ct.normalizeSpline {gCrisprTools} | R Documentation |
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.
ct.normalizeSpline(eset, annotation, geneSymb = NULL, lib.size = NULL)
eset |
An ExpressionSet object containing, at minimum, count data accessible by |
annotation |
An annotation dataframe indicating the nontargeting controls in the geneID column. |
geneSymb |
The |
lib.size |
An optional vector of voom-appropriate library size adjustment factors, usually calculated with |
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)