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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 423) records

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1 2 3 4 5 of 5

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 Uygur MIC			0.071		49	See
7	A4		Greece Athens MIC			0.148		27	See
8	A4		Iran Tehran MIC			0.083		18	See
9	A4		Italy Rome MIC			0.096		26	See
10	A4		Japan Tokyo MIC			0.161		352	See
11	A4		Kazakhstan MIC			0.131		38	See
12	A4		Saudi Arabia Riyadh MIC			0.056		18	See
13	A4		Spain Majorca Chueta MIC		35.8	0.199		95	See
14	A4		Spain Majorca MIC		30.0	0.163		165	See
15	A5		China Baotou Han MIC			0.293		104	See
16	A5		China Guangzhou Han MIC			0.288		106	See
17	A5		China Hui MIC			0.307		44	See
18	A5		China Hunan Province Han MIC			0.376		85	See
19	A5		China North Han MIC			0.281		32	See
20	A5		China Uygur MIC			0.163		49	See
21	A5		Greece Athens MIC			0.111		27	See
22	A5		Iran Tehran MIC			0.167		18	See
23	A5		Italy Rome MIC			0.212		26	See
24	A5		Japan Tokyo MIC			0.292		352	See
25	A5		Kazakhstan MIC			0.237		38	See
26	A5		Saudi Arabia Riyadh MIC			0.083		18	See
27	A5		Spain Majorca Chueta MIC		22.1	0.117		95	See
28	A5		Spain Majorca MIC		13.3	0.069		165	See
29	A5.1		China Baotou Han MIC			0.236		104	See
30	A5.1		China Guangzhou Han MIC			0.264		106	See
31	A5.1		China Hui MIC			0.239		44	See
32	A5.1		China Hunan Province Han MIC			0.265		85	See
33	A5.1		China North Han MIC			0.266		32	See
34	A5.1		China Uygur MIC			0.225		49	See
35	A5.1		Greece Athens MIC			0.223		27	See
36	A5.1		Iran Tehran MIC			0.167		18	See
37	A5.1		Italy Rome MIC			0.115		26	See
38	A5.1		Japan Tokyo MIC			0.123		352	See
39	A5.1		Kazakhstan MIC			0.224		38	See
40	A5.1		Saudi Arabia Riyadh MIC			0.222		18	See
41	A5.1		Spain Majorca Chueta MIC		29.5	0.160		95	See
42	A5.1		Spain Majorca MIC		44.0	0.252		165	See
43	A6		China Baotou Han MIC			0.178		104	See
44	A6		China Guangzhou Han MIC			0.146		106	See
45	A6		China Hui MIC			0.170		44	See
46	A6		China Hunan Province Han MIC			0.076		85	See
47	A6		China North Han MIC			0.156		32	See
48	A6		China Uygur MIC			0.337		49	See
49	A6		Greece Athens MIC			0.407		27	See
50	A6		Iran Tehran MIC			0.472		18	See
51	A6		Italy Rome MIC			0.404		26	See
52	A6		Japan Tokyo MIC			0.258		352	See
53	A6		Kazakhstan MIC			0.224		38	See
54	A6		Saudi Arabia Riyadh MIC			0.500		18	See
55	A6		Spain Majorca Chueta MIC		49.5	0.289		95	See
56	A6		Spain Majorca MIC		56.7	0.342		165	See
57	A9		China Baotou Han MIC			0.139		104	See
58	A9		China Guangzhou Han MIC			0.170		106	See
59	A9		China Hui MIC			0.193		44	See
60	A9		China Hunan Province Han MIC			0.118		85	See
61	A9		China North Han MIC			0.203		32	See
62	A9		China Uygur MIC			0.204		49	See
63	A9		Greece Athens MIC			0.111		27	See
64	A9		Iran Tehran MIC			0.111		18	See
65	A9		Italy Rome MIC			0.173		26	See
66	A9		Japan Tokyo MIC			0.166		352	See
67	A9		Kazakhstan MIC			0.184		38	See
68	A9		Saudi Arabia Riyadh MIC			0.139		18	See
69	A9		Spain Majorca Chueta MIC		34.7	0.192		95	See
70	A9		Spain Majorca MIC		31.3	0.171		165	See
71	A10		China Hunan Province Han MIC			0.006		85	See
72	MICA*001		Argentina Formosa Toba MIC			0.005		94	See
73	MICA*001		Argentina Formosa Wichi MIC			0.000		42	See
74	MICA*001		Brazil Limao Verde and Corrego Reserve Terena MIC			0.000		60	See
75	MICA*001		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
76	MICA*001		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
77	MICA*001		Brazil Parana Guarani M'byá MIC			0.000		100	See
78	MICA*001		Brazil Parana Kaingang MIC			0.002		245	See
79	MICA*001		Morocco Nador Metalsa MIC			0.030		82	See
80	MICA*001		Spain Majorca Chueta MIC			0.005		95	See
81	MICA*001		Spain Majorca MIC			0.051		165	See
82	MICA*001		Spain Murcia MIC			0.078		154	See
83	MICA*001		Thailand North East MIC			0.000		255	See
84	MICA*001		USA Caucasian MIC pop2			0.030		242	See
85	MICA*002		Japan MIC			0.146		130	See
86	MICA*002		Spain Majorca Chueta MIC			0.158		95	See
87	MICA*002		Spain Majorca MIC			0.142		165	See
88	MICA*002		Spain Murcia MIC			0.161		154	See
89	MICA*002		Thailand North East MIC			0.176		255	See
90	MICA*002		USA Caucasian MIC pop2			0.130		242	See
91	MICA*002:01		Argentina Formosa Toba MIC			0.346		94	See
92	MICA*002:01		Argentina Formosa Wichi MIC			0.476		42	See
93	MICA*002:01		Brazil Limao Verde and Corrego Reserve Terena MIC			0.445		60	See
94	MICA*002:01		Brazil Mato Grosso do Sul Kaiowa MIC			0.641		174	See
95	MICA*002:01		Brazil Mato Grosso do Sul Nandeva MIC			0.375		89	See
96	MICA*002:01		Brazil Parana Guarani M'byá MIC			0.215		100	See
97	MICA*002:01		Brazil Parana Kaingang MIC			0.396		245	See
98	MICA*002:01		China Baotou Han MIC			0.120		104	See
99	MICA*002:01		China Guangxi Zhuang MIC			0.151		209	See
100	MICA*002:01		Morocco Nador Metalsa MIC			0.073		82	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.