I'm trying to perform jackknifing or bootstrapping on the P-values from 6 data sets (which have previously been combined in a meta analysis). However, I'm not quite clear on the input and what the results are actually telling me. 

My aim is to assess if my top genes will remain robust if I jackknife the P-values of the data sets.

I've yet to find an answer online since there doesn't appear to be anything concrete on how to interpret bias values or in fact how to input for various data sets. So here's a run down of what I've done so far. 

#xdata = 6 columns (data sets) with 8000 P.values for various genes 
combine <- function(x) {pchisq(-2 * sum(log(x)),df=2*length(x),lower=FALSE)}
results <- boot(combine,xdata)

Question:

That function doesn't actually work across my matrix. It produces 0 values across the board...not sure what's wrong/

Thank you!