plotKmers {ngsReports} | R Documentation |
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 |
usePlotly |
|
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 |
|
lineWidth |
Passed to |
pal |
The colour palette. If the vector supplied is less than n,
|
cluster |
|
dendrogram |
|
pwfCols |
Object of class |
heatCol |
Colour palette used for the heatmap. Default is |
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]])