fisher.method: Perform Fisher's Method for combining p-values
In pmoulos/metaseqr: An R package for the analysis and result reporting of RNA-Seq data by combining multiple statistical algorithms.

Description Usage Arguments Details Value Note Author(s) References See Also Examples

Function for combining p-values by performing Fisher's method. The approach as described by Fisher's combines p-values to a statistic

S = -2 ∑^k \log p

, which follows a χ^2 distribution with 2k degrees of freedom.

1 2	fisher.method(pvals, method = c("fisher"), p.corr = c("bonferroni", "BH", "none"), zero.sub = 1e-05, na.rm = FALSE, mc.cores=NULL)

`pvals`	A matrix or data.frame containing the p-values from the single tests
`method`	A string indicating how to combine the p-values for deriving a sumary p-value. Currently only the classical approach described by Fisher is implemented.
`p.corr`	Method for correcting the summary p-values. BH: Benjamini-Hochberg (default); Bonferroni's method or no ('none') correction are currently supported.
`zero.sub`	Replacement for p-values of 0
`na.rm`	A flag indicating whether NA values should be removed from the analysis.
`mc.cores`	Currently ignored

As log(0) results in Inf we replace p-values of 0 by default with a small float. If you want to keep them as 0 you have to provide 0 as a parameter in zero.sub.

Note that only p-values between 0 and 1 are allowed to be passed to this method.

This method returns a data.frame containing the following columns

`S`	The statistic
`num.p`	The number of p-values used to calculate S
`p.value`	The overall p-value
`p.adj`	The adjusted p-value

This function was copied from the CRAN package MADAM which is no longer maintained. Recognition goes to the original author(s) below.

Karl Kugler <karl@eigenlab.net>

Fisher, R.A. (1925). Statistical Methods for Research Workers. Oliver and Boyd (Edinburgh). Moreau, Y.et al. (2003). Comparison and meta-analysis of microarray data: from the bench to the computer desk. Trends in Genetics, 19(10), 570-577.

fisher.method.perm

set.seed(123)
pp <- matrix(c(runif(20),c(0.001,0.02,0.03,0.001)), ncol=4)
pp[2,3] <- NA
fisher.method(pp) #returns one NA row
fisher.method(pp, na.rm=TRUE) #ignore NA entry in that row