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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 601 to 700 (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
601	MICA*017		Wales MIC		9.0	0.048		166	See
602	MICA*018		Argentina Formosa Toba MIC			0.000		94	See
603	MICA*018		Argentina Formosa Wichi MIC			0.000		42	See
604	MICA*018		Brazil Limao Verde and Corrego Reserve Terena MIC			0.000		60	See
605	MICA*018		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
606	MICA*018		Brazil Mato Grosso do Sul Nandeva MIC			0.057		89	See
607	MICA*018		Brazil Parana Guarani M'byá MIC			0.000		100	See
608	MICA*018		Brazil Parana Japanese MIC			0.008		190	See
609	MICA*018		Brazil Parana Kaingang MIC			0.000		245	See
610	MICA*018		Brazil Parana Mixed MIC			0.050		201	See
611	MICA*018		Brazil Sao Paulo Mixed MIC		5.0	0.025		200	See
612	MICA*018		China Baotou Han MIC			0.005		104	See
613	MICA*018		China Zhangjiajie Tujias MIC			0.000		187	See
614	MICA*018		England Bedfordshire MIC			0.032		354	See
615	MICA*018		England Northwest MIC		4.4	0.022		250	See
616	MICA*018		Morocco Nador Metalsa MIC			0.024		82	See
617	MICA*018		Slovenia MIC		12.9	0.067		70	See
618	MICA*018		Spain Majorca Chueta MIC			0.042		95	See
619	MICA*018		Spain Majorca MIC			0.051		165	See
620	MICA*018		Spain Murcia MIC			0.025		154	See
621	MICA*018		Thailand North East MIC			0.061		255	See
622	MICA*018		Turkey MIC		12.3	0.077		65	See
623	MICA*018		USA African American MIC			0.025		201	See
624	MICA*018		USA Caucasian MIC			0.035		103	See
625	MICA*018		Wales MIC		6.6	0.033		166	See
626	MICA*019		Argentina Formosa Toba MIC			0.000		94	See
627	MICA*019		Argentina Formosa Wichi MIC			0.000		42	See
628	MICA*019		Brazil Limao Verde and Corrego Reserve Terena MIC			0.000		60	See
629	MICA*019		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
630	MICA*019		Brazil Mato Grosso do Sul Nandeva MIC			0.006		89	See
631	MICA*019		Brazil Parana Guarani M'byá MIC			0.000		100	See
632	MICA*019		Brazil Parana Japanese MIC			0.029		190	See
633	MICA*019		Brazil Parana Kaingang MIC			0.000		245	See
634	MICA*019		Brazil Parana Mixed MIC			0.010		201	See
635	MICA*019		Brazil Sao Paulo Mixed MIC		4.5	0.023		200	See
636	MICA*019		China Baotou Han MIC			0.039		104	See
637	MICA*019		China Guangxi Zhuang MIC			0.103		209	See
638	MICA*019		China Zhangjiajie Tujias MIC			0.206		187	See
639	MICA*019		China Zhejiang Province Han MIC			0.095		100	See
640	MICA*019		England Bedfordshire MIC			0.028		354	See
641	MICA*019		Japan MIC			0.035		130	See
642	MICA*019		Morocco Nador Metalsa MIC			0.012		82	See
643	MICA*019		South Korea Seoul MIC			0.004		139	See
644	MICA*019		Spain Majorca Chueta MIC			0.021		95	See
645	MICA*019		Spain Majorca MIC			0.018		165	See
646	MICA*019		Thailand North East MIC			0.153		255	See
647	MICA*019		USA African American MIC			0.010		201	See
648	MICA*019		USA Caucasian MIC			0.025		103	See
649	MICA*019		Wales MIC		3.0	0.021		166	See
650	MICA*020		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
651	MICA*020		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
652	MICA*020		Brazil Parana Guarani M'byá MIC			0.005		100	See
653	MICA*020		Brazil Parana Kaingang MIC			0.165		245	See
654	MICA*020		China Zhangjiajie Tujias MIC			0.000		187	See
655	MICA*020		Thailand North East MIC			0.004		255	See
656	MICA*020		Turkey MIC		7.7	0.038		65	See
657	MICA*022		England Northwest MIC		0.0	0.000		250	See
658	MICA*022		Wales MIC		0.0	0.000		166	See
659	MICA*023		China Zhangjiajie Tujias MIC			0.000		187	See
660	MICA*023		England Northwest MIC		0.0	0.000		250	See
661	MICA*023		Spain Murcia MIC			0.012		154	See
662	MICA*023		Wales MIC		0.0	0.000		166	See
663	MICA*024		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
664	MICA*024		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
665	MICA*024		Brazil Parana Guarani M'byá MIC			0.000		100	See
666	MICA*024		Brazil Parana Kaingang MIC			0.000		245	See
667	MICA*024		England Northwest MIC		0.0	0.000		250	See
668	MICA*024		Wales MIC		0.0	0.000		166	See
669	MICA*025		England Northwest MIC		0.0	0.000		250	See
670	MICA*025		Wales MIC		0.0	0.000		166	See
671	MICA*026		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
672	MICA*026		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
673	MICA*026		Brazil Parana Guarani M'byá MIC			0.000		100	See
674	MICA*026		Brazil Parana Kaingang MIC			0.000		245	See
675	MICA*026		China Zhangjiajie Tujias MIC			0.000		187	See
676	MICA*026		Thailand North East MIC			0.014		255	See
677	MICA*027		Argentina Formosa Toba MIC			0.309		94	See
678	MICA*027		Argentina Formosa Wichi MIC			0.310		42	See
679	MICA*027		Brazil Limao Verde and Corrego Reserve Terena MIC			0.352		60	See
680	MICA*027		Brazil Mato Grosso do Sul Kaiowa MIC			0.112		174	See
681	MICA*027		Brazil Mato Grosso do Sul Nandeva MIC			0.136		89	See
682	MICA*027		Brazil Parana Guarani M'byá MIC			0.395		100	See
683	MICA*027		Brazil Parana Japanese MIC			0.121		190	See
684	MICA*027		Brazil Parana Kaingang MIC			0.008		245	See
685	MICA*027		Brazil Parana Mixed MIC			0.047		201	See
686	MICA*027		China Baotou Han MIC			0.053		104	See
687	MICA*027		China Guangxi Zhuang MIC			0.019		209	See
688	MICA*027		China Zhangjiajie Tujias MIC			0.000		187	See
689	MICA*027		China Zhejiang Province Han MIC			0.070		100	See
690	MICA*027		England Northwest MIC		1.6	0.008		250	See
691	MICA*027		Morocco Nador Metalsa MIC			0.006		82	See
692	MICA*027		Slovenia MIC		1.4	0.007		70	See
693	MICA*027		South Korea MIC			0.136		199	See
694	MICA*027		South Korea Seoul MIC			0.050		139	See
695	MICA*027		Spain Murcia MIC			0.025		154	See
696	MICA*027		USA African American MIC			0.005		201	See
697	MICA*027		USA Caucasian MIC			0.049		103	See
698	MICA*027		Wales MIC		1.2	0.006		166	See
699	MICA*028		Wales MIC		0.0	0.000		166	See
700	MICA*029		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	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.