plotKmers-methods: Plot Overrepresented Kmers
In ngsReports: Load FastqQC reports and other NGS related files

Description Usage Arguments Details Value Examples

Plot Overrepresented Kmers

plotKmers(x, usePlotly = FALSE, labels, ...)

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

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

## S4 method for signature 'FastqcData'
plotKmers(
  x,
  usePlotly = FALSE,
  labels,
  n = 6,
  ...,
  lineWidth = 0.5,
  pal = c("red", "blue", "green", "black", "magenta", "yellow")
)

## S4 method for signature 'FastqcDataList'
plotKmers(
  x,
  usePlotly = FALSE,
  labels,
  cluster = FALSE,
  dendrogram = FALSE,
  pwfCols,
  heatCol = inferno(50),
  ...
)

`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 vector of labels for the file names. All filenames must be present in the names. File extensions are dropped by default.
`...`	Used to pass various potting parameters to theme. Can also be used to set size and colour for box outlines.
`n`	`numeric`. The number of Kmers to show.
`lineWidth`	Passed to `geom_line(size = lineWidth)`
`pal`	The colour palette. If the vector supplied is less than n, `grDevices::colorRampPalette()` will be used
`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.
`pwfCols`	Object of class `PwfCols` to give colours for pass, warning, and fail values in the plot
`heatCol`	Colour palette used for the heatmap. Default is `inferno` from the package `viridris`

As the Kmer Content module present in FastQC reports is relatively uninformative, and omitted by default in later versions of FastQC, these are rudimentary plots.

Plots for FastqcData objects replicate those contained in a FastQC report, whilst the heatmap generated from FastqcDataList objects simply show the location and abundance of over-represented Kmers.

A standard ggplot2 object or an interactive plotly 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)
plotKmers(fdl[[1]])