suRface.analytics (version 0.1.0)

antimicrobial_analysis: Antimicrobial Data Analysis

Description

Analyzes and visualizes antimicrobial test data through a combination of descriptive statistics, inferential analyses (ANOVA, Tukey HSD, Chi-square), and multivariate techniques including Multidimensional Scaling (MDS), and Random Forest classification. This function provides insights into group differences, underlying data structure, and variable importance in antimicrobial activity.

Value

A list containing the results of the antimicrobial analysis, including:

• Summary statistics of the zone of inhibition per bacterial strain and antimicrobial agent.

• Chi-square test results for associations between bacterial strain and contact area.

• Boxplot visualizing the distribution of zone of inhibition across antimicrobial treatments and bacterial strains.

• Heatmap displaying zone of inhibition values across bacterial strains and antimicrobial agents.

• ANOVA and Tukey HSD test results for differences in zone of inhibition across treatments.

• Linear model diagnostics including residuals vs. fitted for model assumptions.

• MDS plot representing similarity of samples in reduced dimensions based on zone of inhibition.

• Random forest model used to classify bacterial response based on zone of inhibition.

• Variable importance results identifying key predictors from the random forest model.

• Variable importance plot visualizing the most influential variables in the classification task.

Arguments

zone_data

A data frame containing the results of antimicrobial testing, with the following columns: 'bacterial_strain', 'antimicrobial_agent', 'zone_inhibition', and 'contact_area'.

seed

Optional. A numeric value to set the seed for reproducibility. If NULL (default), no seed is set.

Author

Paul Angelo C. Manlapaz

Examples

# EXAMPLE 1: Two Bacterial Strain
bacterial_strain = rep(c("S. aureus", "K. pneumoniae"), each = 12)
antimicrobial_agent = rep(rep(c("Control", "HGS1 (30% wet pick-up)", "HGS2 (50% wet pick-up)",
                                "HGS3 (80% wet pick-up)"), each = 3), times = 2)
zone_inhibition = c(0, 0, 0, 10.2, 11.0, 9.8, 14.1, 13.8, 15.0, 18.5, 17.9, 19.2,
                    0, 0, 0, 8.5, 9.0, 8.8, 12.7, 13.1, 12.9, 16.4, 15.8, 16.9)
contact_area = c("Growth", "Growth", "Growth", "Partial Growth",
                 "Growth", "Partial Growth", "No Growth", "No Growth",
                 "Partial Growth", "No Growth", "No Growth", "No Growth",
                 "Growth", "Growth", "Growth", "Growth",
                 "Partial Growth", "Growth", "Partial Growth", "No Growth",
                 "No Growth", "No Growth", "No Growth", "No Growth")
zone_data <- data.frame(bacterial_strain, antimicrobial_agent, zone_inhibition, contact_area)
antimicrobial_analysis(zone_data)                 # seed = NULL, no seed is set
antimicrobial_analysis(zone_data, seed = 123)     # seed is set to ensure reproducible results

# EXAMPLE 2: Four Bacterial Strain
bacterial_strain = rep(c("S. aureus", "K. pneumoniae", "E. coli", "S. pneumoniae"), each = 12)
antimicrobial_agent = rep(rep(c("Control", "HGS1 (30% wet pick-up)", "HGS2 (50% wet pick-up)",
                                "HGS3 (80% wet pick-up)"), each = 3), times = 4)
zone_inhibition = c(0, 0, 0, 10.2, 11.0, 9.8, 14.1, 13.8, 15.0, 18.5, 17.9, 19.2,
                    0, 0, 0, 8.5, 9.0, 8.8, 12.7, 13.1, 12.9, 16.4, 15.8, 16.9,
                    0, 0, 0, 9.3, 8.9, 9.1, 13.0, 13.5, 13.2, 16.7, 17.0, 16.9,
                    0, 0, 0, 11.5, 11.2, 11.0, 15.2, 14.9, 15.0, 19.0, 18.7, 19.3)
contact_area = c("Growth", "Growth", "Growth", "Partial Growth",
                 "Growth", "Partial Growth", "No Growth", "No Growth",
                 "Partial Growth", "No Growth", "No Growth", "No Growth",
                 "Growth", "Growth", "Growth", "Growth",
                 "Partial Growth", "Growth", "Partial Growth", "No Growth",
                 "No Growth", "No Growth", "No Growth", "No Growth",
                 "Growth", "Growth", "Growth", "Partial Growth",
                 "Partial Growth", "Growth", "Partial Growth", "No Growth",
                 "Partial Growth", "No Growth", "No Growth", "No Growth",
                 "Growth", "Growth", "Growth", "Partial Growth",
                 "Partial Growth", "Growth", "No Growth", "No Growth",
                 "Partial Growth", "No Growth", "No Growth", "No Growth")
zone_data <- data.frame(bacterial_strain, antimicrobial_agent, zone_inhibition, contact_area)
antimicrobial_analysis(zone_data)                 # seed = NULL, no seed is set
antimicrobial_analysis(zone_data, seed = 123)     # seed is set to ensure reproducible results