reSample-methods: Compute enrichment analysis on an 'Enrichment' object
In snpEnrichment: SNPs Enrichment Analysis

Description Usage Arguments Value Author(s) See Also Examples

After initFiles and readEnrichment has been run. reSample computes a statistic value and a p-value for each chromosomes and for the whole genome.

## S4 method for signature 'Enrichment'
reSample(object, nSample = 100,
         empiricPvalue = TRUE,
         MAFpool = c(0.05, 0.10, 0.2, 0.3, 0.4, 0.5),
         mc.cores = 1, onlyGenome = TRUE)

## S4 method for signature 'Chromosome'
reSample(object, nSample = 100,
         empiricPvalue = TRUE, sigThresh = 0.05,
         MAFpool = c(0.05, 0.10, 0.2, 0.3, 0.4, 0.5),
         mc.cores = 1)

`object`	[Enrichment or Chromosome]: an object to be updated. It is intended, an object returned by the `readEnrichment` function.
`nSample`	[numeric]: the number of resampling done by `reSample` for p-values computation (minimum is 100).
`empiricPvalue`	[logical]: `empiricPvalue=TRUE` (default) compute PValue based on the null distribution (resampling). If `empiricPvalue=TRUE`, the empirical p-values are computed instead.
`sigThresh`	[numeric]: statistical threshold for signal (e.g. `sigThresh = 0.05` for a given GWAS signal) used to compute an Enrichment Ratio.
`MAFpool`	[vector(numeric)]: either a numeric vector giving the breaks points of intervals into which SNP's MAF (Minor Allele Frequency) is to be split.
`mc.cores`	[numeric]: the number of cores to use (default is `mc.cores=1`), i.e. at most how many child processes will be run simultaneously. Must be at least one, and parallelization requires at least two cores.
`onlyGenome`	[logical]: `onlyGenome=TRUE` (default) compute resampling step for all chromosomes.

Return the object given in argument, updated by the resampling results.

Mickael Canouil mickael.canouil@good.ibl.fr

Overview : snpEnrichment-package
Classes : Enrichment, Chromosome, EnrichSNP
Methods : plot, reSample, getEnrichSNP, excludeSNP, compareEnrichment,
enrichment, is.enrichment, chromosome, is.chromosome
Functions : initFiles, writeLD, readEnrichment

## Not run: data(toyEnrichment)
reSample(object = toyEnrichment,
         nSample = 10,
         empiricPvalue = TRUE,
         MAFpool = c(0.05, 0.10, 0.2, 0.3, 0.4, 0.5),
         onlyGenome = TRUE)
toyEnrichment
## End(Not run)