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AMR Logistic Regression Analysis

Source: R/plot_estimates.R
amr_logistic.Rd

Performs logistic regression to analyze the relationship between genetic markers and phenotype (R, and NWT) for a specified antibiotic.

Usage

amr_logistic(
  geno_table,
  pheno_table,
  antibiotic,
  drug_class_list,
  geno_sample_col = NULL,
  pheno_sample_col = NULL,
  sir_col = "pheno",
  ecoff_col = "ecoff",
  maf = 10,
  fit_glm = FALSE,
  single_plot = TRUE,
  colors = c("maroon", "blue4"),
  axis_label_size = 9,
  marker_col = "marker.label"
)

Arguments

geno_table

A data frame containing the genotype data.

pheno_table

A data frame containing the phenotypic data.

antibiotic

A character string specifying the antibiotic to model using logistic regression.

drug_class_list

A vector of drug class names. Used to subset the relevant markers for analysis.

geno_sample_col

(Optional) A character string specifying the column in geno_table that identifies the sample IDs. Defaults to NULL.

pheno_sample_col

(Optional) A character string specifying the column in pheno_table that identifies the sample IDs. Defaults to NULL.

sir_col

(Optional) A character string specifying the column in pheno_table that contains the phenotype values (e.g., resistance/susceptibility). Defaults to "pheno".

ecoff_col

(Optional) A character string specifying the column in pheno_table containing the ECOFF (epidemiological cutoff) values. Defaults to "ecoff".

maf

(Optional) An integer specifying the minimum allele frequency (MAF) threshold. Markers with a MAF lower than this value will be excluded. Defaults to 10.

fit_glm

(Optional) Change to TRUE to fit model with glm. Otherwise fit model with logistf (default).

single_plot

(Optional) A logical value. If TRUE, a single plot is produced comparing the estimates for resistance (R) and non-resistance (NWT). Otherwise, two plots are printed side-by-side. Defaults to TRUE.

colors

(Optional) A vector of two colors, to use for R and NWT models in the plots. Defaults to c("maroon", "blue4").

axis_label_size

(Optional) A numeric value controlling the size of axis labels in the plot. Defaults to 9.

marker_col

(Optional) Name of the column containing the marker identifiers, whose unique values will be treate as predictors in the regression. Defaults to "marker".

Value

A list with the following components:

  • bin_mat: The binary matrix of genetic data and phenotypic resistance information.

  • modelR: The fitted logistic regression model for resistance (R).

  • modelNWT: The fitted logistic regression model for non-resistance (NWT).

  • plot: A ggplot object comparing the estimates for resistance and non-resistance with corresponding statistical significance indicators.

Examples

# Example usage of the amr_logistic function
result <- amr_logistic(
  geno_table = import_amrfp(ecoli_geno_raw, "Name"),
  pheno_table = ecoli_ast,
  sir_col = "pheno_clsi",
  antibiotic = "Ciprofloxacin",
  drug_class_list = c("Quinolones"),
  maf = 10
)
#>  Defining NWT in binary matrix using ecoff column provided: ecoff 
#> ...Fitting logistic regression model to R using logistf
#> Warning: logistf.fit: Maximum number of iterations for full model exceeded. Try to increase the number of iterations or alter step size by passing 'logistf.control(maxit=..., maxstep=...)' to parameter control
#> ...Fitting logistic regression model to NWT using logistf
#> Warning: logistf.fit: Maximum number of iterations for full model exceeded. Try to increase the number of iterations or alter step size by passing 'logistf.control(maxit=..., maxstep=...)' to parameter control
#> Generating plots

# To access the plot:
print(result$plot)