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Home	Populations	HLA	KIR	Other polymorphisms	HLA-ADR	KDDB

MIC » MIC Allele Frequency Search

Please specify your search by selecting options from boxes. Then, click "Search" to find MIC allele / gene frequencies that match your criteria. Remember at least one option must be selected.

Locus:  All loci MICA MICB Starting Allele:  A4 A5 A5.1 A6 A9 A9.1 A10 MICA*001 MICA*002 MICA*002:01 MICA*002:02 MICA*002:03 MICA*002:04 MICA*004 MICA*005 MICA*006 MICA*007 MICA*007:01 MICA*007:02 MICA*007:03 MICA*007:04 MICA*007:05 MICA*007:06 MICA*008 MICA*008:01 MICA*008:01:01 MICA*008:01:02 MICA*008:02 MICA*008:03 MICA*008:04 MICA*008:05 MICA*009 MICA*009:01 MICA*009:02 MICA*010 MICA*010:01 MICA*010:02 MICA*011 MICA*012 MICA*012:01 MICA*012:02 MICA*012:03 MICA*012:04 MICA*013 MICA*014 MICA*015 MICA*016 MICA*017 MICA*018 MICA*018:01 MICA*018:02 MICA*019 MICA*020 MICA*022 MICA*023 MICA*024 MICA*025 MICA*026 MICA*027 MICA*028 MICA*029 MICA*030 MICA*031 MICA*032 MICA*033 MICA*034 MICA*035 MICA*036 MICA*037 MICA*038 MICA*039 MICA*040 MICA*041 MICA*042 MICA*043 MICA*044 MICA*045 MICA*046 MICA*047 MICA*048 MICA*049 MICA*050 MICA*051 MICA*052 MICA*053 MICA*054 MICA*055 MICA*056 MICA*057 MICA*058 MICA*059 MICA*060 MICA*061 MICA*062 MICA*063N MICA*064N MICA*065 MICA*066 MICA*067 MICA*068 MICA*069 MICA*070 MICA*072 MICA*073 MICA*074 MICA*075 MICA*076 MICA*077 MICA*078 MICA*079 MICA*080 MICA*081 MICA*082 MICA*083 MICA*084 MICA*085 MICB*001 MICB*002 MICB*002:01 MICB*002:01:01 MICB*002:01:02 MICB*003 MICB*004 MICB*004:01 MICB*004:01:01 MICB*004:01:02 MICB*005 MICB*005:01 MICB*005:02 MICB*005:02:01 MICB*005:02:02 MICB*005:02:03 MICB*005:02:04 MICB*005:03 MICB*005:04 MICB*005:05 MICB*005:06 MICB*005:07 MICB*005:08 MICB*006 MICB*007 MICB*008 MICB*009N MICB*010 MICB*011 MICB*012 MICB*013 MICB*014 MICB*015 MICB*016 MICB*018 MICB*019 MICB*020 MICB*021N MICB*022 MICB*023 MICB*024 MICB*025 MICB*026 MICB*027 MICB*028 MICB*029 MICB*030 Ending Allele:  A4 A5 A5.1 A6 A9 A9.1 A10 MICA*001 MICA*002 MICA*002:01 MICA*002:02 MICA*002:03 MICA*002:04 MICA*004 MICA*005 MICA*006 MICA*007 MICA*007:01 MICA*007:02 MICA*007:03 MICA*007:04 MICA*007:05 MICA*007:06 MICA*008 MICA*008:01 MICA*008:01:01 MICA*008:01:02 MICA*008:02 MICA*008:03 MICA*008:04 MICA*008:05 MICA*009 MICA*009:01 MICA*009:02 MICA*010 MICA*010:01 MICA*010:02 MICA*011 MICA*012 MICA*012:01 MICA*012:02 MICA*012:03 MICA*012:04 MICA*013 MICA*014 MICA*015 MICA*016 MICA*017 MICA*018 MICA*018:01 MICA*018:02 MICA*019 MICA*020 MICA*022 MICA*023 MICA*024 MICA*025 MICA*026 MICA*027 MICA*028 MICA*029 MICA*030 MICA*031 MICA*032 MICA*033 MICA*034 MICA*035 MICA*036 MICA*037 MICA*038 MICA*039 MICA*040 MICA*041 MICA*042 MICA*043 MICA*044 MICA*045 MICA*046 MICA*047 MICA*048 MICA*049 MICA*050 MICA*051 MICA*052 MICA*053 