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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 501 to 600 (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
501	MICA*012		Spain Majorca Chueta MIC			0.084		95	See
502	MICA*012		Spain Majorca MIC			0.018		165	See
503	MICA*012		Thailand North East MIC			0.031		255	See
504	MICA*012		Turkey MIC		6.2	0.031		65	See
505	MICA*012		USA Caucasian MIC pop2			0.020		242	See
506	MICA*012:01		Argentina Formosa Toba MIC			0.000		94	See
507	MICA*012:01		Argentina Formosa Wichi MIC			0.000		42	See
508	MICA*012:01		Brazil Limao Verde and Corrego Reserve Terena MIC			0.000		60	See
509	MICA*012:01		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
510	MICA*012:01		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
511	MICA*012:01		Brazil Parana Guarani M'byá MIC			0.000		100	See
512	MICA*012:01		Brazil Parana Kaingang MIC			0.002		245	See
513	MICA*012:01		China Baotou Han MIC			0.010		104	See
514	MICA*012:01		China Guangxi Zhuang MIC			0.079		209	See
515	MICA*012:01		China Zhangjiajie Tujias MIC			0.107		187	See
516	MICA*012:01		China Zhejiang Province Han MIC			0.050		100	See
517	MICA*012:01		England Bedfordshire MIC			0.011		354	See
518	MICA*012:01		South Korea Seoul MIC			0.094		139	See
519	MICA*012:01		USA African American MIC			0.015		201	See
520	MICA*012:01		USA Caucasian MIC			0.025		103	See
521	MICA*012:01		Wales MIC		3.6	0.018		166	See
522	MICA*013		China Shanghai Han MIC			0.010		183	See
523	MICA*013		China Xinjiang Province Uygur MIC			0.000		66	See
524	MICA*013		China Yunnan Province Dai MIC			0.000		41	See
525	MICA*013		England MIC		0.0	0.000		118	See
526	MICA*013		England Northwest MIC		0.0	0.000		250	See
527	MICA*013		Wales MIC		0.0	0.000		166	See
528	MICA*014		England Northwest MIC		0.0	0.000		250	See
529	MICA*014		Wales MIC		0.0	0.000		166	See
530	MICA*015		Brazil Mato Grosso do Sul Kaiowa MIC			0.006		174	See
531	MICA*015		Brazil Mato Grosso do Sul Nandeva MIC			0.006		89	See
532	MICA*015		Brazil Parana Guarani M'byá MIC			0.000		100	See
533	MICA*015		Brazil Parana Kaingang MIC			0.016		245	See
534	MICA*015		Brazil Parana Mixed MIC			0.010		201	See
535	MICA*015		Brazil Sao Paulo Mixed MIC		4.0	0.020		200	See
536	MICA*015		China Zhangjiajie Tujias MIC			0.000		187	See
537	MICA*015		England Northwest MIC		0.0	0.000		250	See
538	MICA*015		Morocco Nador Metalsa MIC			0.018		82	See
539	MICA*015		Spain Majorca Chueta MIC			0.000		95	See
540	MICA*015		Spain Majorca MIC			0.006		165	See
541	MICA*015		Spain Murcia MIC			0.025		154	See
542	MICA*015		USA African American MIC			0.027		201	See
543	MICA*015		USA Caucasian MIC			0.000		103	See
544	MICA*015		USA Caucasian MIC pop2			0.000		242	See
545	MICA*015		Wales MIC		0.0	0.000		166	See
546	MICA*016		Argentina Formosa Toba MIC			0.000		94	See
547	MICA*016		Argentina Formosa Wichi MIC			0.000		42	See
548	MICA*016		Brazil Limao Verde and Corrego Reserve Terena MIC			0.000		60	See
549	MICA*016		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
550	MICA*016		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
551	MICA*016		Brazil Parana Guarani M'byá MIC			0.005		100	See
552	MICA*016		Brazil Parana Japanese MIC			0.013		190	See
553	MICA*016		Brazil Parana Kaingang MIC			0.016		245	See
554	MICA*016		Brazil Parana Mixed MIC			0.027		201	See
555	MICA*016		Brazil Sao Paulo Mixed MIC		4.5	0.023		200	See
556	MICA*016		China Baotou Han MIC			0.010		104	See
557	MICA*016		China Shanghai Han MIC			0.010		183	See
558	MICA*016		China Xinjiang Province Uygur MIC			0.020		66	See
559	MICA*016		China Yunnan Province Dai MIC			0.000		41	See
560	MICA*016		China Zhangjiajie Tujias MIC			0.000		187	See
561	MICA*016		England Bedfordshire MIC			0.011		354	See
562	MICA*016		England MIC		2.0	0.008		118	See
563	MICA*016		England Northwest MIC		11.2	0.058		250	See
564	MICA*016		Japan MIC pop 2			0.030		152	See
565	MICA*016		Morocco Nador Metalsa MIC			0.018		82	See
566	MICA*016		Slovenia MIC		8.6	0.044		70	See
567	MICA*016		Spain Majorca Chueta MIC			0.089		95	See
568	MICA*016		Spain Majorca MIC			0.024		165	See
569	MICA*016		Spain Murcia MIC			0.071		154	See
570	MICA*016		Thailand North East MIC			0.002		255	See
571	MICA*016		Turkey MIC		16.9	0.092		65	See
572	MICA*016		USA African American MIC			0.000		201	See
573	MICA*016		USA Caucasian MIC			0.010		103	See
574	MICA*016		USA Caucasian MIC pop2			0.020		242	See
575	MICA*016		Wales MIC		1.2	0.006		166	See
576	MICA*017		Argentina Formosa Toba MIC			0.000		94	See
577	MICA*017		Argentina Formosa Wichi MIC			0.000		42	See
578	MICA*017		Brazil Limao Verde and Corrego Reserve Terena MIC			0.000		60	See
579	MICA*017		Brazil Mato Grosso do Sul Kaiowa MIC			0.000		174	See
580	MICA*017		Brazil Mato Grosso do Sul Nandeva MIC			0.000		89	See
581	MICA*017		Brazil Parana Guarani M'byá MIC			0.000		100	See
582	MICA*017		Brazil Parana Japanese MIC			0.005		190	See
583	MICA*017		Brazil Parana Kaingang MIC			0.000		245	See
584	MICA*017		Brazil Parana Mixed MIC			0.017		201	See
585	MICA*017		Brazil Sao Paulo Mixed MIC		1.5	0.008		200	See
586	MICA*017		China Baotou Han MIC			0.019		104	See
587	MICA*017		China Guangxi Zhuang MIC			0.002		209	See
588	MICA*017		China Zhangjiajie Tujias MIC			0.000		187	See
589	MICA*017		England Bedfordshire MIC			0.035		354	See
590	MICA*017		England Northwest MIC		8.0	0.041		250	See
591	MICA*017		Morocco Nador Metalsa MIC			0.018		82	See
592	MICA*017		Slovenia MIC		7.1	0.036		70	See
593	MICA*017		South Korea Seoul MIC			0.004		139	See
594	MICA*017		Spain Majorca Chueta MIC			0.053		95	See
595	MICA*017		Spain Majorca MIC			0.012		165	See
596	MICA*017		Spain Murcia MIC			0.012		154	See
597	MICA*017		Thailand North East MIC			0.022		255	See
598	MICA*017		Turkey MIC		1.5	0.008		65	See
599	MICA*017		USA African American MIC			0.005		201	See
600	MICA*017		USA Caucasian MIC			0.025		103	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.