plotSummary {ngsReports} | R Documentation

## Plot the PASS/WARN/FAIL information

### Description

Extract the PASS/WARN/FAIL summaries and plot them

### Usage

    plotSummary(x, usePlotly = FALSE, labels, pwfCols, cluster = FALSE,
      dendrogram = FALSE, ...)

    ## S4 method for signature 'ANY'
    plotSummary(x, usePlotly = FALSE, labels, pwfCols,
      cluster = FALSE, dendrogram = FALSE, ...)

    ## S4 method for signature 'character'
    plotSummary(x, usePlotly = FALSE, labels, pwfCols,
      cluster = FALSE, dendrogram = FALSE, ...)

    ## S4 method for signature 'FastqcDataList'
    plotSummary(x, usePlotly = FALSE, labels,
      pwfCols, cluster = FALSE, dendrogram = FALSE, ...,
      gridlineWidth = 0.2, gridlineCol = "grey20")

### Arguments

`x` | Can be a `FastqcData`, `FastqcDataList` or character vector of file paths
`usePlotly` | `logical`. Generate an interactive plot using plotly
`labels` | An optional named vector of labels for the file names. All filenames must be present in the names. File extensions are dropped by default.
`pwfCols` | Object of class `PwfCols` containing the colours for PASS/WARN/FAIL
`cluster` | `logical` default `FALSE`. If set to `TRUE`, fastqc data will be clustered using hierarchical clustering
`dendrogram` | `logical` redundant if `cluster` is `FALSE` if both `cluster` and `dendrogram` are specified as `TRUE` then the dendrogram will be displayed.
`...` | Used to pass various potting parameters to theme.
`gridlineWidth, gridlineCol` | Passed to geom_hline and geom_vline to determine width and colour of gridlines

### Details

This uses the standard ggplot2 syntax to create a three colour plot. The output of this function can be further modified using the standard ggplot2 methods if required.

### Value

A ggplot2 object (`usePlotly = FALSE`) or an interactive plotly object (`usePlotly = TRUE`)

### Examples

    # Get the files included with the package
    packageDir <- system.file("extdata", package = "ngsReports")
    fl <- list.files(packageDir, pattern = "fastqc.zip", full.names = TRUE)

    # Load the FASTQC data as a FastqcDataList object
    fdl <- FastqcDataList(fl)

    # Check the overall PASS/WARN/FAIL status
    plotSummary(fdl)

[Package ngsReports version 1.2.0 Index]