Skip to contents

Plotting Helpers for AMR Data Analysis

Source: R/plotting.R
plot.Rd

Functions to plot classes sir, mic and disk, with support for base R and ggplot2.

Especially the scale_*_mic() functions are relevant wrappers to plot MIC values for ggplot2. They allows custom MIC ranges and to plot intermediate log2 levels for missing MIC values.

Usage

scale_x_mic(keep_operators = "edges", mic_range = NULL, drop = FALSE, ...)

scale_y_mic(keep_operators = "edges", mic_range = NULL, drop = FALSE, ...)

scale_colour_mic(keep_operators = "edges", mic_range = NULL, drop = FALSE, ...)

scale_fill_mic(keep_operators = "edges", mic_range = NULL, drop = FALSE, ...)

# S3 method for class 'mic'
plot(
  x,
  mo = NULL,
  ab = NULL,
  guideline = "EUCAST",
  main = deparse(substitute(x)),
  ylab = translate_AMR("Frequency", language = language),
  xlab = translate_AMR("Minimum Inhibitory Concentration (mg/L)", language = language),
  colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
  language = get_AMR_locale(),
  expand = TRUE,
  include_PKPD = getOption("AMR_include_PKPD", TRUE),
  breakpoint_type = getOption("AMR_breakpoint_type", "human"),
  ...
)

# S3 method for class 'mic'
autoplot(
  object,
  mo = NULL,
  ab = NULL,
  guideline = "EUCAST",
  title = deparse(substitute(object)),
  ylab = translate_AMR("Frequency", language = language),
  xlab = translate_AMR("Minimum Inhibitory Concentration (mg/L)", language = language),
  colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
  language = get_AMR_locale(),
  expand = TRUE,
  include_PKPD = getOption("AMR_include_PKPD", TRUE),
  breakpoint_type = getOption("AMR_breakpoint_type", "human"),
  ...
)

# S3 method for class 'mic'
fortify(object, ...)

# S3 method for class 'disk'
plot(
  x,
  main = deparse(substitute(x)),
  ylab = translate_AMR("Frequency", language = language),
  xlab = translate_AMR("Disk diffusion diameter (mm)", language = language),
  mo = NULL,
  ab = NULL,
  guideline = "EUCAST",
  colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
  language = get_AMR_locale(),
  expand = TRUE,
  include_PKPD = getOption("AMR_include_PKPD", TRUE),
  breakpoint_type = getOption("AMR_breakpoint_type", "human"),
  ...
)

# S3 method for class 'disk'
autoplot(
  object,
  mo = NULL,
  ab = NULL,
  title = deparse(substitute(object)),
  ylab = translate_AMR("Frequency", language = language),
  xlab = translate_AMR("Disk diffusion diameter (mm)", language = language),
  guideline = "EUCAST",
  colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
  language = get_AMR_locale(),
  expand = TRUE,
  include_PKPD = getOption("AMR_include_PKPD", TRUE),
  breakpoint_type = getOption("AMR_breakpoint_type", "human"),
  ...
)

# S3 method for class 'disk'
fortify(object, ...)

# S3 method for class 'sir'
plot(
  x,
  ylab = translate_AMR("Percentage", language = language),
  xlab = translate_AMR("Antimicrobial Interpretation", language = language),
  main = deparse(substitute(x)),
  language = get_AMR_locale(),
  ...
)

# S3 method for class 'sir'
autoplot(
  object,
  title = deparse(substitute(object)),
  xlab = translate_AMR("Antimicrobial Interpretation", language = language),
  ylab = translate_AMR("Frequency", language = language),
  colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B"),
  language = get_AMR_locale(),
  ...
)

# S3 method for class 'sir'
fortify(object, ...)

facet_sir(facet = c("interpretation", "antibiotic"), nrow = NULL)

scale_y_percent(
  breaks = function(x) seq(0, max(x, na.rm = TRUE), 0.1),
  limits = c(0, NA)
)

scale_sir_colours(
  ...,
  aesthetics = "fill",
  colours_SIR = c("#3CAEA3", "#F6D55C", "#ED553B")
)

theme_sir()

labels_sir_count(
  position = NULL,
  x = "antibiotic",
  translate_ab = "name",
  minimum = 30,
  language = get_AMR_locale(),
  combine_SI = TRUE,
  datalabels.size = 3,
  datalabels.colour = "grey15"
)

