table of fold change P value and FDR for comparison of groups

[#1]

I have datasets with many response variables (~15K) and many samples (~7K).  I have clustered the samples based on prior knowledge into 10 clusters, and need to define the variables that are characteristic for each.  I want to generate a table/matrix that lists all the variables vs the clusters,  with the fold change (ratio) in mean response values (each cluster vs all other samples together) with P values (either corrected or not) and FDR if possible. 

Hoping there is a simple way to generate this.   ANOVA or negative binomial options would be helpful.

[#2]

I would suggest you look at the screening tools: Analyze > Screening > Response Screening.  I often use the response screening platform for what I think you are trying to do.  The documentaiton is at:

https://www.jmp.com/support/help/14/response-screening.shtml

[#3]

Response screening gives the difference in means.  However for our purposes the difference in mean values is not as relevant as the difference in the ratios of each gropup mean to the whole.  

Hence a table of fold change with P values and FDR is needed. I wonder if their are availble scripts that do this.

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thanks

[#4]

My experience in such cases was in virology when the useful information was a doubling but the response was titer. So a transformation could make the response more meaningful transforming as Ln( titer ) / Ln( 2 ). (That is effectively the logarithm base 2.) You can do this transformation with a column formula without the need for a separate script.