Plot row-wise statistics

Scatter plot to compare between the row-wise mean, median, variance or range from a data frame or matrix. Also supports transformations of those variables, such as log10(mean). If y = NULL, a density plot is rendered instead.

Usage

plotRowStats(
  data,
  x,
  y = NULL,
  subset = NULL,
  xmin = NULL,
  xmax = NULL,
  ymin = NULL,
  ymax = NULL,
  xlim = NULL,
  ylim = NULL,
  cache = NULL,
  verbose = FALSE,
  data2 = NULL,
  legend = FALSE,
  legendLabels = c("Original", "Highlighted")
)

Arguments

data

Data frame or matrix containing samples per column and, for instance, gene or alternative splicing event per row

x, y

Character: statistic to calculate and display in the plot per row; choose between mean, median, var or range (or transformations of those variables, e.g. log10(var)); if y = NULL, the density of x will be plot instead

subset

Boolean or integer: data points to highlight

xmin, xmax, ymin, ymax

Numeric: minimum and maximum X and Y values to draw in the plot

xlim, ylim

Numeric: X and Y axis range

cache

List of summary statistics for data previously calculated to avoid repeating calculations (output also returns cache in attribute named cache with appropriate data)

verbose

Boolean: print messages of the steps performed

data2

Same as data argument but points in data2 are highlighted (unless data2 = NULL)

legend

Boolean: show legend?

legendLabels

Character: legend labels

Value

Plot of data

See also

Other functions for gene expression pre-processing: convertGeneIdentifiers(), filterGeneExpr(), normaliseGeneExpression(), plotGeneExprPerSample(), plotLibrarySize()

Other functions for PSI quantification: filterPSI(), getSplicingEventTypes(), listSplicingAnnotations(), loadAnnotation(), quantifySplicing()

Examples

library(ggplot2)

# Plotting gene expression data
geneExpr <- readFile("ex_gene_expression.RDS")
plotRowStats(geneExpr, "mean", "var^(1/4)") +
    ggtitle("Mean-variance plot") +
    labs(y="Square Root of the Standard Deviation")
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's fill values.


# Plotting alternative splicing quantification
annot <- readFile("ex_splicing_annotation.RDS")
junctionQuant <- readFile("ex_junctionQuant.RDS")
psi <- quantifySplicing(annot, junctionQuant, eventType=c("SE", "MXE"))
#> Using 3 of 3 events (100%) whose junctions are present in junction quantification data...
#>   |                                        |   0% 
  |========                                |  20% 
  |================                        |  40% 
  |========================                |  60% 
  |================================        |  80% 
  |========================================| 100% 

#> Using 3 of 3 events (100%) whose junctions are present in junction quantification data...
#>   |                                        |   0% 
  |========                                |  20% 
  |================                        |  40% 
  |========================                |  60% 
  |================================        |  80% 
  |========================================| 100% 


medianVar <- plotRowStats(psi, x="median", y="var", xlim=c(0, 1)) +
    labs(x="Median PSI", y="PSI variance")
medianVar
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's fill values.


rangeVar  <- plotRowStats(psi, x="range", y="log10(var)", xlim=c(0, 1)) +
    labs(x="PSI range", y="log10(PSI variance)")
rangeVar
#> Warning: No shared levels found between `names(values)` of the manual scale and the
#> data's fill values.