plotRowStats {psichomics} | R Documentation

## Plot row-wise statistics

### Description

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")

    # Plotting alternative splicing quantification
    annot <- readFile("ex_splicing_annotation.RDS")
    junctionQuant <- readFile("ex_junctionQuant.RDS")
    psi <- quantifySplicing(annot, junctionQuant, eventType=c("SE", "MXE"))

    medianVar <- plotRowStats(psi, x="median", y="var", xlim=c(0, 1)) +
        labs(x="Median PSI", y="PSI variance")
    medianVar

    rangeVar  <- plotRowStats(psi, x="range", y="log10(var)", xlim=c(0, 1)) +
        labs(x="PSI range", y="log10(PSI variance)")
    rangeVar

[Package psichomics version 1.16.0 Index]