Create Batches of Null Permutations for a Crispr Screen

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Description

This is a wrapper function to partition batches of calls to ct.RRAalpha() for multicore processing. It is called internally as a single instance of the beta aggregation step in RRAa. Users should not interact with it directly.

Usage

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ct.RRAalphaBatch(p, g.key, alpha, result.environment, batch.size = 100,
  permutation.seed = NULL)

Arguments

p

A single column matrix of rank statistics, with row.names indicating the gRNA labels.

g.key

data.frame with guide and gene names

alpha

The alpha cutoff parameter, corresponding to the P-value threshold or fold change proportion at which gRNAs should no longer be considered to be differentially expressed. Alternatively, this can be provided as a logical vector of the same length as the number of rows in p, containing only TRUE and FALSE elements indicating whether the element should be included during the aggeregation step.

result.environment

The target environment containing the quasi-global variables incremented during the permutations in the child functions.

batch.size

Number of iterations to deploy to each daughter process.

permutation.seed

numeric seed for permutation reproducibility. Default is NULL, in which case no seed is set.

Value

An integer vector indicating the number of iterations in which each gene's score was better than those indicated in result.environment$obs.

Author(s)

Russell Bainer

Examples

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data('fit')
data('ann')
batch.size <- 50
env <- new.env()
env$obs <- ct.RRAalpha(fit$p.value, ann, alpha = 0.1, return.obj = 'none')
env$ngenes <- length(levels(ann$geneSymbol))
passed <- ct.RRAalphaBatch(fit$p.value, ann, alpha = 0.1, result.environment = env, batch.size = batch.size)
hist(passed/batch.size, main = 'Empirical P-value', xlab = 'P')

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