MICA*054 MICA*055 MICA*056 MICA*057 MICA*058 MICA*059 MICA*060 MICA*061 MICA*062 MICA*063N MICA*064N MICA*065 MICA*066 MICA*067 MICA*068 MICA*069 MICA*070 MICA*072 MICA*073 MICA*074 MICA*075 MICA*076 MICA*077 MICA*078 MICA*079 MICA*080 MICA*081 MICA*082 MICA*083 MICA*084 MICA*085 MICB*001 MICB*002 MICB*002:01 MICB*002:01:01 MICB*002:01:02 MICB*003 MICB*004 MICB*004:01 MICB*004:01:01 MICB*004:01:02 MICB*005 MICB*005:01 MICB*005:02 MICB*005:02:01 MICB*005:02:02 MICB*005:02:03 MICB*005:02:04 MICB*005:03 MICB*005:04 MICB*005:05 MICB*005:06 MICB*005:07 MICB*005:08 MICB*006 MICB*007 MICB*008 MICB*009N MICB*010 MICB*011 MICB*012 MICB*013 MICB*014 MICB*015 MICB*016 MICB*018 MICB*019 MICB*020 MICB*021N MICB*022 MICB*023 MICB*024 MICB*025 MICB*026 MICB*027 MICB*028 MICB*029 MICB*030    (A4, A5, A5.1, etc. refer to data on frequencies of microsatellites)
Select specific alleles    (If you want to pick specific alleles, make sure your alleles are within the Start-End range above)
Clear Select your alleles   Clear All   Hide A4 A5 A5.1 A6 A9 A9.1 A10 MICA*001 MICA*002 MICA*002:01 MICA*002:02 MICA*002:03 MICA*002:04 MICA*004 MICA*005 MICA*006 MICA*007 MICA*007:01 MICA*007:02 MICA*007:03 MICA*007:04 MICA*007:05 MICA*007:06 MICA*008 MICA*008:01 MICA*008:01:01 MICA*008:01:02 MICA*008:02 MICA*008:03 MICA*008:04 MICA*008:05 MICA*009 MICA*009:01 MICA*009:02 MICA*010 MICA*010:01 MICA*010:02 MICA*011 MICA*012 MICA*012:01 MICA*012:02 MICA*012:03 MICA*012:04 MICA*013 MICA*014 MICA*015 MICA*016 MICA*017 MICA*018 MICA*018:01 MICA*018:02 MICA*019 MICA*020 MICA*022 MICA*023 MICA*024 MICA*025 MICA*026 MICA*027 MICA*028 MICA*029 MICA*030 MICA*031 MICA*032 MICA*033 MICA*034 MICA*035 MICA*036 MICA*037 MICA*038 MICA*039 MICA*040 MICA*041 MICA*042 MICA*043 MICA*044 MICA*045 MICA*046 MICA*047 MICA*048 MICA*049 MICA*050 MICA*051 MICA*052 MICA*053 MICA*054 MICA*055 MICA*056 MICA*057 MICA*058 MICA*059 MICA*060 MICA*061 MICA*062 MICA*063N MICA*064N MICA*065 MICA*066 MICA*067 MICA*068 MICA*069 MICA*070 MICA*072 MICA*073 MICA*074 MICA*075 MICA*076 MICA*077 MICA*078 MICA*079 MICA*080 MICA*081 MICA*082 MICA*083 MICA*084 MICA*085 MICB*001 MICB*002 MICB*002:01 MICB*002:01:01 MICB*002:01:02 MICB*003 MICB*004 MICB*004:01 MICB*004:01:01 MICB*004:01:02 MICB*005 MICB*005:01 MICB*005:02 MICB*005:02:01 MICB*005:02:02 MICB*005:02:03 MICB*005:02:04 MICB*005:03 MICB*005:04 MICB*005:05 MICB*005:06 MICB*005:07 MICB*005:08 MICB*006 MICB*007 MICB*008 MICB*009N MICB*010 MICB*011 MICB*012 MICB*013 MICB*014 MICB*015 MICB*016 MICB*018 MICB*019 MICB*020 MICB*021N MICB*022 MICB*023 MICB*024 MICB*025 MICB*026 MICB*027 MICB*028 MICB*029 MICB*030
