Plot the Base Qualities for each file

Plot the Base Qualities for each file as separate plots

plotBaseQuals(x, usePlotly = FALSE, labels, pattern = ".(fast|fq|bam).*", ...)

# S4 method for class 'ANY'
plotBaseQuals(x, usePlotly = FALSE, labels, pattern = ".(fast|fq|bam).*", ...)

# S4 method for class 'FastqcData'
plotBaseQuals(
  x,
  usePlotly = FALSE,
  labels,
  pattern = ".(fast|fq|bam).*",
  pwfCols,
  warn = 25,
  fail = 20,
  boxWidth = 0.8,
  showPwf = TRUE,
  plotlyLegend = FALSE,
  ...
)

# S4 method for class 'FastqcDataList'
plotBaseQuals(
  x,
  usePlotly = FALSE,
  labels,
  pattern = ".(fast|fq|bam).*",
  pwfCols,
  warn = 25,
  fail = 20,
  showPwf = TRUE,
  boxWidth = 0.8,
  plotType = c("heatmap", "boxplot"),
  plotValue = "Mean",
  cluster = FALSE,
  dendrogram = FALSE,
  nc = 2,
  heat_w = 8L,
  ...
)

# S4 method for class 'FastpData'
plotBaseQuals(
  x,
  usePlotly = FALSE,
  labels,
  pattern = ".(fast|fq|bam).*",
  pwfCols,
  warn = 25,
  fail = 20,
  showPwf = FALSE,
  module = c("Before_filtering", "After_filtering"),
  reads = c("read1", "read2"),
  readsBy = c("facet", "linetype"),
  bases = c("A", "T", "C", "G", "mean"),
  scaleColour = NULL,
  plotTheme = theme_get(),
  plotlyLegend = FALSE,
  ...
)

# S4 method for class 'FastpDataList'
plotBaseQuals(
  x,
  usePlotly = FALSE,
  labels,
  pattern = ".(fast|fq|bam).*",
  pwfCols,
  warn = 25,
  fail = 20,
  showPwf = FALSE,
  module = c("Before_filtering", "After_filtering"),
  plotType = "heatmap",
  plotValue = c("mean", "A", "T", "C", "G"),
  scaleFill = NULL,
  plotTheme = theme_get(),
  cluster = FALSE,
  dendrogram = FALSE,
  heat_w = 8L,
  ...
)

Arguments

x

Can be a FastqcData, FastqcDataList or character vector of 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.

pattern

Regex to remove from the end of the Fastp report and Fastq file names

...

Used to pass additional attributes to theme() and between methods

pwfCols

Object of class PwfCols() to give colours for pass, warning, and fail values in plot

warn, fail

The default values for warn and fail are 30 and 20 respectively (i.e. percentages)

boxWidth

set the width of boxes when using a boxplot

showPwf

Include the Pwf status colours

plotlyLegend

logical(1) Show legend for interactive plots. Only called when drawing line plots

plotType

character Can be either "boxplot" or "heatmap"

plotValue

character Type of data to be presented. Can be any of the columns returned by the appropriate call to getModule()

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.

nc

numeric. The number of columns to create in the plot layout. Only used if drawing boxplots for multiple files in a FastqcDataList

heat_w

Relative width of any heatmap plot components

module

Select Before and After filtering when using a FastpDataList

reads

Create plots for read1, read2 or all when using a FastpDataList

readsBy

If paired reads are present, separate using either linetype or by facet

bases

Which bases to include on the plot

scaleColour

ggplot discrete colour scale, passed to lines

plotTheme

theme object

scaleFill

ggplot2 continuous scale. Passed to heatmap cells

Value

A standard ggplot2 object or an interactive plotly object

Details

When acting on a FastqcDataList, this defaults to a heatmap using the mean Per_base_sequence_quality score. A set of plots which replicate those obtained through a standard FastQC html report can be obtained by setting plotType = "boxplot", which uses facet_wrap to provide the layout as a single ggplot object.

When acting an a FastqcData object, this replicates the Per base sequence quality plots from FastQC with no faceting.

For large datasets, subsetting by R1 or R2 reads may be helpful.

An interactive plot can be obtained by setting 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)

# The default plot for multiple libraries is a heatmap
plotBaseQuals(fdl)


# The default plot for a single library is the standard boxplot
plotBaseQuals(fdl[[1]])


# FastpData objects have qyalities by base
fp <-  FastpData(system.file("extdata/fastp.json.gz", package = "ngsReports"))
plotBaseQuals(
  fp, plotTheme = theme(plot.title = element_text(hjust = 0.5))
)