ct.applyAlpha: Apply RRA 'alpha' cutoff to RRAalpha input

In OscarBrock/gCrisprTools: Suite of Functions for Pooled Crispr Screen QC and Analysis

Apply RRA 'alpha' cutoff to RRAalpha input

Description

The 'alpha' part of RRAalpha is used to consider only the top guide-level scores for gene-level statistics. Practically, all guides failing the cutoff get a pvalue of 1. There are three ways of determining which guides fail. See 'scoring' below.

Usage

ct.applyAlpha(
  stats,
  RRAalphaCutoff = 0.1,
  scoring = c("combined", "pvalue", "fc")
)

Arguments

stats	three-column numeric matrix with pvalues for down and up one-sided test with guide-level fold changes (coefficients from the relevant contrast).
RRAalphaCutoff	A cutoff to use when defining gRNAs with significantly altered abundance during the RRAa aggregation step, which may be specified as a single numeric value on the unit interval or as a logical vector. When supplied as a logical vector (of length equal to nrows(fit)), this parameter directly indicates the gRNAs to include during RRAa aggregation. Otherwise, if scoring is set to pvalue or combined, this parameter is interpreted as the maximum nominal p-value required to consider a gRNA's abundance meaningfully altered during the aggregation step. If scoring is fc, this parameter is interpreted as the proportion of the list to be considered meaningfully altered in the experiment (e.g., if RRAalphaCutoff is set to 0.05, only consider the rankings of the 5 (or downregulated) gRNAs for the purposes of RRAa calculations).
scoring	The gRNA ranking method to use in RRAa aggregation. May take one of three values: pvalue, fc, or 'combined'. pvalue indicates that the gRNA ranking statistic should be created from the (one-sided) p-values in the fit object. fc indicates that the ranks of the gRNA coefficients should be used instead, and combined indicates that that the coefficents should be used as the ranking statistic but gRNAs are discarded in the aggregation step based on the corresponding nominal p-value in the fit object.

Value

data.frame with guide-level pvals, fold change, and scores.deplete and scores.enrich which are the input the RRAalpha

Author(s)

Russell Bainer

Examples

fakestats <- matrix(runif(300), ncol = 3)
colnames(fakestats) = c('Depletion.P', 'Enrichment.P', 'lfc')
ct.applyAlpha(fakestats)

OscarBrock/gCrisprTools documentation built on Oct. 25, 2022, 7:29 a.m.