I am working with NanoString transcriptomics targeted data panel (containing 800 gene panel), the raw counts data was normalized in the nSolver Data Analysis software. I have the normalized data, and would like to use
limma for further analysis like filtering and statistical modelling. I would like to perform filter by expression on the normalized data matrix, it seems like in
limma this type of filtering could be performed only on the raw data (counts). Is there a functionality that I can use this normalized matrix in
limma to perform filtering by gene expression.
For instance, the below functionality I use in RNA-Seq analysis:
dge <- DGEList(counts=counts) The next step is to remove rows that consistently have zero or very low counts. One can for example use keep <- filterByExpr(dge, design) dge <- dge[keep,,keep.lib.sizes=FALSE] dge <- calcNormFactors(dge)
Thank you in advance.