Power Calculation of multiple factors design of RNA-sequencing study
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Dear Community, I am working on the power calculation of a multiple factors design of RNA-Sequencing study. My project has three factors, I use generalized linear model to fit the model including three main effects, two-way interaction terms and the three-way interaction term. The model fitting is implemented by using DESeq and edgeR package. We would like to see how much power we have for this design. My question is: Can the power calculation function provided in RNASeqPower R package fit in our setup? Since we have three factors instead of only compare two conditions. Thanks, Yanzhu -- output of sessionInfo(): R version 3.0.1 (2013-05-16) Platform: x86_64-w64-mingw32/x64 (64-bit) locale: [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252 LC_NUMERIC=C [5] LC_TIME=English_United States.1252 attached base packages: [1] parallel stats graphics grDevices utils datasets methods base other attached packages: [1] RColorBrewer_1.0-5 DESeq_1.12.1 lattice_0.20-15 locfit_1.5-9.1 Biobase_2.20.1 BiocGenerics_0.6.0 edgeR_3.2.4 limma_3.16.8 loaded via a namespace (and not attached): [1] annotate_1.38.0 AnnotationDbi_1.22.6 DBI_0.2-7 genefilter_1.42.0 geneplotter_1.38.0 grid_3.0.1 IRanges_1.18.4 RSQLite_0.11.4 [9] splines_3.0.1 stats4_3.0.1 survival_2.37-4 tools_3.0.1 XML_3.98-1.1 xtable_1.7-1 > -- Sent via the guest posting facility at bioconductor.org.
edgeR DESeq RNASeqPower edgeR DESeq RNASeqPower • 655 views
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