Line |
Allele |
Population |
% of individuals
that have the allele |
Allele
Frequency
(in_decimals) |
Sample
Size |
IMGT/HLA¹
Database |
Distribution² |
Haplotype³
Association |
Notesª |
201 |
B*51:01 | | Malaysia Peninsular Chinese | 5.2 | 0.0258 | | 194 | See | | |
|
202 |
B*51:01 | | Mali Bandiagara | | 0.0250 | | 138 | See | | | |
203 |
B*51:01 | | USA NMDP African | | 0.0241 | | 28,557 | See | | | |
204 |
B*51:01 | | USA NMDP Hawaiian or other Pacific Islander | | 0.0236 | | 11,499 | See | | | |
205 |
B*51:01 | | Israel Bukhara Jews | | 0.0230 | | 2,317 | See | | |
|
206 |
B*51:01 | | China Shanxi HIV negative | | 0.0230 | | 22 | See | | | |
207 |
B*51:01 | | Kenya Luo | | 0.0230 | | 265 | See | | | |
208 |
B*51:01 | | Israel USA Jews | | 0.0229 | | 6,058 | See | | |
|
209 |
B*51:01 | | USA NMDP Vietnamese | | 0.0228 | | 43,540 | See | | | |
210 |
B*51:01 | | USA NMDP Caribean Black | | 0.0226 | | 33,328 | See | | | |
211 |
B*51:01 | | Mexico Oaxaca Zapotec | | 0.0220 | | 90 | See | | | |
212 |
B*51:01 | | USA African American pop 4 | | 0.0218 | | 2,411 | See | | | |
213 |
B*51:01 | | USA NMDP African American pop 2 | | 0.0217 | | 416,581 | See | | | |
214 |
B*51:01 | | USA African American pop 8 | | 0.0210 | | 605 | See | | | |
215 |
B*51:01 | | Israel Poland Jews | | 0.0201 | | 13,871 | See | | |
|
216 |
B*51:01 | | China Guizhou Province Bouyei | | 0.0200 | | 109 | See | | | |
217 |
B*51:01 | | Ghana Ga-Adangbe | 3.8 | 0.0191 | | 131 | See | | | |
218 |
B*51:01 | | South Africa Worcester | 4.0 | 0.0190 | | 159 | See | | |
|
219 |
B*51:01 | | Malaysia Mandailing | 3.7 | 0.0190 | | 27 | See | | |
|
220 |
B*51:01 | | China Guangxi Region Maonan | | 0.0190 | | 108 | See | | | |
221 |
B*51:01 | | New Caledonia | | 0.0190 | | 65 | See | | | |
222 |
B*51:01 | | Ireland South | 3.6 | 0.0180 | | 250 | See | | | |
223 |
B*51:01 | | Malaysia Champa | 3.5 | 0.0170 | | 29 | See | | |
|
224 |
B*51:01 | | Israel Ashkenazi Jews pop 3 | | 0.0152 | | 4,625 | See | | |
|
225 |
B*51:01 | | Cameroon Beti | | 0.0140 | | 174 | See | | | |
226 |
B*51:01 | | Peru Titikaka Lake Uro | | 0.0140 | | 105 | See | | | |
227 |
B*51:01 | | Peru Titikaka Lake Uros | | 0.0140 | | 105 | See | | |
|
228 |
B*51:01 | | Malaysia Pahang Semai | 2.6 | 0.0130 | | 38 | See | | |
|
229 |
B*51:01 | | Italy North Pavia | | 0.0120 | | 81 | See | | | |
230 |
B*51:01 | | USA African American | | 0.0120 | | 252 | See | | | |
231 |
B*51:01 | | USA African American pop 3 | | 0.0110 | | 564 | See | | | |
232 |
B*51:01 | | Mexico Chichen Itza Maya (prehispanic) | | 0.0106 | | 47 | See | | |
|
233 |
B*51:01 | | Taiwan Siraya | 2.0 | 0.0100 | | 51 | See | | | |
234 |
B*51:01 | | China Yunnan Hani | | 0.0100 | | 150 | See | | | |
235 |
B*51:01 | | Sweden Northern Sami | | 0.0100 | | 154 | See | | | |
