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이환 형제 자료에 대한 유전적 연관성 분석 방법의 비교

DC FieldValueLanguage
dc.contributor.author고민진-
dc.contributor.author송기준-
dc.date.accessioned2015-04-24T17:02:10Z-
dc.date.available2015-04-24T17:02:10Z-
dc.date.issued2009-
dc.identifier.issn1225-066X-
dc.identifier.urihttps://ir.ymlib.yonsei.ac.kr/handle/22282913/104637-
dc.description.abstractFor complex diseases such as diabetes, hypertension, it is believed that model-free methods might work better because they do not require a precise knowledge of the mode of inheritance controlling the disease trait. This is done by estimating the sharing probabilities that a pair shares zero, one, or two alleles identical by descent(IBD) and has some specific branches of test procedure, i.e., the mean test, the proportion test, and the minmax test. Among them, the minmax test is known to be more robust than others regardless of genetic mode of inheritance in current use. In this study, we compared the power of the methods which are based on minmax test and considering weighting schemes for sib-pairs to analyze sibship data. In simulation result, we found that the method based on Suarez' was more powerful than any others without respect to marker allele frequency, genetic mode of inheritance, sibship size. Also, The power of both Suarez- and Hodge-based methods was higher when marker allele frequency and sibship size were higher, and this result was remarkable in dominant mode of inheritance especially-
dc.description.statementOfResponsibilityopen-
dc.format.extent329~340-
dc.relation.isPartOfKorean Journal of Applied Statistics (응용통계연구)-
dc.rightsCC BY-NC-ND 2.0 KR-
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/2.0/kr/-
dc.title이환 형제 자료에 대한 유전적 연관성 분석 방법의 비교-
dc.title.alternativeComparison of Methods for Linkage Analysis of Affected Sibship Data-
dc.typeArticle-
dc.contributor.collegeCollege of Medicine (의과대학)-
dc.contributor.departmentDept. of Biostatistics (의학통계학)-
dc.contributor.googleauthor고민진-
dc.contributor.googleauthor임길섭-
dc.contributor.googleauthor이학배-
dc.contributor.googleauthor송기준-
dc.admin.authorfalse-
dc.admin.mappingfalse-
dc.contributor.localIdA00118-
dc.contributor.localIdA02016-
dc.relation.journalcodeJ01964-
dc.subject.keywordLinkage analysis-
dc.subject.keywordaffected sibship data-
dc.subject.keywordweighted method-
dc.subject.keywordpower-
dc.contributor.alternativeNameGo, Min Jin-
dc.contributor.alternativeNameSong, Ki Jun-
dc.contributor.affiliatedAuthorGo, Min Jin-
dc.contributor.affiliatedAuthorSong, Ki Jun-
dc.citation.volume22-
dc.citation.number2-
dc.citation.startPage329-
dc.citation.endPage340-
dc.identifier.bibliographicCitationKorean Journal of Applied Statistics (응용통계연구), Vol.22(2) : 329-340, 2009-
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Biomedical Systems Informatics (의생명시스템정보학교실) > 1. Journal Papers

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