Description Usage Arguments Value Author(s) Examples
View source: R/StackedGuides.R
This function identifies the gRNAs or targets that change the most from sample to sample within an experiment as a percentage of
the entire library. It then plots the abundance of the top nguides
as a stacked barplot for all samples in the experiment. The purpose of this
algorithm is to detect potential distortions in the library composition that might not be properly controlled by sample normalization, and so
the most variable entites are defined by calculating the percent of aligned reads that they contribute to each sample, and then ranking each entity
by the range of these percentages across all samples. Consequently, gRNAs or Targets that are highly abundant in at least one condition will be
are more likely to be identified.
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eset |
An ExpressionSet object containing, at minimum, a matrix of gRNA abundances extractable with the exprs() function, and a metadata
object containing a column named |
sampleKey |
An optional sample key, supplied as an ordered factor linking the samples to experimental
variables. The |
nguides |
The number of guides (or targets) to display. |
plotType |
A string indicating whether the individual guides should be displayed (" |
annotation |
An optional data.frame containing an annotation object to be used to aggregate the guides into targets. gRNAs are annotated by row,
and must minimally contain a column |
ylimit |
An optional numeric vector of length 2 specifying the y limits for the plot, useful in comparin across studies. |
subset |
An optional character vector containing the sample labels to be used in the analysis; all elements must be contained in the |
A stacked barplot displaying the appropriate entities on the default device.
Russell Bainer
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