236 |
B*51:01 | | Colombia North Wiwa El Encanto | | 0.0096 | | 52 | See | | |
|
237 |
B*51:01 | | Mexico Chiapas Lacandon Mayans | | 0.0092 | | 218 | See | | |
|
238 |
B*51:01 | | Brazil Terena | 1.7 | 0.0090 | | 60 | See | | | |
239 |
B*51:01 | | Czech Republic | | 0.0090 | | 106 | See | | | |
240 |
B*51:01 | | Mexico Oaxaca Mixe | | 0.0090 | | 55 | See | | | |
241 |
B*51:01 | | Uganda Kampala pop 2 | | 0.0090 | | 175 | See | | | |
242 |
B*51:01 | | Israel Morocco Jews | | 0.0074 | | 36,718 | See | | |
|
243 |
B*51:01 | | Australia Groote Eylandt Aborigine | | 0.0070 | | 75 | See | | | |
244 |
B*51:01 | | Singapore SGVP Malay MAS | | 0.0060 | | 89 | See | | |
|
245 |
B*51:01 | | Israel Libya Jews | | 0.0040 | | 3,739 | See | | |
|
246 |
B*51:01 | | Zimbabwe Harare Shona | | 0.0040 | | 230 | See | | | |
247 |
B*51:01 | | USA Arizona Gila River Amerindian | | 0.0020 | | 492 | See | | | |
248 |
B*51:01 | | Brazil Vale do Ribeira Quilombos | 0.0380 | 0 | | 144 | See | | | |
249 |
B*51:01 | | Argentina Gran Chaco Mataco Wichi | 0.0 | 0 | | 49 | See | | | |
250 |
B*51:01 | | Australia Yuendumu Aborigine | | 0 | | 191 | See | | | |
251 |
B*51:01 | | Cameroon Baka Pygmy | | 0 | | 10 | See | | | |
252 |
B*51:01 | | Cameroon Sawa | | 0 | | 13 | See | | | |
253 |
B*51:01 | | China North Han | | 0 | | 105 | See | | | |
254 |
B*51:01 | | Papua New Guinea East New Britain Rabaul | | 0 | | 60 | See | | | |
255 |
B*51:01 | | Papua New Guinea Eastern Highlands Goroka Asaro | | 0 | | 57 | See | | | |
256 |
B*51:01 | | Papua New Guinea Karimui Plateau Pawaia | | 0 | | 80 | See | | | |
257 |
B*51:01 | | Papua New Guinea Madang | | 0 | | 65 | See | | | |
258 |
B*51:01 | | Papua New Guinea Wanigela Keapara | | 0 | | 66 | See | | | |
259 |
B*51:01 | | Papua New Guinea West Schrader Ranges Haruai | | 0 | | 55 | See | | | |
260 |
B*51:01 | | Papua New Guinea Wosera Abelam | | 0 | | 131 | See | | | |
261 |
B*51:01 | | South Africa Natal Zulu | 0.0 | 0 | | 100 | See | | | |
262 |
B*51:01:01 | | Canada Cree NA-DHS_3 (G) | 50.0 (*) | 0.3056 (*) | | 18 | See | | |
|
263 |
B*51:01:01 | | Bulgaria | | 0.2090 | | 55 | See | | | |
264 |
B*51:01:01 | | Saudi Arabia pop 6 (G) | | 0.1901 (*) | | 28,927 | See | | | |
265 |
B*51:01:01 | | Georgia Tibilisi | | 0.1570 | | 109 | See | | | |
266 |
B*51:01:01 | | India Tamil Nadu Nadar | | 0.1560 | | 61 | See | | | |
267 |
B*51:01:01 | | Chile Huilliche NA-DHS_14 (G) | 25.0 (*) | 0.1500 (*) | | 20 | See | | |
|
268 |
B*51:01:01 | | China North Han | | 0.1480 | | 105 | See | | | |
269 |
B*51:01:01 | | Saudi Arabia pop 5 | 22.8 | 0.1361 | | 158 | See | | | |
270 |
B*51:01:01 | | Russia Bashkortostan, Bashkirs | 23.3 | 0.1292 | | 120 | See | | |
|
271 |
B*51:01:01 | | Georgia Tibilisi Kurd | | 0.1210 | | 31 | See | | | |
