fisher.method.perm: Derive a p-value for a summary statistic of p-values by...
In 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

Given a set of p-values and a summary statistic S:

S = -2 ∑ \log p,

a p-value for this statistic can be derived by randomly generating summary statistics [Rhodes,2002]. Therefore, a p-value is randomly sampled from each contributing study and a random statistic is calculated. The fraction of random statistics greater or equal to S then gives the p-value.

1 2	fisher.method.perm(pvals, p.corr = c("bonferroni", "BH", "none"), zero.sub = 1e-05, B = 10000, mc.cores = NULL, blinker = 1000)

`pvals`	A matrix or data.frame containing the p-values from the single tests
`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
`B`	Number of random statistics
`mc.cores`	Number of cores used for calculating the permutations. If not `NULL` the `multicore` package is used for parallelization with the given number of cores.
`blinker`	An indicator that prints "`=`" after each `blinker` rows of `pvals` in order to follow the progress.

At the moment this function only supports situations were all passed p-values are not NA. We plan on extending this functionality in upcoming versions.

For large data sets and/or large B we strongly recommend using the mc.cores option as the calculation will otherwise be computationally demanding. This will call the mclapply function from the multicore package, which you will have to install in that case.

By default a blinker (a small string "=") is shown after each 1000 rows that were computed. This function allows you to assess the progress of the analysis. If you don't want to see the blinker set it to NA.

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This function was copied from the CRAN package MADAM which is no longer maintained.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>

Rhodes, D. R., (2002). Meta-analysis of microarrays: interstudy alidation of gene expression profiles reveals pathway dysregulation in prostate cancer. Cancer research, 62(15), 4427-33.

fisher.sum, fisher.method

  set.seed(123)
  pp <- matrix(c(runif(20),c(0.001,0.02,0.03,0.001)), ncol=4)
  fisher.method.perm(pp, B=10, blinker=1)
  ## Not run: 
    fisher.method.perm(pp, B=10000, mc.cores=3, blinker=1) #use multicore
  
## End(Not run)