Arguments

keep_operators

a character specifying how to handle operators (such as > and <=) in the input. Accepts one of three values: "all" (or TRUE) to keep all operators, "none" (or FALSE) to remove all operators, or "edges" to keep operators only at both ends of the range.

mic_range

a manual range to limit the MIC values, e.g., mic_range = c(0.001, 32). Use NA to set no limit on one side, e.g., mic_range = c(NA, 32).

drop

a logical to remove intermediate MIC values, defaults to FALSE

...

arguments passed on to methods

x, object

values created with as.mic(), as.disk() or as.sir() (or their random_* variants, such as random_mic())

mo

any (vector of) text that can be coerced to a valid microorganism code with as.mo()

ab

any (vector of) text that can be coerced to a valid antimicrobial drug code with as.ab()

guideline

interpretation guideline to use - the default is the latest included EUCAST guideline, see Details

main, title

title of the plot

xlab, ylab

axis title

colours_SIR

colours to use for filling in the bars, must be a vector of three values (in the order S, I and R). The default colours are colour-blind friendly.

language

language to be used to translate 'Susceptible', 'Increased exposure'/'Intermediate' and 'Resistant' - the default is system language (see get_AMR_locale()) and can be overwritten by setting the package option AMR_locale, e.g. options(AMR_locale = "de"), see translate. Use language = NULL or language = "" to prevent translation.

expand

a logical to indicate whether the range on the x axis should be expanded between the lowest and highest value. For MIC values, intermediate values will be factors of 2 starting from the highest MIC value. For disk diameters, the whole diameter range will be filled.

include_PKPD

a logical to indicate that PK/PD clinical breakpoints must be applied as a last resort - the default is TRUE. Can also be set with the package option AMR_include_PKPD.

breakpoint_type

the type of breakpoints to use, either "ECOFF", "animal", or "human". ECOFF stands for Epidemiological Cut-Off values. The default is "human", which can also be set with the package option AMR_breakpoint_type. If host is set to values of veterinary species, this will automatically be set to "animal".

facet

variable to split plots by, either "interpretation" (default) or "antibiotic" or a grouping variable

nrow

(when using facet) number of rows

breaks

a numeric vector of positions

limits

a numeric vector of length two providing limits of the scale, use NA to refer to the existing minimum or maximum

aesthetics

aesthetics to apply the colours to - the default is "fill" but can also be (a combination of) "alpha", "colour", "fill", "linetype", "shape" or "size"

position

position adjustment of bars, either "fill", "stack" or "dodge"

translate_ab

a column name of the antibiotics data set to translate the antibiotic abbreviations to, using ab_property()

minimum

the minimum allowed number of available (tested) isolates. Any isolate count lower than minimum will return NA with a warning. The default number of 30 isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see Source.

combine_SI

a logical to indicate whether all values of S, SDD, and I must be merged into one, so the output only consists of S+SDD+I vs. R (susceptible vs. resistant) - the default is TRUE

datalabels.size

size of the datalabels

datalabels.colour

colour of the datalabels

Value

The autoplot() functions return a ggplot model that is extendible with any ggplot2 function.

The fortify() functions return a data.frame as an extension for usage in the ggplot2::ggplot() function.

Details

The interpretation of "I" will be named "Increased exposure" for all EUCAST guidelines since 2019, and will be named "Intermediate" in all other cases.

