I know there are a lot of packages out there to perform statistical tests on microarray expression data and I dont know how to adapt them to use for nanostring data which is similar to microarray but the nanostring result files have different extensions from microarrays.
I have done background correction, positive and negative control normalization. Are there any statistical tests that I can perform as part of data assessment after normalization and make plots in R?because I want to cluster this data to get groups of genes with similar expression patterns. My data contains samples across columns and genes or probes in the rows with normalized values. I know how to cluster this data but what statistical tests can I perform and how would they be useful in interpreting the data. Can I use the same packages in bioconductor that have been designed for microarrays?
Can I perform a Q-test and FDR on normalized expression data in R?
I do not know, but I suspect that the popularity of R has made such a test or package available. I found this link - http://strimmerlab.org/notes/fdr.html - for just such a test.