plotOverrep-methods: Plot a summary of Over-represented Sequences
In ngsReports: Load FastqQC reports and other NGS related files

Description Usage Arguments Details Value Examples

Plot a summary of Over-represented Sequences for a set of FASTQC reports

plotOverrep(x, usePlotly = FALSE, labels, pwfCols, ...)

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

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

## S4 method for signature 'FastqcData'
plotOverrep(
  x,
  usePlotly = FALSE,
  labels,
  pwfCols,
  n = 10,
  ...,
  expand.x = expansion(mult = c(0, 0.05)),
  expand.y = expansion(0, 0.6)
)

## S4 method for signature 'FastqcDataList'
plotOverrep(
  x,
  usePlotly = FALSE,
  labels,
  pwfCols,
  cluster = FALSE,
  dendrogram = FALSE,
  ...,
  paletteName = "Set1",
  expand.x = expansion(mult = c(0, 0.05)),
  expand.y = expansion(0, 0)
)

`x`	Can be a `FastqcData`, `FastqcDataList` or file paths
`usePlotly`	`logical` Default `FALSE` will render using ggplot. If `TRUE` plot will be rendered with plotly
`labels`	An optional named factor 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
`...`	Used to pass additional attributes to theme() and between methods
`n`	The number of sequences to plot from an individual file
`expand.x, expand.y`	Output from `expansion()` or numeric vectors of length 4. Passed to `scale_*_continuous()`
`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.
`paletteName`	Name of the palette for colouring the possible sources of the overrepresented sequences. Must be a palette name from `RColorBrewer`

Percentages are obtained by simply summing those within a report. Any possible double counting by FastQC is ignored for the purposes of a simple approximation.

Plots generated from a FastqcData object will show the top n sequences grouped by their predicted source & coloured by whether the individual sequence would cause a WARN/FAIL.

Plots generated from a FastqcDataList group sequences by predicted source and summarise as a percentage of the total reads.

A standard ggplot2 object

# 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)

# Another example which isn't ideal
plotOverrep(fdl)