Population:  All populations Argentina Formosa Toba MIC (n=94) Argentina Formosa Wichi MIC (n=42) Brazil Limao Verde and Corrego Reserve Terena MIC (n=60) Brazil Mato Grosso do Sul Kaiowa MIC (n=174) Brazil Mato Grosso do Sul Nandeva MIC (n=89) Brazil Parana Guarani M'byá MIC (n=100) Brazil Parana Japanese MIC (n=190) Brazil Parana Kaingang MIC (n=245) Brazil Parana Mixed MIC (n=201) Brazil Sao Paulo Mixed MIC (n=200) China Baotou Han MIC (n=104) China Guangxi Zhuang MIC (n=209) China Guangzhou Han MIC (n=106) China Hui MIC (n=44) China Hunan Province Han MIC (n=85) China North Han MIC (n=32) China Shanghai Han MIC (n=183) China Sichuan Province Han MIC (n=200) China Uygur MIC (n=49) China Xinjiang Province Uygur MIC (n=66) China Yunnan Province Dai MIC (n=41) China Zhangjiajie Tujias MIC (n=187) China Zhejiang Han MIC (n=400) China Zhejiang Province Han MIC (n=100) England Bedfordshire MIC (n=354) England MIC (n=118) England Northwest MIC (n=250) Germany MIC (n=154) Greece Athens MIC (n=27) Iran Tehran MIC (n=18) Italy MIC (n=101) Italy MIC pop 2 (n=98) Italy Perugia MIC (n=158) Italy Rome MIC (n=26) Japan MIC (n=130) Japan MIC pop 2 (n=152) Japan MIC pop 3 (n=114) Japan Tokyo MIC (n=352) Kazakhstan MIC (n=38) Latvia MIC (n=108) Morocco Nador Metalsa MIC (n=82) Nigeria South Efik MIC (n=32) Nigeria South Igbo MIC (n=46) Nigeria South Yoruba MIC (n=74) Saudi Arabia Riyadh MIC (n=18) Slovenia MIC (n=70) South Korea MIC (n=199) South Korea Seoul MIC (n=139) Spain Majorca Chueta MIC (n=95) Spain Majorca MIC (n=165) Spain Malaga MIC (n=241) Spain MIC (n=116) Spain MIC pop 2 (n=342) Spain Murcia MIC (n=154) Sweden MIC (n=503) Thailand North East MIC (n=255) Thailand North East MIC pop 2 (n=100) Turkey MIC (n=65) USA African American MIC (n=201) USA African American MIC pop 2 (n=39) USA Boston African American MIC (n=60) USA Caucasian MIC (n=103) USA Caucasian MIC pop2 (n=242) Wales MIC (n=166) Country:  All countries Argentina Brazil China England Germany Greece Iran Italy Japan Kazakhstan Korea, South Latvia Morocco Nigeria Saudi Arabia Slovenia South Africa Spain Sweden Thailand Turkey United States Wales Source of dataset:  All Sources Literature Proceedings of IHWs Unpublished
Region:  All regions Central Asia Europe North Africa North America North-East Asia South and Central America South-East Asia Sub-Saharan Africa Western Asia Ethnic Origin:  All ethnicities Amerindian Arab Asian Black Caucasoid Mixed Oriental    Type of study:  All Studies Anthropology Study Blood Donor Bone Marrow Registry Controls for Disease Study Other Sort by:  Allele/Gene Allele/Gene, Highest to Lowest Frequency Population Population, Highest to Lowest Frequency
Sample Size:  = <> < > <= >= All 50 100 500 1000 5000     Sample Year:  = <> < > <= >= All years 1995 1996 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2011 2012 2013 2014 2017     Level of resolution :  = <> < > <= >= All 0 1 2 3  (Click here for further details)
Show frequencies: All Only positives Only negatives

