ct.normalizeSpline: Normalize sample abundance estimates by a spline fit to the...
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 fiting a smoothed spline to the nontargeting gRNAs within each sample and then equalizing these curves across the experiment. Specifically, the algorithm ranks the gRNA abundance estimates within each sample and uses a smoothed spline to determine a relationship between the ranks of nontargeting guides and their abundance estimates. It then removes the spline trend from each sample, centering each experiment around the global median abundance; these values are returned as normalized counts in the 'exprs' slot of the input eset.

1	ct.normalizeSpline(eset, annotation, geneSymb = NULL, lib.size = 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.
`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.
`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`.

A normalized eset.

Russell Bainer

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

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

es.norm <- ct.normalizeSpline(es, ann, 'NoTarget', lib.size = ls)
ct.gRNARankByReplicate(es, sk, lib.size = ls)
ct.gRNARankByReplicate(es.norm, sk, lib.size = ls)