Hi,
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?
Many thanks!!!
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written
by
Diana
1 answer
Have you tried a Q test, or False Discovery Rate? You can set FDR to 0.05, or even 0.10. Some even set a threshold of 0.2 for FDR.
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.
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