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Perform Solo PPV Analysis for AMR Markers

Source: R/solo_ppv.R
solo_ppv_analysis.Rd

This function performs a Positive Predictive Value (PPV) analysis for AMR markers associated with a given antibiotic and drug class. It calculates the PPV for solo markers and visualizes the results using various plots.

Usage

solo_ppv_analysis(
  geno_table,
  pheno_table,
  antibiotic = NULL,
  drug_class_list = NULL,
  geno_sample_col = NULL,
  pheno_sample_col = NULL,
  sir_col = NULL,
  ecoff_col = "ecoff",
  icat = FALSE,
  marker_col = "marker",
  binary_matrix = NULL,
  min = 1,
  axis_label_size = 9,
  pd = position_dodge(width = 0.8),
  excludeRanges = NULL,
  colours_SIR = c(S = "#3CAEA3", SDD = "#8FD6C4", I = "#F6D55C", R = "#ED553B"),
  colours_ppv = c(R = "maroon", I = "skyblue", NWT = "navy")
)

Arguments

geno_table

(Required if binary_matrix not provided) A data frame containing genotype data, formatted with import_amrfp(). Only used if binary_matrix not provided.

pheno_table

(Required if binary_matrix not provided) A data frame containing phenotype data, formatted with import_ast(). Only used if binary_matrix not provided.

antibiotic

(Required if binary_matrix not provided) A character string specifying the antibiotic of interest to filter phenotype data. The value must match one of the entries in the drug_agent column of pheno_table. Only used if binary_matrix not provided or if breakpoints required.

drug_class_list

(Required if binary_matrix not provided) A character vector of drug classes to filter genotype data for markers related to the specified antibiotic. Markers in geno_table will be filtered based on whether their drug_class matches any value in this list. Only used if binary_matrix not provided.

geno_sample_col

A character string (optional) specifying the column name in geno_table containing sample identifiers. Defaults to NULL, in which case it is assumed the first column contains identifiers. Only used if binary_matrix not provided.

pheno_sample_col

A character string (optional) specifying the column name in pheno_table containing sample identifiers. Defaults to NULL, in which case it is assumed the first column contains identifiers. Only used if binary_matrix not provided.

sir_col

A character string specifying the column name in pheno_table that contains the resistance interpretation (SIR) data. The values should be "S", "I", "R" or otherwise interpretable by AMR::as.sir(). If not provided, the first column prefixed with "phenotype*" will be used if present, otherwise an error is thrown. Only used if binary_matrix not provided.

ecoff_col

A character string specifying the column name in pheno_table that contains resistance interpretations (SIR) made against the ECOFF rather than a clinical breakpoint. The values should be "S", "I", "R" or otherwise interpretable by AMR::as.sir(). Default ecoff. Set to NULL if not available. Only used if binary_matrix not provided.

icat

A logical indicating whether to calculate PPV for "I" (if such a category exists in the phenotype column) (default FALSE).

marker_col

A character string specifying the column name in geno_table containing the marker identifiers. Default "marker". Only used if binary_matrix not provided.

binary_matrix

A data frame containing the original binary matrix output from the get_binary_matrix() function. If not provided (or set to NULL), user must specify geno_table, pheno_table, antibiotic, drug_class_list and optionally geno_sample_col, pheno_sample_col, sir_col, ecoff_col, marker_col to pass to get_binary_matrix().

min

Minimum number of genomes with the solo marker, to include the marker in the plot (default 1).

axis_label_size

Font size for axis labels in the PPV plot (default 9).

pd

A ggplot2::position_dodge() object controlling horizontal spacing of points and confidence intervals in the PPV plot. Default position_dodge(width = 0.8).

excludeRanges

Vector of phenotype categories (comprised of "R", "I", "NWT") for which we should ignore MIC values expressed as ranges when calculating PPVs. To include MICs expressed as ranges set this to NULL.

colours_SIR

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 colour names or hexadecimal colour codes. Default values are those used in the AMR package AMR::scale_fill_sir().

colours_ppv

A named vector of colours for the plot of PPV estimates. The names should be "R", "I", "NWT", and the values should be valid colour names or hexadecimal colour codes.

Value

A list containing the following elements:

  • solo_stats: A data frame summarizing the PPV for resistance (R vs S/I) and NWT (R/I vs S), including the number of positive hits, sample size, PPV, and 95% confidence intervals for each marker.

  • combined_plot: A combined ggplot object showing the PPV plot for the solo markers, and a bar plot for the phenotype distribution.

  • solo_binary: A dataframe with binary values indicating the presence or absence of the solo markers.

  • solo_binary_norange: A dataframe with binary values indicating the presence or absence of the solo markers, excluding samples for which MIC or disk measures are expressed as ranges.

  • amr_binary: A copy of the genotype-phenotype binary matrix for all markers (either provided as input or generated by the function)

  • plot_order: Ordered list of rows in the output plot (to facilitate alignment with other plots)

Details

The function analyzes the predictive power of individual AMR markers when they are found 'solo' in the genome with no other markers associated with the same class. The phenotype data are matched with genotype presence/absence and then stratified to compute PPV for resistance and non-wild-type interpretations. The function also generates plots to aid in interpretation.

Examples

if (FALSE) { # \dontrun{
geno_table <- import_amrfp(ecoli_geno_raw, "Name")
head(ecoli_ast)

# Generate binary matrix
binary_matrix <- get_binary_matrix(
  geno_table = geno_table,
  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 solo PPV analysis plot analysis using this binary_matrix
solo_ppv_analysis(binary_matrix = binary_matrix)

# Alternatively, generate binary matrix and solo PPV analysis in one step
# (note `antibiotic` and `drug_class` list are optional here, and only used
# for titling the plot)
soloPPV_cipro <- solo_ppv_analysis(
  binary_matrix = binary_matrix,
  antibiotic = "Ciprofloxacin",
  drug_class_list = c("Quinolones")
)

soloPPV_cipro$solo_stats
soloPPV_cipro$combined_plot
} # }