levelplot(correlation,scales=list(x=list(rot=90)),pretty=TRUE,main="Spearman correlation between conditions after Normalization",xlab="Conditions",ylab="Conditions")
#A key strength of limma’s linear modelling approach, is the ability accommodate arbitrary experimental complexity. Simple designs, such as the one in this workflow, with cell type and batch, through to more complicated factorial designs and models with interaction terms can be handled relatively easily
#' Build design matrix
#' > A key strength of limma’s linear modelling approach, is the ability accommodate arbitrary experimental complexity. Simple designs, such as the one in this workflow, with cell type and batch, through to more complicated factorial designs and models with interaction terms can be handled relatively easily
#'
#' Make sure that non of the batch-factors is confounded with treatment (condition). See https://support.bioconductor.org/p/39385/ for a discussion