loadMatrix {somhca} | R Documentation |
Load Data and Convert to a Matrix
Description
Loads data from a CSV file or an in-memory object (data frame or matrix), optionally removes row headings, and applies specified normalization methods before converting the data to a matrix. In the original dataset, rows represent observations (e.g., samples), columns represent variables (e.g., features), and all cells (except for column headers and, if applicable, row headers) must only contain numeric values.
Usage
loadMatrix(input, remove_row_headings = FALSE, scaling = "no")
Arguments
input |
A string specifying the path to the CSV file, or an in-memory object (data frame or matrix). |
remove_row_headings |
A logical value. If 'TRUE', removes the first column of the dataset. This is useful when the first column contains non-numeric identifiers (e.g., sample names) that should be excluded from the analysis. Default is 'FALSE'. |
scaling |
A string specifying the scaling method. Options are:
|
Value
A matrix with the processed data.
Examples
# Example 1: Load toy data from a CSV file
file_path <- system.file("extdata", "toy_data.csv", package = "somhca")
# Run the loadMatrix function with the mock data
myMatrix <- loadMatrix(file_path, TRUE, "minMax")
# Example 2: Load from a toy data frame
df <- data.frame(
ID = paste0("Sample", 1:100), # Character column for row headings
matrix(rnorm(900), nrow = 100, ncol = 9) # Numeric data
)
# Run the loadMatrix function with the mock data
myMatrix <- loadMatrix(df, TRUE, "zScore")
# Example 3: Load from a toy matrix
mat <- matrix(rnorm(900), nrow = 100, ncol = 9) # Numeric data
# Run the loadMatrix function with the mock data
myMatrix <- loadMatrix(mat, FALSE, "simpleFeature")