predict_sporulation: Predict Sporulation Potential

In SpoMAG: Probability of Sporulation Potential in MAGs

Predict Sporulation Potential

Description

This function predicts the sporulation potential of MAGs using an ensemble learning model. It uses probabilities from Random Forest and SVM classifiers as inputs to a meta-model.

Usage

predict_sporulation(binary_matrix)

Arguments

binary_matrix

A binary matrix (1/0) indicating gene presence/absence for each MAG. Must include a genome_ID column.

Value

A tibble with predicted class and probability of sporulation for each genome.

Examples

# Load package
library(SpoMAG)

# Load example annotation tables
file_spor <- system.file("extdata", "one_sporulating.csv.gz", package = "SpoMAG")
file_aspo <- system.file("extdata", "one_asporogenic.csv.gz", package = "SpoMAG")

# Read files
df_spor <- readr::read_csv(file_spor, show_col_types = FALSE)
df_aspo <- readr::read_csv(file_aspo, show_col_types = FALSE)

# Step 1: Extract sporulation-related genes
genes_spor <- sporulation_gene_name(df_spor)
genes_aspo <- sporulation_gene_name(df_aspo)

# Step 2: Convert to binary matrix
bin_spor <- build_binary_matrix(genes_spor)
bin_aspo <- build_binary_matrix(genes_aspo)

# Step 3: Predict using ensemble model (preloaded in package)

result_spor <- predict_sporulation(bin_spor)
result_aspo <- predict_sporulation(bin_aspo)

 

SpoMAG documentation built on June 8, 2025, 1:48 p.m.