Analysis of Microbial Social Behavior in Bacterial Consortia

Provides an S4 class and methods for analyzing microbial social behavior in bacterial consortia. Includes growth parameter extraction, social behavior classification (cooperators/cheaters/neutrals), diversity effect analysis, consortium assembly path finding, and stability analysis via coefficient of variation. Methods are described in Purswani et al. (2017) .

bsocialv2

Overview

bsocialv2 provides an S4 class and methods for analyzing microbial social behavior in bacterial consortia. The package implements a complete analysis pipeline:

Data Import - Raw plate reader data or pre-processed growth parameters
Growth Analysis - Parameter extraction (NGen, GR, LogPhase) via growthcurver or grofit
Social Behavior - Fitness comparisons identifying cooperators, cheaters, and neutrals
Diversity Effects - Relationship between consortium diversity and fitness
Stability Analysis - Coefficient of variation across replicates/diversity levels
Assembly Paths - Graph-based consortium assembly sequence finding

Installation

# Install from GitHub
remotes::install_github("Juane99/bsocialv2")

# Or install from CRAN (once accepted)
# install.packages("bsocialv2")

Quick Start

library(bsocialv2)

# Create a bsocial object
obj <- new("bsocial")

# Load your data
consortia <- read.csv("consortia.csv")
curated <- read.csv("curated_data.csv")

obj@cepas_seleccionadas <- setdiff(colnames(consortia), "Consortia")
obj@datos_crudos <- list(
  consortia = consortia,
  curated = curated,
  type = "curated"
)

# Run the analysis pipeline
obj <- transform_curated_data(obj)
obj <- analyze_growth(obj)
obj <- analyze_social_behavior(obj)
obj <- summarize_social_behavior(obj)
obj <- analyze_diversity(obj)
obj <- analyze_stability(obj)
obj <- analyze_biofilm_sequence(obj)

# Access results
obj@graficos$growth_scatter
obj@resultados_analisis$summary_gen

See vignette("bsocial-workflow") for a complete tutorial.