Closed ojziff closed 3 years ago
Dear Oliver,
Regarding your first question: Indeed the run_viper()
function requires normalised gene expression data
Regarding your second question: If you would like to compare both datasets I would recommend to normalise the sample all-together and then apply viper on the combined matrix. However, please note that we are not the developer of the underlying viper()
function. We are just providing a wrapper to use it with our dorothea regulons. You might consider to address this question to the viper developers.
Best wishes, Christian
Dear team,
Thank you for this excellent package.
I am trying to use
run_viper
function with the dorothea regulons on two different datasets and look for overlap between the two datasets.For the gene_expression input to run_viper, is this expecting normalised counts? I was planning to use the [http://bioconductor.org/packages/devel/bioc/vignettes/DESeq2/inst/doc/DESeq2.html#variance-stabilizing-transformation](variance stabilised values from DESeq2) for this - is this correct?
Because I am interested in the enrichment similarities between two datasets would you advise that the input should contain the gene counts for all samples from both datasets together like:
Or should I perform run_viper separately for both datasets? and then merge output matrices i.e.:
Presumably if together is better then i should run DESeq2
vst
function on all samples together too?Many thanks for your help! Oliver