Displaying 301 to 400 (from 813) records

Pages:

1 2 3 4 5 6 7 8 9 of 9

Line	Allele	Population		% of individuals that have the allele		Allele Frequency (3_decimals)		Sample Size	IMGT/HLA Database¹	Distribution²	MIC-HLA Associations³
301	MICA*007:02		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
302	MICA*007:02		Brazil Parana Guarani M'byá MIC			0.000		100	See
303	MICA*007:02		Brazil Parana Kaingang MIC			0.000		245	See
304	MICA*007:02		China Zhangjiajie Tujias MIC			0.000		187	See
305	MICA*007:02		South Korea Seoul MIC			0.004		139	See
306	MICA*007:02		Wales MIC		0.0	0.000		166	See
307	MICA*008		Brazil Parana Japanese MIC			0.189		190	See
308	MICA*008		Brazil Parana Mixed MIC			0.281		201	See
309	MICA*008		Brazil Sao Paulo Mixed MIC		47.0	0.272		200	See
310	MICA*008		China Shanghai Han MIC			0.340		183	See
311	MICA*008		China Xinjiang Province Uygur MIC			0.350		66	See
312	MICA*008		China Yunnan Province Dai MIC			0.280		41	See
313	MICA*008		China Zhangjiajie Tujias MIC			0.000		187	See
314	MICA*008		England MIC		74.0	0.480		118	See
315	MICA*008		England Northwest MIC		72.0	0.471		250	See
316	MICA*008		Japan MIC			0.304		130	See
317	MICA*008		Japan MIC pop 2			0.145		152	See
318	MICA*008		Japan MIC pop 3			0.252		114	See
319	MICA*008		Slovenia MIC		62.9	0.391		70	See
320	MICA*008		Spain Majorca Chueta MIC			0.174		95	See
321	MICA*008		Spain Majorca MIC			0.285		165	See
322	MICA*008		Spain Murcia MIC			0.253		154	See
323	MICA*008		Thailand North East MIC			0.214		255	See
324	MICA*008		Turkey MIC		41.5	0.231		65	See
325	MICA*008		USA Caucasian MIC pop2			0.550		242	See
326	MICA*008:01		Argentina Formosa Toba MIC			0.010		94	See
327	MICA*008:01		Argentina Formosa Wichi MIC			0.000		42	See
328	MICA*008:01		Brazil Limao Verde and Corrego Reserve Terena MIC			0.008		60	See
329	MICA*008:01		Brazil Mato Grosso do Sul Kaiowa MIC			0.006		174	See
330	MICA*008:01		Brazil Mato Grosso do Sul Nandeva MIC			0.034		89	See
331	MICA*008:01		Brazil Parana Guarani M'byá MIC			0.015		100	See
332	MICA*008:01		Brazil Parana Kaingang MIC			0.020		245	See
333	MICA*008:01		China Baotou Han MIC			0.231		104	See
334	MICA*008:01		China Guangxi Zhuang MIC			0.101		209	See
335	MICA*008:01		China Zhangjiajie Tujias MIC			0.000		187	See
336	MICA*008:01		China Zhejiang Province Han MIC			0.270		100	See
337	MICA*008:01		England Bedfordshire MIC			0.497		354	See
338	MICA*008:01		Morocco Nador Metalsa MIC			0.268		82	See
339	MICA*008:01		Nigeria South Efik MIC			0.328		32	See
340	MICA*008:01		Nigeria South Igbo MIC			0.250		46	See
341	MICA*008:01		Nigeria South Yoruba MIC			0.142		74	See
342	MICA*008:01		South Korea MIC			0.108		199	See
343	MICA*008:01		South Korea Seoul MIC			0.147		139	See
344	MICA*008:01		USA African American MIC			0.269		201	See
345	MICA*008:01		USA African American MIC pop 2			0.231		39	See
346	MICA*008:01		USA Boston African American MIC			0.183		60	See
347	MICA*008:01		USA Caucasian MIC			0.377		103	See
348	MICA*008:01		Wales MIC		78.3	0.530		166	See
349	MICA*008:02		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
350	MICA*008:02		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
351	MICA*008:02		Brazil Parana Guarani M'byá MIC			0.000		100	See
352	MICA*008:02		Brazil Parana Kaingang MIC			0.000		245	See
353	MICA*008:02		China Baotou Han MIC			0.005		104	See
