Plot the average expression value of two subsets of the data.
Generally these might be 1 cell and multiple-cell replicates,
in which case if the mcols
column ncells
is
set then the averages will be adjusted accordingly.
But it could be any grouping.
plotSCAConcordance(SCellAssay, NCellAssay, filterCriteria = list(nOutlier = 2, sigmaContinuous = 9, sigmaProportion = 9), groups = NULL, ...)
SCellAssay | is a FluidigmAssay for the 1-cell per well assay |
---|---|
NCellAssay | is a FluidigmAssay for the n-cell per well assay |
filterCriteria | is a list of filtering criteria to apply to the SCellAssay and NCellAssay |
groups | is a character vector naming the group within which to perform filtering. NULL by default. |
... | passed to |
printed plot
getConcordance
data(vbetaFA) sca1 <- subset(vbetaFA, ncells==1) sca100 <- subset(vbetaFA, ncells==100) plotSCAConcordance(sca1, sca100)#>#>#>#>#>#> #>