plotFunctions: Heatmap of the most abundant functions in a SQM object

In SQMtools: Analyze Results Generated by the 'SqueezeMeta' Pipeline

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 = "copy_number",
  N = 25,
  fun = NULL,
  samples = NULL,
  display_function_names = TRUE,
  ignore_unmapped = TRUE,
  ignore_unclassified = TRUE,
  gradient_col = c("ghostwhite", "dodgerblue4"),
  base_size = 11,
  metadata_groups = NULL
)

Arguments

SQM	A SQM, SQMbunch or SQMlite object.
fun_level	character. Either "KEGG", "COG", "PFAM" or any other custom database used for annotation (default "KEGG").
count	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).
N	integer Plot the N most abundant functions (default 25).
fun	character. Custom functions to plot. If provided, it will override N (default NULL).
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 NULL).
display_function_names	logical. Plot function names alongside function IDs, if available (default TRUE).
ignore_unmapped	logical. Don't include unmapped reads in the plot (default TRUE).
ignore_unclassified	logical. Don't include unclassified ORFs in the plot (default TRUE).
gradient_col	A vector of two colors representing the low and high ends of the color gradient (default c("ghostwhite", "dodgerblue4")).
base_size	numeric. Base font size (default 11).
metadata_groups	list. Split the plot into groups defined by the user: list('G1' = c('sample1', sample2'), 'G2' = c('sample3', 'sample4')) default NULL).

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)

SQMtools documentation built on April 3, 2025, 6:16 p.m.