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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 101 to 200 (from 745) records

Pages:

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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
101	MICA*004		South Korea MIC			0.123		199	See
102	MICA*004		South Korea Seoul MIC			0.083		139	See
103	MICA*004		Spain Majorca Chueta MIC			0.200		95	See
104	MICA*004		Spain Majorca MIC			0.176		165	See
105	MICA*004		Spain Murcia MIC			0.149		154	See
106	MICA*004		Thailand North East MIC			0.035		255	See
107	MICA*004		Turkey MIC		12.3	0.062		65	See
108	MICA*004		USA African American MIC			0.187		201	See
109	MICA*004		USA African American MIC pop 2			0.295		39	See
110	MICA*004		USA Boston African American MIC			0.233		60	See
111	MICA*004		USA Caucasian MIC			0.055		103	See
112	MICA*004		USA Caucasian MIC pop2			0.060		242	See
113	MICA*004		Wales MIC		9.0	0.045		166	See
114	MICA*005		China Shanghai Han MIC			0.010		183	See
115	MICA*005		China Xinjiang Province Uygur MIC			0.000		66	See
116	MICA*005		China Yunnan Province Dai MIC			0.010		41	See
117	MICA*005		China Zhangjiajie Tujias MIC			0.000		187	See
118	MICA*005		England Northwest MIC		0.0	0.000		250	See
119	MICA*005		Spain Murcia MIC			0.006		154	See
120	MICA*005		Wales MIC		0.0	0.000		166	See
121	MICA*006		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
122	MICA*006		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
123	MICA*006		Brazil Parana Guarani M'byá MIC			0.000		100	See
124	MICA*006		Brazil Parana Japanese MIC			0.003		190	See
125	MICA*006		Brazil Parana Kaingang MIC			0.000		245	See
126	MICA*006		Brazil Parana Mixed MIC			0.012		201	See
127	MICA*006		Brazil Sao Paulo Mixed MIC		1.5	0.008		200	See
128	MICA*006		China Zhangjiajie Tujias MIC			0.000		187	See
129	MICA*006		England MIC		5.0	0.025		118	See
130	MICA*006		England Northwest MIC		0.4	0.002		250	See
131	MICA*006		Slovenia MIC		0.0	0.000		70	See
132	MICA*006		South Korea Seoul MIC			0.014		139	See
133	MICA*006		Spain Majorca Chueta MIC			0.000		95	See
134	MICA*006		Spain Majorca MIC			0.012		165	See
135	MICA*006		Turkey MIC		4.6	0.023		65	See
136	MICA*006		USA Caucasian MIC pop2			0.000		242	See
137	MICA*006		Wales MIC		0.6	0.003		166	See
138	MICA*007		Brazil Parana Mixed MIC			0.017		201	See
139	MICA*007		Brazil Sao Paulo Mixed MIC		2.5	0.013		200	See
140	MICA*007		China Shanghai Han MIC			0.070		183	See
141	MICA*007		China Xinjiang Province Uygur MIC			0.020		66	See
142	MICA*007		China Yunnan Province Dai MIC			0.070		41	See
143	MICA*007		China Zhangjiajie Tujias MIC			0.000		187	See
144	MICA*007		England MIC		10.0	0.051		118	See
145	MICA*007		England Northwest MIC		7.6	0.039		250	See
146	MICA*007		Japan MIC			0.012		130	See
147	MICA*007		Japan MIC pop 2			0.013		152	See
148	MICA*007		Japan MIC pop 3			0.009		114	See
149	MICA*007		Slovenia MIC		11.4	0.059		70	See
150	MICA*007		Spain Majorca Chueta MIC			0.068		95	See
151	MICA*007		Spain Majorca MIC			0.045		165	See
152	MICA*007		Spain Murcia MIC			0.012		154	See
153	MICA*007		Thailand North East MIC			0.000		255	See
154	MICA*007		Turkey MIC		9.2	0.046		65	See
155	MICA*007		USA Caucasian MIC pop2			0.020		242	See
156	MICA*007:01		Argentina Formosa Toba MIC			0.000		94	See
157	MICA*007:01		Argentina Formosa Wichi MIC			0.012		42	See
158	MICA*007:01		Brazil Limao Verde and Corrego Reserve Terena MIC			0.000		60	See
159	MICA*007:01		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
160	MICA*007:01		Brazil Mato Grosso do Sul Nandeva MIC			0.011		89	See
161	MICA*007:01		Brazil Parana Guarani M'byá MIC			0.000		100	See
162	MICA*007:01		Brazil Parana Kaingang MIC			0.000		245	See
163	MICA*007:01		China Baotou Han MIC			0.014		104	See
164	MICA*007:01		China Zhangjiajie Tujias MIC			0.000		187	See
165	MICA*007:01		China Zhejiang Province Han MIC			0.010		100	See
166	MICA*007:01		England Bedfordshire MIC			0.049		354	See
167	MICA*007:01		Morocco Nador Metalsa MIC			0.024		82	See
168	MICA*007:01		South Korea MIC			0.033		199	See
169	MICA*007:01		South Korea Seoul MIC			0.040		139	See
170	MICA*007:01		USA African American MIC			0.007		201	See
171	MICA*007:01		USA Caucasian MIC			0.040		103	See
172	MICA*007:01		Wales MIC		7.2	0.042		166	See
173	MICA*007:02		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
174	MICA*007:02		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
175	MICA*007:02		Brazil Parana Guarani M'byá MIC			0.000		100	See
176	MICA*007:02		Brazil Parana Kaingang MIC			0.000		245	See
177	MICA*007:02		China Zhangjiajie Tujias MIC			0.000		187	See
178	MICA*007:02		South Korea Seoul MIC			0.004		139	See
179	MICA*007:02		Wales MIC		0.0	0.000		166	See
180	MICA*008		Brazil Parana Japanese MIC			0.189		190	See
181	MICA*008		Brazil Parana Mixed MIC			0.281		201	See
182	MICA*008		Brazil Sao Paulo Mixed MIC		47.0	0.272		200	See
183	MICA*008		China Shanghai Han MIC			0.340		183	See
184	MICA*008		China Xinjiang Province Uygur MIC			0.350		66	See
185	MICA*008		China Yunnan Province Dai MIC			0.280		41	See
186	MICA*008		China Zhangjiajie Tujias MIC			0.000		187	See
187	MICA*008		England MIC		74.0	0.480		118	See
188	MICA*008		England Northwest MIC		72.0	0.471		250	See
189	MICA*008		Japan MIC			0.304		130	See
190	MICA*008		Japan MIC pop 2			0.145		152	See
191	MICA*008		Japan MIC pop 3			0.252		114	See
192	MICA*008		Slovenia MIC		62.9	0.391		70	See
193	MICA*008		Spain Majorca Chueta MIC			0.174		95	See
194	MICA*008		Spain Majorca MIC			0.285		165	See
195	MICA*008		Spain Murcia MIC			0.253		154	See
196	MICA*008		Thailand North East MIC			0.214		255	See
197	MICA*008		Turkey MIC		41.5	0.231		65	See
198	MICA*008		USA Caucasian MIC pop2			0.550		242	See
199	MICA*008:01		Argentina Formosa Toba MIC			0.010		94	See
200	MICA*008:01		Argentina Formosa Wichi MIC			0.000		42	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.