meta.test {metaseqR} | R Documentation |
This function calculates the combined p-values 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
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 p-value matrix
whose colnames are the names of the statistical tests
applied to the data. See the main |
meta.p |
the p-value 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 p-values. The names are the contrasts and the list members are combined p-value vectors, one for each contrast.
Panagiotis Moulos
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