366 |
A*01:02 | | Kenya Nandi | | 0.0270 | | 240 | See | | | |
367 |
A*01:02 | | Madeira | | 0.0080 | | 185 | See | | | |
368 |
A*01:02 | | Mali Bandiagara | | 0.0110 | | 138 | See | | | |
369 |
A*01:02 | | Mexico Mestizo | 0.0 | 0 | | 41 | See | | | |
370 |
A*01:02 | | Mexico Mexico City Mestizo pop 2 | | 0.0043 | | 234 | See | | | |
371 |
A*01:02 | | Morocco Atlantic Coast Chaouya | | 0.0070 | | 98 | See | | | |
372 |
A*01:02 | | Morocco Nador Metalsa pop 2 | | 0 | | 73 | See | | | |
373 |
A*01:02 | | Morocco Settat Chaouya | 1.4 | 0.0070 | | 98 | See | | | |
374 |
A*01:02 | | Netherlands Leiden | | 0 | | 1,305 | See | | | |
375 |
A*01:02 | | Nicaragua Managua | 0.3 | 0.0015 | | 339 | See | | |
|
376 |
A*01:02 | | Oman | 0.0 | 0 | | 118 | See | | | |
377 |
A*01:02 | | Pakistan Baloch | | 0 | | 66 | See | | | |
378 |
A*01:02 | | Pakistan Brahui | | 0 | | 104 | See | | | |
379 |
A*01:02 | | Pakistan Burusho | | 0 | | 92 | See | | | |
380 |
A*01:02 | | Pakistan Kalash | | 0 | | 69 | See | | | |
381 |
A*01:02 | | Pakistan Karachi Parsi | | 0 | | 91 | See | | | |
382 |
A*01:02 | | Pakistan Mixed Pathan | | 0 | | 100 | See | | | |
383 |
A*01:02 | | Panama | | 0.0045 | | 462 | See | | |
|
384 |
A*01:02 | | Philippines Ivatan | 0.0 | 0 | | 50 | See | | | |
385 |
A*01:02 | | Poland BMR | 0.0127 | 0.0000640 | | 23,595 | See | | |
|
386 |
A*01:02 | | Romania | 0.0 | 0 | | 348 | See | | | |
387 |
A*01:02 | | Russia Nizhny Novgorod, Russians | 0.0662 | 0.0003 | | 1,510 | See | | |
|
388 |
A*01:02 | | Russia Tuva pop 2 | | 0.0030 | | 169 | See | | | |
389 |
A*01:02 | | Saudi Arabia pop 5 | 1.3 | 0.0063 | | 158 | See | | | |
390 |
A*01:02 | | Saudi Arabia pop 6 (G) | | 0.0006 (*) | | 28,927 | See | | | |
391 |
A*01:02 | | Senegal Niokholo Mandenka | | 0.0160 | | 165 | See | | | |
392 |
A*01:02 | | Singapore Chinese | 0.0 | 0 | | 149 | See | | | |
393 |
A*01:02 | | South Africa Natal Zulu | 0.0 | 0 | | 100 | See | | | |
394 |
A*01:02 | | South Korea pop 10 | | 0.0001 | | 4,128 | See | | | |
395 |
A*01:02 | | South Korea pop 3 | | 0 | | 485 | See | | | |
396 |
A*01:02 | | Spain (Catalunya, Navarra, Extremadura, Aaragón, Cantabria, | 0.6 | 0.0029 | | 4,335 | See | | |
|
397 |
A*01:02 | | Switzerland Aargau-Solothurn | | 0 | | 1,838 | See | | | |
398 |
A*01:02 | | Switzerland Basel | | 0 | | 1,888 | See | | | |
399 |
A*01:02 | | Switzerland Bern | | 0 | | 3,545 | See | | | |
400 |
A*01:02 | | Switzerland Geneva pop 2 | | 0 | | 1,267 | 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 301 to 400
(from 790) records |
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