This function generates an upset plot showing summaries of phenotype results (assay distributions, phenotype category percentages, and/or predictive value for phenotype) for each combination of markers observed in the data.
Usage
amr_upset(
binary_matrix = NULL,
assay = "mic",
min_set_size = 2,
order = "value",
geno_table,
pheno_table,
antibiotic = NULL,
drug_class_list,
geno_sample_col = NULL,
pheno_sample_col = NULL,
sir_col = NULL,
ecoff_col = "ecoff",
marker_col = "marker",
plot_set_size = FALSE,
plot_category = TRUE,
print_category_counts = FALSE,
print_set_size = FALSE,
boxplot_col = "grey",
SIR_col = c(S = "#3CAEA3", I = "#F6D55C", R = "#ED553B"),
species = NULL,
bp_site = NULL,
guideline = "EUCAST 2025",
bp_S = NULL,
bp_R = NULL,
ecoff_bp = NULL
)Arguments
- binary_matrix
A data frame containing the original binary matrix output from the
get_binary_matrix()function. If not provided (or set toNULL), user must specifygeno_table,pheno_table,antibiotic,drug_class_listand optionallygeno_sample_col,pheno_sample_col,sir_col,ecoff_col,marker_colto pass toget_binary_matrix().- assay
A character string indicating whether to plot MIC or disk diffusion data. Must be one of:
"mic": plot MIC data stored in columnmic"disk": plot disk diffusion data stored in columndisk
- min_set_size
An integer specifying the minimum size for a gene set to be included in the analysis and plots. Default is 2. Only marker combinations with at least this number of occurrences are included in the plots.
- order
A character string indicating the order of the combinations on the x-axis. Options are:
"": decreasing frequency of combinations"genes": order by the number of genes in each combination"value" (default): order by the median assay value (MIC or disk zone) for each combination"ppv": order by the PPV estimated for each combination
- geno_table
(Required if
binary_matrixnot provided) A data frame containing genotype data, formatted withimport_amrfp(). Only used ifbinary_matrixnot provided.- pheno_table
(Required if
binary_matrixnot provided) A data frame containing phenotype data, formatted withimport_ast(). Only used ifbinary_matrixnot provided.- antibiotic
Optional. Antibiotic name used to retrieve clinical breakpoints for annotation of the assay distribution plot.
- drug_class_list
(Required if
binary_matrixnot provided) A character vector of drug classes to filter genotype data for markers related to the specified antibiotic. Markers ingeno_tablewill be filtered based on whether theirdrug_classmatches any value in this list. Only used ifbinary_matrixnot provided.- geno_sample_col
A character string (optional) specifying the column name in
geno_tablecontaining sample identifiers. Defaults toNULL, in which case it is assumed the first column contains identifiers. Only used ifbinary_matrixnot provided.- pheno_sample_col
A character string (optional) specifying the column name in
pheno_tablecontaining sample identifiers. Defaults toNULL, in which case it is assumed the first column contains identifiers. Only used ifbinary_matrixnot provided.- sir_col
A character string specifying the column name in
pheno_tablethat contains the resistance interpretation (SIR) data. The values should be"S","I","R"or otherwise interpretable byAMR::as.sir(). If not provided, the first column prefixed with "phenotype*" will be used if present, otherwise an error is thrown. Only used ifbinary_matrixnot provided.- ecoff_col
A character string specifying the column name in
pheno_tablethat contains resistance interpretations (SIR) made against the ECOFF rather than a clinical breakpoint. The values should be"S","I","R"or otherwise interpretable byAMR::as.sir(). Defaultecoff. Set toNULLif not available. Only used ifbinary_matrixnot provided.- marker_col
A character string specifying the column name in
geno_tablecontaining the marker identifiers. Default"marker". Only used ifbinary_matrixnot provided.- plot_set_size
Logical indicating whether to include a bar plot showing the set size (i.e., number of times each combination of markers is observed). Default is
FALSE.- plot_category
Logical indicating whether to include a stacked bar plot showing, for each marker combination, the proportion of samples with each phenotype classification (specified by the
phenocolumn in the input file). Default isTRUE.- print_category_counts
Logical indicating whether, if
plot_category=TRUE, to print the number of strains in each resistance category for each marker combination in the plot. Default isFALSE.- print_set_size
Logical indicating whether, if
plot_set_size=TRUE, to print the number of strains with each marker combination on the plot. Default isFALSE.- boxplot_col
Colour for lines of the box plots summarising the MIC distribution for each marker combination. Default is
"grey".- SIR_col
A named vector of colours for the percentage bar plot. The names should be the phenotype categories (e.g.,
"R","I","S"), and the values should be valid color names or hexadecimal color codes. Default values are those used in the AMR packageAMR::scale_colour_sir().- species
Optional. Species name used for breakpoint lookup.
- bp_site
Optional. Breakpoint site (e.g. "Non-meningitis") used when retrieving clinical breakpoints.
- guideline
Guideline used for breakpoint lookup. Default is
"EUCAST 2025".- bp_S
(optional) S breakpoint to add to plot (numerical).
- bp_R
(optional) R breakpoint to add to plot (numerical).
- ecoff_bp
(optional) ECOFF breakpoint to add to plot (numerical).
Value
A list containing the following elements:
plot: A grid of plots displaying: (i) grid showing the marker combinations observed, MIC distribution per marker combination, frequency per marker and (optionally) phenotype classification and/or number of samples for each marker combination.binary_matrix: A copy of the genotype-phenotype binary matrix (either provided as input or generated by the function)summary: A data frame summarizing each marker combination observed, including median MIC (and interquartile range), number of resistant isolates, and positive predictive value for resistance.
Examples
if (FALSE) { # \dontrun{
ecoli_geno <- import_amrfp(ecoli_geno_raw, "Name")
# Generate binary matrix
binary_matrix <- get_binary_matrix(
geno_table = ecoli_geno,
pheno_table = ecoli_ast,
antibiotic = "Ciprofloxacin",
drug_class_list = c("Quinolones"),
sir_col = "pheno_clsi",
keep_assay_values = TRUE,
keep_assay_values_from = "mic"
)
# Run upset plot analysis using this binary_matrix
amr_upset(binary_matrix, assay = "mic")
# Alternatively, generate binary matrix and run ppv() in one step
amr_upset(
assay = "mic",
geno_table = ecoli_geno,
pheno_table = ecoli_ast,
antibiotic = "Ciprofloxacin",
drug_class_list = c("Quinolones"),
sir_col = "pheno_clsi"
)
} # }