For interpreting MIC values as well as disk diffusion diameters, supported guidelines to be used as input for the guideline argument are: "EUCAST 2024", "EUCAST 2023", "EUCAST 2022", "EUCAST 2021", "EUCAST 2020", "EUCAST 2019", "EUCAST 2018", "EUCAST 2017", "EUCAST 2016", "EUCAST 2015", "EUCAST 2014", "EUCAST 2013", "EUCAST 2012", "EUCAST 2011", "CLSI 2024", "CLSI 2023", "CLSI 2022", "CLSI 2021", "CLSI 2020", "CLSI 2019", "CLSI 2018", "CLSI 2017", "CLSI 2016", "CLSI 2015", "CLSI 2014", "CLSI 2013", "CLSI 2012", and "CLSI 2011".

Simply using "CLSI" or "EUCAST" as input will automatically select the latest version of that guideline.

Additional ggplot2 Functions

This package contains several functions that extend the ggplot2 package, to help in visualising AMR data results. All these functions are internally used by ggplot_sir() too.

  • facet_sir() creates 2d plots (at default based on S/I/R) using ggplot2::facet_wrap().

  • scale_y_percent() transforms the y axis to a 0 to 100% range using ggplot2::scale_y_continuous().

  • scale_sir_colours() sets colours to the bars (green for S, yellow for I, and red for R). Has multilingual support. The default colours are colour-blind friendly, while maintaining the convention that e.g. 'susceptible' should be green and 'resistant' should be red.

  • theme_sir() is a [ggplot2 theme][ggplot2::theme() with minimal distraction.

  • labels_sir_count() print datalabels on the bars with percentage and number of isolates, using ggplot2::geom_text().

Examples

some_mic_values <- random_mic(size = 100)
some_disk_values <- random_disk(size = 100, mo = "Escherichia coli", ab = "cipro")
some_sir_values <- random_sir(50, prob_SIR = c(0.55, 0.05, 0.30))

plot(some_mic_values)

plot(some_disk_values)

plot(some_sir_values)


# when providing the microorganism and antibiotic, colours will show interpretations:
plot(some_mic_values, mo = "S. aureus", ab = "ampicillin")

plot(some_disk_values, mo = "Escherichia coli", ab = "cipro")

plot(some_disk_values, mo = "Escherichia coli", ab = "cipro", language = "nl")



# Plotting using scale_x_mic() ---------------------------------------------
# \donttest{
if (require("ggplot2")) {
  mic_plot <- ggplot(data.frame(mics = as.mic(c(0.25, "<=4", 4, 8, 32, ">=32")),
                                counts = c(1, 1, 2, 2, 3, 3)),
                     aes(mics, counts)) +
    geom_col()
  mic_plot +
    labs(title = "without scale_x_mic()")
}

if (require("ggplot2")) {
  mic_plot +
    scale_x_mic() +
    labs(title = "with scale_x_mic()")
}

if (require("ggplot2")) {
  mic_plot +
    scale_x_mic(keep_operators = "all") +
    labs(title = "with scale_x_mic() keeping all operators")
}

if (require("ggplot2")) {
  mic_plot +
    scale_x_mic(mic_range = c(1, 16)) +
    labs(title = "with scale_x_mic() using a manual 'within' range")
}

if (require("ggplot2")) {
  mic_plot +
    scale_x_mic(mic_range = c(0.032, 256)) +
    labs(title = "with scale_x_mic() using a manual 'outside' range")
}


if (require("ggplot2")) {
  autoplot(some_mic_values)
}

if (require("ggplot2")) {
  autoplot(some_disk_values, mo = "Escherichia coli", ab = "cipro")
}

if (require("ggplot2")) {
  autoplot(some_sir_values)
}


# Plotting using scale_y_percent() -----------------------------------------
if (require("ggplot2")) {
  p <- ggplot(data.frame(mics = as.mic(c(0.25, "<=4", 4, 8, 32, ">=32")),
                               counts = c(1, 1, 2, 2, 3, 3)),
                         aes(mics, counts / sum(counts))) +
    geom_col()
  print(p)
  
  p2 <- p +
    scale_y_percent() +
    theme_sir()
  print(p2)
  
  p +
    scale_y_percent(breaks = seq(from = 0, to = 1, by = 0.1),
                    limits = c(0, 1)) +
    theme_sir()
}



# }