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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 701 to 800 (from 813) records

Pages:

1 2 3 4 5 6 7 8 9 of 9

Line	Allele	Population		% of individuals that have the allele		Allele Frequency (3_decimals)		Sample Size	IMGT/HLA Database¹	Distribution²	MIC-HLA Associations³
701	MICA*029		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
702	MICA*029		Brazil Parana Guarani M'byá MIC			0.000		100	See
703	MICA*029		Brazil Parana Kaingang MIC			0.000		245	See
704	MICA*029		Brazil Sao Paulo Mixed MIC		0.5	0.003		200	See
705	MICA*029		Turkey MIC		1.5	0.008		65	See
706	MICA*029		Wales MIC		0.6	0.003		166	See
707	MICA*030		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
708	MICA*030		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
709	MICA*030		Brazil Parana Guarani M'byá MIC			0.000		100	See
710	MICA*030		Brazil Parana Kaingang MIC			0.000		245	See
711	MICA*030		China Zhangjiajie Tujias MIC			0.000		187	See
712	MICA*030		Spain Murcia MIC			0.012		154	See
713	MICA*030		USA African American MIC			0.005		201	See
714	MICA*030		USA Caucasian MIC			0.000		103	See
715	MICA*030		Wales MIC		0.0	0.000		166	See
716	MICA*031		Wales MIC		0.0	0.000		166	See
717	MICA*032		Wales MIC		0.0	0.000		166	See
718	MICA*033		China Baotou Han MIC			0.005		104	See
719	MICA*033		China Guangxi Zhuang MIC			0.007		209	See
720	MICA*033		China Zhangjiajie Tujias MIC			0.000		187	See
721	MICA*033		Spain Murcia MIC			0.012		154	See
722	MICA*033		Wales MIC		0.0	0.000		166	See
723	MICA*034		Wales MIC		0.0	0.000		166	See
724	MICA*035		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
725	MICA*035		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
726	MICA*035		Brazil Parana Guarani M'byá MIC			0.000		100	See
727	MICA*035		Brazil Parana Kaingang MIC			0.000		245	See
728	MICA*035		Morocco Nador Metalsa MIC			0.006		82	See
729	MICA*035		Wales MIC		0.0	0.000		166	See
730	MICA*036		Wales MIC		0.0	0.000		166	See
731	MICA*037		Wales MIC		0.0	0.000		166	See
732	MICA*038		Wales MIC		0.0	0.000		166	See
733	MICA*039		Wales MIC		0.0	0.000		166	See
734	MICA*040		Wales MIC		0.0	0.000		166	See
735	MICA*041		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
736	MICA*041		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
737	MICA*041		Brazil Parana Guarani M'byá MIC			0.000		100	See
738	MICA*041		Brazil Parana Kaingang MIC			0.000		245	See
739	MICA*041		Brazil Sao Paulo Mixed MIC		0.5	0.003		200	See
740	MICA*041		Nigeria South Efik MIC			0.031		32	See
741	MICA*041		Nigeria South Igbo MIC			0.098		46	See
742	MICA*041		Nigeria South Yoruba MIC			0.020		74	See
743	MICA*041		USA African American MIC			0.022		201	See
744	MICA*041		USA African American MIC pop 2			0.013		39	See
745	MICA*041		USA Boston African American MIC			0.158		60	See
746	MICA*041		USA Caucasian MIC			0.000		103	See
747	MICA*041		Wales MIC		0.0	0.000		166	See
748	MICA*042		Wales MIC		0.0	0.000		166	See
749	MICA*043		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
750	MICA*043		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
751	MICA*043		Brazil Parana Guarani M'byá MIC			0.000		100	See
752	MICA*043		Brazil Parana Kaingang MIC			0.000		245	See
753	MICA*043		Brazil Sao Paulo Mixed MIC		0.5	0.003		200	See
754	MICA*043		Wales MIC		0.0	0.000		166	See
755	MICA*044		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
756	MICA*044		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
757	MICA*044		Brazil Parana Guarani M'byá MIC			0.000		100	See
758	MICA*044		Brazil Parana Kaingang MIC			0.000		245	See
759	MICA*044		Wales MIC		0.0	0.000		166	See
760	MICA*045		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
761	MICA*045		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
762	MICA*045		Brazil Parana Guarani M'byá MIC			0.000		100	See
763	MICA*045		Brazil Parana Japanese MIC			0.008		190	See
764	MICA*045		Brazil Parana Kaingang MIC			0.000		245	See
765	MICA*045		China Baotou Han MIC			0.082		104	See
766	MICA*045		China Guangxi Zhuang MIC			0.172		209	See
767	MICA*045		China Zhangjiajie Tujias MIC			0.000		187	See
768	MICA*045		China Zhejiang Province Han MIC			0.015		100	See
769	MICA*045		South Korea Seoul MIC			0.032		139	See
770	MICA*045		Wales MIC		0.0	0.000		166	See
771	MICA*046		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
772	MICA*046		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
773	MICA*046		Brazil Parana Guarani M'byá MIC			0.000		100	See
774	MICA*046		Brazil Parana Kaingang MIC			0.000		245	See
775	MICA*046		Brazil Parana Mixed MIC			0.000		201	See
776	MICA*046		China Zhangjiajie Tujias MIC			0.000		187	See
777	MICA*046		Morocco Nador Metalsa MIC			0.012		82	See
778	MICA*046		Spain Murcia MIC			0.006		154	See
779	MICA*046		Wales MIC		0.0	0.000		166	See
780	MICA*047		Argentina Formosa Toba MIC			0.000		94	See
781	MICA*047		Argentina Formosa Wichi MIC			0.000		42	See
782	MICA*047		Brazil Limao Verde and Corrego Reserve Terena MIC			0.000		60	See
783	MICA*047		China Zhangjiajie Tujias MIC			0.000		187	See
784	MICA*047		USA African American MIC			0.000		201	See
785	MICA*047		USA Caucasian MIC			0.005		103	See
786	MICA*047		Wales MIC		0.0	0.000		166	See
787	MICA*048		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
788	MICA*048		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
789	MICA*048		Brazil Parana Guarani M'byá MIC			0.000		100	See
790	MICA*048		Brazil Parana Kaingang MIC			0.000		245	See
791	MICA*048		China Zhangjiajie Tujias MIC			0.000		187	See
792	MICA*048		Japan MIC pop 2			0.118		152	See
793	MICA*048		Wales MIC		0.0	0.000		166	See
794	MICA*049		Brazil Parana Japanese MIC			0.005		190	See
795	MICA*049		China Guangxi Zhuang MIC			0.002		209	See
796	MICA*049		China Zhangjiajie Tujias MIC			0.000		187	See
797	MICA*049		China Zhejiang Province Han MIC			0.035		100	See
798	MICA*049		South Korea Seoul MIC			0.079		139	See
799	MICA*049		Wales MIC		0.0	0.000		166	See
800	MICA*050		China Zhangjiajie Tujias MIC			0.000		187	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.