354	MICA*008:02		China Zhangjiajie Tujias MIC			0.000		187	See
355	MICA*008:02		China Zhejiang Province Han MIC			0.015		100	See
356	MICA*008:02		Nigeria South Efik MIC			0.031		32	See
357	MICA*008:02		Nigeria South Igbo MIC			0.011		46	See
358	MICA*008:02		Nigeria South Yoruba MIC			0.068		74	See
359	MICA*008:02		South Korea Seoul MIC			0.004		139	See
360	MICA*008:02		USA African American MIC			0.055		201	See
361	MICA*008:02		USA African American MIC pop 2			0.051		39	See
362	MICA*008:02		USA Boston African American MIC			0.075		60	See
363	MICA*008:02		USA Caucasian MIC			0.000		103	See
364	MICA*008:02		Wales MIC		0.0	0.000		166	See
365	MICA*008:04		China Guangxi Zhuang MIC			0.101		209	See
366	MICA*008:04		China Zhangjiajie Tujias MIC			0.294		187	See
367	MICA*009		Brazil Parana Japanese MIC			0.168		190	See
368	MICA*009		Brazil Parana Mixed MIC			0.104		201	See
369	MICA*009		Brazil Sao Paulo Mixed MIC		23.5	0.125		200	See
370	MICA*009		China Shanghai Han MIC			0.110		183	See
371	MICA*009		China Xinjiang Province Uygur MIC			0.220		66	See
372	MICA*009		China Yunnan Province Dai MIC			0.060		41	See
373	MICA*009		China Zhangjiajie Tujias MIC			0.000		187	See
374	MICA*009		England MIC		9.0	0.055		118	See
375	MICA*009		England Northwest MIC		11.6	0.060		250	See
376	MICA*009		Japan MIC			0.165		130	See
377	MICA*009		Japan MIC pop 2			0.197		152	See
378	MICA*009		Japan MIC pop 3			0.184		114	See
379	MICA*009		Slovenia MIC		21.4	0.113		70	See
380	MICA*009		Spain Majorca Chueta MIC			0.084		95	See
381	MICA*009		Spain Majorca MIC			0.094		165	See
382	MICA*009		Spain Murcia MIC			0.071		154	See
383	MICA*009		Thailand North East MIC			0.024		255	See
384	MICA*009		Turkey MIC		29.2	0.169		65	See
385	MICA*009		USA Caucasian MIC pop2			0.030		242	See
386	MICA*009:01		Argentina Formosa Toba MIC			0.016		94	See
387	MICA*009:01		Argentina Formosa Wichi MIC			0.012		42	See
388	MICA*009:01		Brazil Limao Verde and Corrego Reserve Terena MIC			0.023		60	See
389	MICA*009:01		Brazil Mato Grosso do Sul Kaiowa MIC			0.089		174	See
390	MICA*009:01		Brazil Mato Grosso do Sul Nandeva MIC			0.017		89	See
391	MICA*009:01		Brazil Parana Guarani M'byá MIC			0.020		100	See
392	MICA*009:01		Brazil Parana Kaingang MIC			0.002		245	See
393	MICA*009:01		China Baotou Han MIC			0.120		104	See
394	MICA*009:01		China Guangxi Zhuang MIC			0.024		209	See
395	MICA*009:01		China Zhangjiajie Tujias MIC			0.000		187	See
396	MICA*009:01		China Zhejiang Province Han MIC			0.080		100	See
397	MICA*009:01		England Bedfordshire MIC			0.066		354	See
398	MICA*009:01		Morocco Nador Metalsa MIC			0.085		82	See
399	MICA*009:01		South Korea MIC			0.106		199	See
400	MICA*009:01		South Korea Seoul MIC			0.036		139	See

Notes:

- Allele Frequency: Total number of copies of the allele in the population sample (Alleles / 2n) in three decimal format.
- % of individuals that have the allele: Percentage of individuals who have the allele or gene (Individuals / n).
- Allele Frequencies shown in green were calculated from the % of the individuals carrying the allele, 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.
¹ IMGT/HLA Database - For more details of the allele.
² Distribution - Graphical distribution of the allele.
³ MICA-HLA-B Associations - Find MICA-HLA-B associations with this allele.