plotSummary-methods: Plot the PASS/WARN/FAIL information

plotSummaryR 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)


UofABioinformaticsHub/fastqcReports documentation built on Feb. 21, 2024, 9:28 a.m.