Improving The Output Of Signaling Pathway Impact Analysis
AbstractRecently biologists want to fi nd out the significant gene sets instead of individual gene. Many packages in different software mostly in R language were developed to find out the gene sets which are significantly regulated. Among them some packages are able to discover up and down regulation as well. Signaling pathway impact analysis (SPIA) is one of them. In this study an approach is mentioned which can be improved the output of SPIA. I proposed that using moderated t values gives more significant results instead of using logFC (log fold change) from Limma’s output in order to calculate probability of perturbation in SPIA.
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Bibliographic InfoArticle provided by Romanian Statistical Review in its journal Romanian Statistical Review.
Volume (Year): 61 (2013)
Issue (Month): 3 (April)
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Microarray; Gene; Signaling pathway; False discovery rate (FDR); Fold changes; and Moderated t value;
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- Smyth Gordon K, 2004. "Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 3(1), pages 1-28, February.
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