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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 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
101	A9		Greece Athens MIC			0.111		27	See
102	A9		Iran Tehran MIC			0.111		18	See
103	A9		Italy MIC			0.136		101	See
104	A9		Italy Perugia MIC			0.210		158	See
105	A9		Italy Rome MIC			0.173		26	See
106	A9		Japan Tokyo MIC			0.166		352	See
107	A9		Kazakhstan MIC			0.184		38	See
108	A9		Saudi Arabia Riyadh MIC			0.139		18	See
109	A9		South Korea Seoul MIC			0.176		139	See
110	A9		Spain Majorca Chueta MIC		34.7	0.192		95	See
111	A9		Spain Majorca MIC		31.3	0.171		165	See
112	A9		Spain Malaga MIC			0.160		241	See
113	A9		Spain MIC		30.0	0.163		116	See
114	A9		Spain MIC pop 2		29.0	0.157		342	See
115	A9		Sweden MIC		25.8	0.139		503	See
116	A9.1		South Korea Seoul MIC			0.004		139	See
117	A10		China Hunan Province Han MIC			0.006		85	See
118	MICA*001		Argentina Formosa Toba MIC			0.005		94	See
119	MICA*001		Argentina Formosa Wichi MIC			0.000		42	See
120	MICA*001		Brazil Limao Verde and Corrego Reserve Terena MIC			0.000		60	See
121	MICA*001		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
122	MICA*001		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
123	MICA*001		Brazil Parana Guarani M'byá MIC			0.000		100	See
124	MICA*001		Brazil Parana Kaingang MIC			0.002		245	See
125	MICA*001		Brazil Parana Mixed MIC			0.025		201	See
126	MICA*001		Brazil Sao Paulo Mixed MIC		3.5	0.018		200	See
127	MICA*001		England MIC		0.0	0.000		118	See
128	MICA*001		Morocco Nador Metalsa MIC			0.030		82	See
129	MICA*001		Spain Majorca Chueta MIC			0.005		95	See
130	MICA*001		Spain Majorca MIC			0.051		165	See
131	MICA*001		Spain Murcia MIC			0.078		154	See
132	MICA*001		Thailand North East MIC			0.000		255	See
133	MICA*001		USA African American MIC			0.012		201	See
134	MICA*001		USA Caucasian MIC			0.015		103	See
135	MICA*001		USA Caucasian MIC pop2			0.030		242	See
136	MICA*001		Wales MIC		1.8	0.009		166	See
137	MICA*002		Brazil Parana Mixed MIC			0.182		201	See
138	MICA*002		Brazil Sao Paulo Mixed MIC		28.5	0.154		200	See
139	MICA*002		England MIC		35.0	0.180		118	See
140	MICA*002		Japan MIC			0.146		130	See
141	MICA*002		Japan MIC pop 2			0.099		152	See
142	MICA*002		Japan MIC pop 3			0.125		114	See
143	MICA*002		Spain Majorca Chueta MIC			0.158		95	See
144	MICA*002		Spain Majorca MIC			0.142		165	See
145	MICA*002		Spain Murcia MIC			0.161		154	See
146	MICA*002		Thailand North East MIC			0.176		255	See
147	MICA*002		Turkey MIC		29.2	0.154		65	See
148	MICA*002		USA Caucasian MIC pop2			0.130		242	See
149	MICA*002:01		Argentina Formosa Toba MIC			0.346		94	See
150	MICA*002:01		Argentina Formosa Wichi MIC			0.476		42	See
151	MICA*002:01		Brazil Limao Verde and Corrego Reserve Terena MIC			0.445		60	See
152	MICA*002:01		Brazil Mato Grosso do Sul Kaiowa MIC			0.641		174	See
153	MICA*002:01		Brazil Mato Grosso do Sul Nandeva MIC			0.375		89	See
154	MICA*002:01		Brazil Parana Guarani M'byá MIC			0.215		100	See
155	MICA*002:01		Brazil Parana Kaingang MIC			0.396		245	See
156	MICA*002:01		China Baotou Han MIC			0.120		104	See
157	MICA*002:01		China Zhejiang Province Han MIC			0.155		100	See
158	MICA*002:01		England Bedfordshire MIC			0.076		354	See
159	MICA*002:01		Morocco Nador Metalsa MIC			0.073		82	See
160	MICA*002:01		Nigeria South Efik MIC			0.172		32	See
161	MICA*002:01		Nigeria South Igbo MIC			0.424		46	See
162	MICA*002:01		Nigeria South Yoruba MIC			0.331		74	See
163	MICA*002:01		South Korea MIC			0.178		199	See
164	MICA*002:01		South Korea Seoul MIC			0.176		139	See
165	MICA*002:01		USA African American MIC			0.279		201	See
166	MICA*002:01		USA African American MIC pop 2			0.256		39	See
167	MICA*002:01		USA Boston African American MIC			0.300		60	See
168	MICA*002:01		USA Caucasian MIC			0.153		103	See
169	MICA*002:01		Wales MIC		18.6	0.096		166	See
170	MICA*002:02		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
171	MICA*002:02		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
172	MICA*002:02		Brazil Parana Guarani M'byá MIC			0.000		100	See
173	MICA*002:02		Brazil Parana Kaingang MIC			0.000		245	See
174	MICA*002:02		Wales MIC		0.6	0.003		166	See
175	MICA*004		Argentina Formosa Toba MIC			0.011		94	See
176	MICA*004		Argentina Formosa Wichi MIC			0.000		42	See
177	MICA*004		Brazil Limao Verde and Corrego Reserve Terena MIC			0.000		60	See
178	MICA*004		Brazil Mato Grosso do Sul Kaiowa MIC			0.003		174	See
179	MICA*004		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
180	MICA*004		Brazil Parana Guarani M'byá MIC			0.000		100	See
181	MICA*004		Brazil Parana Kaingang MIC			0.020		245	See
182	MICA*004		Brazil Parana Mixed MIC			0.119		201	See
183	MICA*004		Brazil Sao Paulo Mixed MIC		27.0	0.146		200	See
184	MICA*004		China Baotou Han MIC			0.048		104	See
185	MICA*004		China Zhejiang Province Han MIC			0.005		100	See
186	MICA*004		England Bedfordshire MIC			0.086		354	See
187	MICA*004		England MIC		17.0	0.100		118	See
188	MICA*004		Japan MIC			0.092		130	See
189	MICA*004		Japan MIC pop 2			0.082		152	See
190	MICA*004		Japan MIC pop 3			0.111		114	See
191	MICA*004		Morocco Nador Metalsa MIC			0.232		82	See
192	MICA*004		Nigeria South Efik MIC			0.219		32	See
193	MICA*004		Nigeria South Igbo MIC			0.130		46	See
194	MICA*004		Nigeria South Yoruba MIC			0.270		74	See
195	MICA*004		South Korea MIC			0.123		199	See
196	MICA*004		South Korea Seoul MIC			0.083		139	See
197	MICA*004		Spain Majorca Chueta MIC			0.200		95	See
198	MICA*004		Spain Majorca MIC			0.176		165	See
199	MICA*004		Spain Murcia MIC			0.149		154	See
200	MICA*004		Thailand North East MIC			0.035		255	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.