## ----knitr, echo=FALSE, results='hide'----------------------------------- library("knitr") opts_chunk$set(tidy=FALSE,dev="pdf",fig.show="hide", fig.width=4,fig.height=4.5, message=FALSE, warning=FALSE) ## ----style, eval=TRUE, echo=FALSE, results="asis"--------------------------------------- BiocStyle::latex() ## ----options, results="hide", echo=FALSE-------------------------------------- options(digits=3, width=80, prompt=" ", continue=" ") opts_chunk$set(comment=NA, fig.width=7, fig.height=7) ## ----initialize, cache=FALSE, echo=FALSE-------------------------------------- # load library library(variancePartition) # optional step to run analysis in parallel on multicore machines # Here use 4 threads # This is strongly recommended since the analysis # can be computationally intensive library(doParallel) cl <- makeCluster(4) registerDoParallel(cl) ## ----corStruct, cache=TRUE---------------------------------------------------- # Fit linear mixed model and examine correlation stucture # for one gene data(varPartData) form <- ~ Age + (1|Individual) + (1|Tissue) fitList <- fitVarPartModel( geneExpr[1:2,], form, info ) # focus on one gene fit = fitList[[1]] ## ----corStructa, cache=TRUE--------------------------------------------------- # Figure 1a # correlation structure based on similarity within Individual # reorder samples based on clustering plotCorrStructure( fit, "Individual" ) ## ----corStructb, cache=TRUE--------------------------------------------------- # Figure 1b # use original order of samples plotCorrStructure( fit, "Individual", reorder=FALSE ) ## ----corStructc, cache=TRUE--------------------------------------------------- # Figure 1c # correlation structure based on similarity within Tissue # reorder samples based on clustering plotCorrStructure( fit, "Tissue" ) ## ----corStructd, cache=TRUE--------------------------------------------------- # Figure 1d # use original order of samples plotCorrStructure( fit, "Tissue", reorder=FALSE ) ## ----corStructe, cache=TRUE--------------------------------------------------- # Figure 2a # correlation structure based on similarity within Individual *and* Tissue # reorder samples based on clustering plotCorrStructure( fit ) ## ----corStructf, cache=TRUE--------------------------------------------------- # Figure 2b # use original order of samples plotCorrStructure( fit, reorder=FALSE ) ## ----resetOptions, results="hide", echo=FALSE--------------------------------- options(prompt="> ", continue="+ ")