ct.normalizeNTC: Normalize sample abundance estimates by the median values of...
In gCrisprTools: Suite of Functions for Pooled Crispr Screen QC and Analysis

Description Usage Arguments Value Author(s) Examples

This function normalizes Crispr gRNA abundance estimates by equalizing the median abundances of the nontargeting gRNAs within each sample. The normalized values are returned as normalized counts in the 'exprs' slot of the input eset. Note that this method may be unstable if the screening library contains relatively few nontargeting gRNAs.

1	ct.normalizeNTC(eset, annotation, lib.size = NULL, geneSymb = NULL)

`eset`	An ExpressionSet object containing, at minimum, count data accessible by `exprs`.
`annotation`	An annotation dataframe indicating the nontargeting controls in the geneID column.
`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`.
`geneSymb`	The `geneSymbol` identifier in `annotation` that corresponds to nontargeting gRNAs. If absent, `ct.gRNARankByReplicate` will attempt to infer nontargeting guides by searching for `"no_gid"` or `NA` in the appropriate columns via `ct.prepareAnnotation()`.

A normalized eset.

Russell Bainer

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

#Build the sample key and library sizes for visualization
library(Biobase)
sk <- ordered(relevel(as.factor(pData(es)$TREATMENT_NAME), "ControlReference"))
names(sk) <- row.names(pData(es))
ls <- colSums(exprs(es))

es.norm <- ct.normalizeNTC(es, ann, lib.size = ls, geneSymb = 'NoTarget')

ct.gRNARankByReplicate(es, sk, lib.size = ls)
ct.gRNARankByReplicate(es.norm, sk, lib.size = ls)