Concordance plots of filtered single vs n-cell assays

Source: R/filterEval.R

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, ...)

Arguments

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 getConcordance

Value

printed plot

See also

getConcordance

Examples

data(vbetaFA)
sca1 <- subset(vbetaFA, ncells==1)
sca100 <- subset(vbetaFA, ncells==100)
plotSCAConcordance(sca1, sca100)
#> Using primerid as id variables
#> Using primerid as id variables
#> Using primerid as id variables
#> Using primerid as id variables
#> Sum of Squares before Filtering: 14.89
#>  After filtering: 14.01
#>  Difference: 0.87