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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 1 to 100 (from 671) records

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Line	Allele	Population		% of individuals that have the allele		Allele Frequency (3_decimals)		Sample Size	IMGT/HLA Database¹	Distribution²	MIC-HLA Associations³
1	A4		China Baotou Han MIC			0.115		104	See
2	A4		China Guangzhou Han MIC			0.132		106	See
3	A4		China Hui MIC			0.091		44	See
4	A4		China Hunan Province Han MIC			0.147		85	See
5	A4		China North Han MIC			0.094		32	See
6	A4		China Sichuan Province Han MIC			0.150		200	See
7	A4		China Uygur MIC			0.071		49	See
8	A4		Germany MIC			0.117		154	See
9	A4		Greece Athens MIC			0.148		27	See
10	A4		Iran Tehran MIC			0.083		18	See
11	A4		Italy MIC			0.141		101	See
12	A4		Italy Perugia MIC			0.120		158	See
13	A4		Italy Rome MIC			0.096		26	See
14	A4		Japan Tokyo MIC			0.161		352	See
15	A4		Kazakhstan MIC			0.131		38	See
16	A4		Saudi Arabia Riyadh MIC			0.056		18	See
17	A4		South Korea Seoul MIC			0.169		139	See
18	A4		Spain Majorca Chueta MIC		35.8	0.199		95	See
19	A4		Spain Majorca MIC		30.0	0.163		165	See
20	A4		Spain Malaga MIC			0.100		241	See
21	A4		Spain MIC		26.0	0.140		116	See
22	A4		Spain MIC pop 2		23.0	0.123		342	See
23	A4		Sweden MIC		25.0	0.134		503	See
24	A5		China Baotou Han MIC			0.293		104	See
25	A5		China Guangzhou Han MIC			0.288		106	See
26	A5		China Hui MIC			0.307		44	See
27	A5		China Hunan Province Han MIC			0.376		85	See
28	A5		China North Han MIC			0.281		32	See
29	A5		China Sichuan Province Han MIC			0.390		200	See
30	A5		China Uygur MIC			0.163		49	See
31	A5		Germany MIC			0.136		154	See
32	A5		Greece Athens MIC			0.111		27	See
33	A5		Iran Tehran MIC			0.167		18	See
34	A5		Italy MIC			0.136		101	See
35	A5		Italy Perugia MIC			0.100		158	See
36	A5		Italy Rome MIC			0.212		26	See
37	A5		Japan Tokyo MIC			0.292		352	See
38	A5		Kazakhstan MIC			0.237		38	See
39	A5		Saudi Arabia Riyadh MIC			0.083		18	See
40	A5		South Korea Seoul MIC			0.248		139	See
41	A5		Spain Majorca Chueta MIC		22.1	0.117		95	See
42	A5		Spain Majorca MIC		13.3	0.069		165	See
43	A5		Spain Malaga MIC			0.200		241	See
44	A5		Spain MIC		28.0	0.151		116	See
45	A5		Spain MIC pop 2		21.0	0.111		342	See
46	A5		Sweden MIC		24.5	0.131		503	See
47	A5.1		China Baotou Han MIC			0.236		104	See
48	A5.1		China Guangzhou Han MIC			0.264		106	See
49	A5.1		China Hui MIC			0.239		44	See
50	A5.1		China Hunan Province Han MIC			0.265		85	See
51	A5.1		China North Han MIC			0.266		32	See
52	A5.1		China Sichuan Province Han MIC			0.230		200	See
53	A5.1		China Uygur MIC			0.225		49	See
54	A5.1		Germany MIC			0.370		154	See
55	A5.1		Greece Athens MIC			0.223		27	See
56	A5.1		Iran Tehran MIC			0.167		18	See
57	A5.1		Italy MIC			0.316		101	See
58	A5.1		Italy Perugia MIC			0.200		158	See
59	A5.1		Italy Rome MIC			0.115		26	See
60	A5.1		Japan Tokyo MIC			0.123		352	See
61	A5.1		Kazakhstan MIC			0.224		38	See
62	A5.1		Saudi Arabia Riyadh MIC			0.222		18	See
63	A5.1		South Korea Seoul MIC			0.151		139	See
64	A5.1		Spain Majorca Chueta MIC		29.5	0.160		95	See
65	A5.1		Spain Majorca MIC		44.0	0.252		165	See
66	A5.1		Spain Malaga MIC			0.280		241	See
67	A5.1		Spain MIC		44.0	0.252		116	See
68	A5.1		Spain MIC pop 2		43.0	0.245		342	See
69	A5.1		Sweden MIC		62.6	0.388		503	See
70	A6		China Baotou Han MIC			0.178		104	See
71	A6		China Guangzhou Han MIC			0.146		106	See
72	A6		China Hui MIC			0.170		44	See
73	A6		China Hunan Province Han MIC			0.076		85	See
74	A6		China North Han MIC			0.156		32	See
75	A6		China Sichuan Province Han MIC			0.097		200	See
76	A6		China Uygur MIC			0.337		49	See
77	A6		Germany MIC			0.224		154	See
78	A6		Greece Athens MIC			0.407		27	See
79	A6		Iran Tehran MIC			0.472		18	See
80	A6		Italy MIC			0.272		101	See
81	A6		Italy Perugia MIC			0.370		158	See
82	A6		Italy Rome MIC			0.404		26	See
83	A6		Japan Tokyo MIC			0.258		352	See
84	A6		Kazakhstan MIC			0.224		38	See
85	A6		Saudi Arabia Riyadh MIC			0.500		18	See
86	A6		South Korea Seoul MIC			0.227		139	See
87	A6		Spain Majorca Chueta MIC		49.5	0.289		95	See
88	A6		Spain Majorca MIC		56.7	0.342		165	See
89	A6		Spain Malaga MIC			0.250		241	See
90	A6		Spain MIC		43.0	0.245		116	See
91	A6		Spain MIC pop 2		55.0	0.329		342	See
92	A6		Sweden MIC		23.3	0.124		503	See
93	A9		China Baotou Han MIC			0.139		104	See
94	A9		China Guangzhou Han MIC			0.170		106	See
95	A9		China Hui MIC			0.193		44	See
96	A9		China Hunan Province Han MIC			0.118		85	See
97	A9		China North Han MIC			0.203		32	See
98	A9		China Sichuan Province Han MIC			0.133		200	See
99	A9		China Uygur MIC			0.204		49	See
100	A9		Germany MIC			0.153		154	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.