PhenoSpectra (version 0.1.0)

feature_selection: Feature Selection for Spectral Data

Description

This function filters healthy vs diseased samples, selects the most discriminative spectral variables, applies FDR correction, and exports the results.

Usage

feature_selection(
  file_path,
  output_path = "selected_features.xlsx",
  fdr_threshold = 0.01
)

Value

A data.table containing selected spectral variables.

Arguments

file_path

Path to the cleaned dataset (output of qaqcs function).

output_path

Path to save the selected features table.

fdr_threshold

Threshold for filtering significant features (default: 0.01).

Examples

# Create mock spectral data
library(openxlsx)
mock_data <- data.frame(
  treatment = sample(0:1, 100, replace = TRUE),
  var1 = rnorm(100),
  var2 = rnorm(100),
  var3 = rnorm(100)
)
temp_file <- tempfile(fileext = ".xlsx")
write.xlsx(mock_data, temp_file)

# Perform feature selection
output_path <- tempfile(fileext = ".xlsx")
selected_features <- feature_selection(temp_file, output_path, fdr_threshold = 0.01)
head(selected_features)