ct.viewControls: View nontargeting guides within an experiment

Description Usage Arguments Value Author(s) Examples

View source: R/ViewControls.R

Description

This function tries to identify, and then plot the abundance of, the full set of non-targeting controls from an ExpressionSet object. Ideally, the user will supply a geneSymbol present in the appropriate annotation file that uniquely identifies the nontargeting gRNAs. Absent this, the the function will search for common identifier used by nontargeting controls (geneID "no_gid", or geneSymbol NA).

Usage

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ct.viewControls(eset, annotation, sampleKey, geneSymb = NULL,
  normalize = TRUE, lib.size = NULL)

Arguments

eset

An ExpressionSet object containing, at minimum, a matrix of gRNA abundances extractable with the exprs function.

annotation

An annotation data.frame for the experiment. gRNAs are annotated by row, and must minimally contain columns geneSymbol and geneID.

sampleKey

A sample key, supplied as an ordered factor linking the samples to experimental variables. The names attribute should exactly match those present in eset, and the control condition is assumed to be the first level.

geneSymb

The geneSymbol identifier in annotation that corresponds to nontargeting gRNAs. If absent, ct.ViewControls will attempt to infer nontargeting guides by searching for "no_gid" or NA in the appropriate columns.

normalize

Logical indicating whether to attempt to normalize the data in the eset by DESeq size factors present in the metadata. If TRUE, then the metadata must contain a column containing these factors, named sizeFactor.crispr-gRNA.

lib.size

An optional vector of voom-appropriate library size adjustment factors, usually calculated with calcNormFactors and transformed to reflect the appropriate library size. These adjustment factors are interpreted as the total library sizes for each sample, and if absent will be extrapolated from the columnwise count sums of the exprs slot of the eset.

Value

An image of nontargeting control gRNA abundances on the default device.

Author(s)

Russell Bainer

Examples

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data('es')
data('ann')

#Build the sample key
library(Biobase)
sk <- ordered(relevel(as.factor(pData(es)$TREATMENT_NAME), "ControlReference"))
names(sk) <- row.names(pData(es))

ct.viewControls(es, ann, sk, geneSymb = NULL, normalize = FALSE)
ct.viewControls(es, ann, sk, geneSymb = NULL, normalize = TRUE)

gCrisprTools documentation built on Nov. 17, 2017, 1:37 p.m.