plotFunctions {SQMtools} | R Documentation |
Heatmap of the most abundant functions in a SQM object
Description
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.
Usage
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
)
Arguments
SQM |
A SQM or SQMlite object. |
fun_level |
character. Either |
count |
character. Either |
N |
integer Plot the |
fun |
character. Custom functions to plot. If provided, it will override |
samples |
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 |
ignore_unmapped |
logical. Don't include unmapped reads in the plot (default |
ignore_unclassified |
logical. Don't include unclassified ORFs in the plot (default |
gradient_col |
A vector of two colors representing the low and high ends of the color gradient (default |
base_size |
numeric. Base font size (default |
metadata_groups |
list. Split the plot into groups defined by the user: list('G1' = c('sample1', sample2'), 'G2' = c('sample3', 'sample4')) default |
Value
a ggplot2 plot object.
See Also
plotTaxonomy
for plotting the most abundant taxa of a SQM object; plotBars
and plotHeatmap
for plotting barplots or heatmaps with arbitrary data.
Examples
data(Hadza)
plotFunctions(Hadza)