This function selects the most abundant bins across all samples in a SQM object and represents their abundances in a barplot. Alternatively, a custom set of bins can be represented.
plotBins(
SQM,
count = "percent",
N = 15,
bins = NULL,
others = TRUE,
samples = NULL,
ignore_unmapped = FALSE,
ignore_nobin = FALSE,
rescale = FALSE,
color = NULL,
base_size = 11,
max_scale_value = NULL,
metadata_groups = NULL
)a ggplot2 plot object.
A SQM or a SQMlite object.
character. Either "abund" for raw abundances, "percent" for percentages, "cov" for coverages, or "cpm" for coverages per million reads (default "percent").
integer Plot the N most abundant bins (default 15).
character. Custom bins to plot. If provided, it will override N (default NULL).
logical. Collapse the abundances of least abundant bins, and include the result in the plot (default TRUE).
character. Character vector with the names of the samples to include in the plot. Can also be used to plot the samples in a custom order. If not provided, all samples will be plotted (default NULL).
logical. Don't include unmapped reads in the plot (default FALSE).
logical. Don't include reads which are not in a bin in the plot (default FALSE).
logical. Re-scale results to percentages (default FALSE).
Vector with custom colors for the different features. If empty, we will use our own hand-picked pallete if N<=15, and the default ggplot2 palette otherwise (default NULL).
numeric. Base font size (default 11).
numeric. Maximum value to include in the y axis. By default it is handled automatically by ggplot2 (default NULL).
list. Split the plot into groups defined by the user: list('G1' = c('sample1', sample2'), 'G2' = c('sample3', 'sample4')) default NULL).
plotBins for plotting the most abundant bins of a SQM object; plotBars and plotHeatmap for plotting barplots or heatmaps with arbitrary data.
data(Hadza)
# Bins distribution.
plotBins(Hadza)
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