omicsTools (version 1.1.7)

perform_batch_assessment: Perform Principal Variance Component Analysis for Batch Effect Assessment

Description

This function performs Principal Variance Component Analysis to assess batch effects in the dataset.

Usage

perform_batch_assessment(data_matrix, sample_info, batch_effects, threshold)

Value

A PVCA object containing the results of the batch effect assessment.

Arguments

data_matrix

A data frame or matrix where rows represent features and columns represent samples.

sample_info

A data frame containing sample information with rows matching the columns of `data_matrix`.

batch_effects

A character vector of column names in `sample_info` that represent batch effects.

threshold

A numeric value between 0 and 1 to specify the PVCA threshold.

Examples

# Example data
set.seed(123)
data_matrix <- data.frame(
  sample1 = rnorm(100),
  sample2 = rnorm(100),
  sample3 = rnorm(100),
  sample4 = rnorm(100),
  sample5 = rnorm(100),
  sample6 = rnorm(100),
  sample7 = rnorm(100),
  sample8 = rnorm(100),
  sample9 = rnorm(100),
  sample10 = rnorm(100)
)
rownames(data_matrix) <- paste0("feature", 1:100)

sample_info <- data.frame(
  dose = c(0, 1, 2, 1, 0, 2, 1, 0, 2, 1),
  time = c(-1, 1, 25, -1, 1, 25, -1, 1, 25, -1),
  batch = rep(c("A", "B", "C"), length.out = 10)
)
rownames(sample_info) <- colnames(data_matrix)

# Perform Batch Effect Assessment
if (requireNamespace("Biobase", quietly = TRUE) &&
    requireNamespace("pvca", quietly = TRUE)) {
  pvca_results <- perform_batch_assessment(
    data_matrix,
    sample_info,
    c("batch", "dose", "time"),
    0.6
  )
}