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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 671) records

Pages:

1 2 3 4 5 6 7 of 7

Line	Allele	Population		% of individuals that have the allele		Allele Frequency (3_decimals)		Sample Size	IMGT/HLA Database¹	Distribution²	MIC-HLA Associations³
301	MICA*008:02		USA African American MIC pop 2			0.051		39	See
302	MICA*008:02		USA Boston African American MIC			0.075		60	See
303	MICA*008:02		USA Caucasian MIC			0.000		103	See
304	MICA*008:02		Wales MIC		0.0	0.000		166	See
305	MICA*009		Brazil Parana Mixed MIC			0.104		201	See
306	MICA*009		Brazil Sao Paulo Mixed MIC		23.5	0.125		200	See
307	MICA*009		England MIC		9.0	0.055		118	See
308	MICA*009		Japan MIC			0.165		130	See
309	MICA*009		Japan MIC pop 2			0.197		152	See
310	MICA*009		Japan MIC pop 3			0.184		114	See
311	MICA*009		Spain Majorca Chueta MIC			0.084		95	See
312	MICA*009		Spain Majorca MIC			0.094		165	See
313	MICA*009		Spain Murcia MIC			0.071		154	See
314	MICA*009		Thailand North East MIC			0.024		255	See
315	MICA*009		Turkey MIC		29.2	0.169		65	See
316	MICA*009		USA Caucasian MIC pop2			0.030		242	See
317	MICA*009:01		Argentina Formosa Toba MIC			0.016		94	See
318	MICA*009:01		Argentina Formosa Wichi MIC			0.012		42	See
319	MICA*009:01		Brazil Limao Verde and Corrego Reserve Terena MIC			0.023		60	See
320	MICA*009:01		Brazil Mato Grosso do Sul Kaiowa MIC			0.089		174	See
321	MICA*009:01		Brazil Mato Grosso do Sul Nandeva MIC			0.017		89	See
322	MICA*009:01		Brazil Parana Guarani M'byá MIC			0.020		100	See
323	MICA*009:01		Brazil Parana Kaingang MIC			0.002		245	See
324	MICA*009:01		China Baotou Han MIC			0.120		104	See
325	MICA*009:01		China Zhejiang Province Han MIC			0.080		100	See
326	MICA*009:01		England Bedfordshire MIC			0.066		354	See
327	MICA*009:01		Morocco Nador Metalsa MIC			0.085		82	See
328	MICA*009:01		South Korea MIC			0.106		199	See
329	MICA*009:01		South Korea Seoul MIC			0.036		139	See
330	MICA*009:01		USA African American MIC			0.042		201	See
331	MICA*009:01		USA Caucasian MIC			0.076		103	See
332	MICA*009:01		Wales MIC		15.0	0.078		166	See
333	MICA*009:02		Argentina Formosa Toba MIC			0.016		94	See
334	MICA*009:02		Argentina Formosa Wichi MIC			0.000		42	See
335	MICA*009:02		Brazil Limao Verde and Corrego Reserve Terena MIC			0.000		60	See
336	MICA*009:02		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
337	MICA*009:02		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
338	MICA*009:02		Brazil Parana Guarani M'byá MIC			0.000		100	See
339	MICA*009:02		Brazil Parana Kaingang MIC			0.000		245	See
340	MICA*009:02		China Baotou Han MIC			0.005		104	See
341	MICA*009:02		China Zhejiang Province Han MIC			0.005		100	See
342	MICA*009:02		England Bedfordshire MIC			0.011		354	See
343	MICA*009:02		Morocco Nador Metalsa MIC			0.140		82	See
344	MICA*009:02		Nigeria South Efik MIC			0.078		32	See
345	MICA*009:02		Nigeria South Igbo MIC			0.000		46	See
346	MICA*009:02		Nigeria South Yoruba MIC			0.007		74	See
347	MICA*009:02		South Korea Seoul MIC			0.004		139	See
