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Plot the variance vs mean of feature expression

Source: R/preprocess.R
plotVarFeatures.Rd

For each dataset where the feature variablitity is calculated, a plot of log10 feature expression variance and log10 mean will be produced. Features that are considered as variable would be highlighted in red.

Usage

plotVarFeatures(object, combinePlot = TRUE, dotSize = 1, ...)

Arguments

object

liger object. selectGenes needs to be run in advance.

combinePlot

Logical. If TRUE, sub-figures for all datasets will be combined into one plot. if FALSE, a list of plots will be returned. Default TRUE.

dotSize

Controls the size of dots in the main plot. Default 0.8.

...

More theme setting parameters passed to .ggplotLigerTheme.

Value

ggplot object when combinePlot = TRUE, a list of ggplot objects when combinePlot = FALSE

Examples

pbmc <- normalize(pbmc)
#> ℹ Normalizing datasets "ctrl"
#> ℹ Normalizing datasets "stim"
#> ✔ Normalizing datasets "stim" ... done
#> 
#> ℹ Normalizing datasets "ctrl"

#> ✔ Normalizing datasets "ctrl" ... done
#> 
pbmc <- selectGenes(pbmc)
#> ℹ Selecting variable features for dataset "ctrl"
#> ✔ ... 168 features selected out of 249 shared features.
#> ℹ Selecting variable features for dataset "stim"
#> ✔ ... 166 features selected out of 249 shared features.
#> ✔ Finally 173 shared variable features are selected.
plotVarFeatures(pbmc)