This function selects the most abundant functions across all samples in a SQM object and represents their abundances in a heatmap. Alternatively, a custom set of functions can be represented.
plotFunctions(
SQM,
fun_level = "KEGG",
count = "tpm",
N = 25,
fun = NULL,
samples = NULL,
ignore_unmapped = TRUE,
ignore_unclassified = TRUE,
gradient_col = c("ghostwhite", "dodgerblue4"),
base_size = 11,
metadata_groups = NULL
)a ggplot2 plot object.
A SQM or SQMlite object.
character. Either "KEGG", "COG", "PFAM" or any other custom database used for annotation (default "KEGG").
character. Either "abund" for raw abundances, "percent" for percentages, "bases" for raw base counts, "cpm" for coverages per million reads, "tpm" for TPM normalized values or "copy_number" for copy numbers (default "tpm"). Note that a given count type might not available in this object (e.g. TPM or copy number in SQMlite objects originating from a SQM reads project).
integer Plot the N most abundant functions (default 25).
character. Custom functions to plot. If provided, it will override N (default NULL).
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 TRUE).
logical. Don't include unclassified ORFs in the plot (default TRUE).
A vector of two colors representing the low and high ends of the color gradient (default c("ghostwhite", "dodgerblue4")).
numeric. Base font size (default 11).
list. Split the plot into groups defined by the user: list('G1' = c('sample1', sample2'), 'G2' = c('sample3', 'sample4')) default NULL).
plotTaxonomy for plotting the most abundant taxa of a SQM object; plotBars and plotHeatmap for plotting barplots or heatmaps with arbitrary data.
data(Hadza)
plotFunctions(Hadza)
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