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pubmed-article:16909391pubmed:dateCreated2006-8-15lld:pubmed
pubmed-article:16909391pubmed:abstractTextA significant proportion of the variation between individuals in gene expression levels is genetic, and it is likely that these differences correlate with phenotypic differences or with risk of disease. Cis-acting polymorphisms are important in determining interindividual differences in gene expression that lead to allelic expression imbalance, which is the unequal expression of homologous alleles in individuals heterozygous for such a polymorphism. This expression imbalance can be detected using a transcribed polymorphism, and, once it is established, the next step is to identify the polymorphisms that are responsible for or predictive of allelic expression levels. We present an expectation-maximization algorithm for such analyses, providing a formal statistical framework to test whether a candidate polymorphism is associated with allelic expression differences.lld:pubmed
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pubmed-article:16909391pubmed:authorpubmed-author:HeighwayJJlld:pubmed
pubmed-article:16909391pubmed:authorpubmed-author:TeareM DMDlld:pubmed
pubmed-article:16909391pubmed:authorpubmed-author:Santibáñez...lld:pubmed
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pubmed-article:16909391pubmed:volume79lld:pubmed
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pubmed-article:16909391pubmed:pagination539-43lld:pubmed
pubmed-article:16909391pubmed:dateRevised2009-11-18lld:pubmed
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pubmed-article:16909391pubmed:year2006lld:pubmed
pubmed-article:16909391pubmed:articleTitleAn expectation-maximization algorithm for the analysis of allelic expression imbalance.lld:pubmed
pubmed-article:16909391pubmed:affiliationDivision of Genomic Medicine, University of Sheffield, United Kingdom.lld:pubmed
pubmed-article:16909391pubmed:publicationTypeJournal Articlelld:pubmed
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