272 |
B*51:01:01 | | India Andhra Pradesh Golla | | 0.1200 | | 111 | See | | | |
273 |
B*51:01:01 | | China Qinghai Province Hui | | 0.1140 | | 110 | See | | | |
274 |
B*51:01:01 | | India Andhra Pradesh Telugu Speaking | 21.5 | 0.1129 | | 186 | See | | |
|
275 |
B*51:01:01 | | Canada Chipewyan NA-DHS_2 (G) | 16.0 (*) | 0.1000 (*) | | 25 | See | | |
|
276 |
B*51:01:01 | | India New Delhi | | 0.0980 | | 71 | See | | | |
277 |
B*51:01:01 | | Libya Cyrenaica | | 0.0980 | | 118 | See | | | |
278 |
B*51:01:01 | | Madeira | | 0.0970 | | 185 | See | | | |
279 |
B*51:01:01 | | Russia Tundra Nentsi NA-DHS_1 (G) | 18.8 (*) | 0.0938 (*) | | 16 | See | | |
|
280 |
B*51:01:01 | | South Africa Natal Tamil | | 0.0920 | | 51 | See | | | |
281 |
B*51:01:01 | | USA Hawaii Okinawa | | 0.0870 | | 106 | See | | | |
282 |
B*51:01:01 | | Brazil Barra Mansa Rio State Caucasian | | 0.0852 | | 405 | See | | |
|
283 |
B*51:01:01 | | Cape Verde Northwestern Islands | | 0.0810 | | 62 | See | | | |
284 |
B*51:01:01 | | Brazil Rio de Janeiro Caucasian | | 0.0806 | | 521 | See | | |
|
285 |
B*51:01:01 | | Mexico Hidalgo Mezquital Valley/ Otomi | 15.3 | 0.0764 | | 72 | See | | | |
286 |
B*51:01:01 | | India Kerala Malayalam speaking | 14.6 | 0.0760 | | 356 | See | | |
|
287 |
B*51:01:01 | | Cape Verde Southeastern Islands | | 0.0730 | | 62 | See | | | |
288 |
B*51:01:01 | | India Karnataka Kannada Speaking | 12.1 | 0.0690 | | 174 | See | | |
|
289 |
B*51:01:01 | | India Mumbai Maratha | | 0.0680 | | 91 | See | | | |
290 |
B*51:01:01 | | Canada Ojibwa NA-DHS_4 (G) | 13.3 (*) | 0.0667 (*) | | 16 | See | | |
|
291 |
B*51:01:01 | | Colombia Wayuu NA-DHS_15 (G) | 13.3 (*) | 0.0667 (*) | | 15 | See | | |
|
292 |
B*51:01:01 | | Brazil Rio de Janeiro Parda | | 0.0618 | | 170 | See | | |
|
293 |
B*51:01:01 | | Russia Tuva pop 2 | | 0.0610 | | 169 | See | | | |
294 |
B*51:01:01 | | Israel Arab Druze | | 0.0600 | | 101 | See | | | |
295 |
B*51:01:01 | | China Inner Mongolia Region | | 0.0590 | | 102 | See | | | |
296 |
B*51:01:01 | | Spain, Canary Islands, Gran canaria island | 11.6 | 0.0581 | | 215 | See | | |
|
297 |
B*51:01:01 | | Czech Republic | | 0.0570 | | 106 | See | | | |
298 |
B*51:01:01 | | Finland | | 0.0560 | | 91 | See | | | |
299 |
B*51:01:01 | | Iran Baloch | | 0.0560 | | 100 | See | | | |
300 |
B*51:01:01 | | Russia Belgorod region | 11.1 | 0.0556 | | 153 | See | | |
|
* Allele Frequency: Total number of copies of the allele in the population sample (Alleles / 2n) in decimal format.
: 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).
were calculated from Phenotype Frequencies assuming Hardy-Weinberg proportions.
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
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.