predict_sporulation {SpoMAG} | R Documentation |
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 |
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)
[Package SpoMAG version 0.1.0 Index]