Description Usage Arguments Value Author(s) Examples
This function calculates the combined pvalues when multiple statistical algorithms are applied to the input dataset. It is a helper and it requires very specific arguments so it should not be used individually
1 2 3 4 5 6 7  meta.test(cp.list,
meta.p = c("simes", "bonferroni", "fisher", "dperm.min",
"dperm.max", "dperm.weight", "fperm", "whitlock",
"minp", "maxp", "weight", "pandora", "none"), counts,
sample.list, statistics, stat.args, libsize.list,
nperm = 10000, weight = rep(1/length(statistics),
length(statistics)), reprod=TRUE, multic = FALSE)

cp.list 
a named list whose names are the contrasts
requested from metaseqr. Each member is a pvalue matrix
whose colnames are the names of the statistical tests
applied to the data. See the main 
meta.p 
the pvalue combination method to use. See
the main 
counts 
the normalized and possibly filtered read
counts matrix. See the main 
sample.list 
the list containing condition names
and the samples under each condition. See the main

statistics 
the statistical algorithms used in
metaseqr. See the main 
stat.args 
the parameters for each statistical
argument. See the main 
libsize.list 
a list with library sizes. See the
main 
nperm 
the number of permutations (Monte Carlo simulations) to perform. 
weight 
a numeric vector of weights for each statistical algorithm. 
reprod 
create reproducible permutations when

multic 
use multiple cores to execute the
premutations. This is an external parameter and implies
the existence of multicore package in the execution
environment. See the main 
A named list with combined pvalues. The names are the contrasts and the list members are combined pvalue vectors, one for each contrast.
Panagiotis Moulos
1  # Not yet available

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