compute_means_vars: Compute Summary Statistics for a List of Datasets

In SUMO: Generating Multi-Omics Datasets for Testing and Benchmarking

Compute Summary Statistics for a List of Datasets

Description

Computes overall, row-wise, and column-wise means and standard deviations for each dataset in a list. Also provides average statistics across datasets.

Usage

compute_means_vars(data_list)

Arguments

data_list

A list of numeric matrices or data frames. Each entry should be a matrix or data frame with numeric values.

Value

A named list containing:

• Overall mean and SD for each dataset.

• Average row-wise mean and SD.

• Average column-wise mean and SD.

• mean_smp: Average row-wise mean across all datasets.

• sd_smp: Average row-wise SD across all datasets.

Examples

# Example using simulated matrices
set.seed(123)
dataset1 <- matrix(rnorm(100, mean = 5, sd = 2), nrow = 10, ncol = 10)
dataset2 <- matrix(rnorm(100, mean = 10, sd = 3), nrow = 10, ncol = 10)
data_list <- list(dataset1, dataset2)
results <- compute_means_vars(data_list)
print(results)

## Not run: 
# Example using real experimental data (requires MOFAdata)
if (requireNamespace("MOFAdata", quietly = TRUE)) {
  utils::data("CLL_data", package = "MOFAdata")
  CLL_data2 <- CLL_data[c(2, 3)]
  results <- compute_means_vars(CLL_data2)
  print(results)
}

## End(Not run)

SUMO documentation built on June 8, 2025, 12:45 p.m.