348	MICA*009:02		USA African American MIC			0.015		201	See
349	MICA*009:02		USA African American MIC pop 2			0.000		39	See
350	MICA*009:02		USA Boston African American MIC			0.033		60	See
351	MICA*009:02		USA Caucasian MIC			0.010		103	See
352	MICA*010		Argentina Formosa Toba MIC			0.277		94	See
353	MICA*010		Argentina Formosa Wichi MIC			0.190		42	See
354	MICA*010		Brazil Limao Verde and Corrego Reserve Terena MIC			0.172		60	See
355	MICA*010		Brazil Mato Grosso do Sul Kaiowa MIC			0.141		174	See
356	MICA*010		Brazil Mato Grosso do Sul Nandeva MIC			0.341		89	See
357	MICA*010		Brazil Parana Guarani M'byá MIC			0.330		100	See
358	MICA*010		Brazil Parana Kaingang MIC			0.265		245	See
359	MICA*010		Brazil Parana Mixed MIC			0.045		201	See
360	MICA*010		Brazil Sao Paulo Mixed MIC		11.0	0.057		200	See
361	MICA*010		China Baotou Han MIC			0.188		104	See
362	MICA*010		China Zhejiang Province Han MIC			0.185		100	See
363	MICA*010		England Bedfordshire MIC			0.058		354	See
364	MICA*010		England MIC		9.0	0.051		118	See
365	MICA*010		Japan MIC			0.108		130	See
366	MICA*010		Japan MIC pop 2			0.161		152	See
367	MICA*010		Japan MIC pop 3			0.125		114	See
368	MICA*010		South Korea MIC			0.183		199	See
369	MICA*010		South Korea Seoul MIC			0.194		139	See
370	MICA*010		Spain Majorca Chueta MIC			0.005		95	See
371	MICA*010		Spain Majorca MIC			0.018		165	See
372	MICA*010		Spain Murcia MIC			0.045		154	See
373	MICA*010		Thailand North East MIC			0.182		255	See
374	MICA*010		Turkey MIC		4.6	0.023		65	See
375	MICA*010		USA African American MIC			0.007		201	See
376	MICA*010		USA Caucasian MIC			0.070		103	See
377	MICA*010		USA Caucasian MIC pop2			0.050		242	See
378	MICA*010		Wales MIC		7.8	0.042		166	See
379	MICA*011		Argentina Formosa Toba MIC			0.005		94	See
380	MICA*011		Argentina Formosa Wichi MIC			0.000		42	See
381	MICA*011		Brazil Limao Verde and Corrego Reserve Terena MIC			0.000		60	See
382	MICA*011		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
383	MICA*011		Brazil Mato Grosso do Sul Nandeva MIC			0.006		89	See
384	MICA*011		Brazil Parana Guarani M'byá MIC			0.000		100	See
385	MICA*011		Brazil Parana Kaingang MIC			0.008		245	See
386	MICA*011		Brazil Parana Mixed MIC			0.037		201	See
387	MICA*011		Brazil Sao Paulo Mixed MIC		6.5	0.033		200	See
388	MICA*011		China Baotou Han MIC			0.005		104	See
389	MICA*011		England Bedfordshire MIC			0.021		354	See
390	MICA*011		Morocco Nador Metalsa MIC			0.030		82	See
391	MICA*011		South Korea Seoul MIC			0.011		139	See
392	MICA*011		Spain Majorca Chueta MIC			0.016		95	See
393	MICA*011		Spain Majorca MIC			0.045		165	See
394	MICA*011		Thailand North East MIC			0.000		255	See
395	MICA*011		Turkey MIC		7.7	0.038		65	See
396	MICA*011		USA African American MIC			0.012		201	See
397	MICA*011		USA Caucasian MIC			0.025		103	See
398	MICA*011		USA Caucasian MIC pop2			0.020		242	See
399	MICA*011		Wales MIC		3.0	0.015		166	See
400	MICA*012		Brazil Parana Mixed MIC			0.015		201	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.