impute {omicsTools} | R Documentation |
Impute function
Description
This function performs data cleaning and imputation on a given data matrix. It removes blank and NIST samples, features with NA values more than the specified threshold, and imputes remaining NA values with half of the smallest non-NA value.
Usage
impute(data, percent = 0.2)
Arguments
data |
A data frame containing the sample data. The first column should contain the sample identifiers, and the rest of the columns contain the peaks. |
percent |
A numeric value between 0 and 1 representing the threshold of the percentage of NA values a feature should have for it to be removed from the dataset. Default value is 0.2. |
Value
A data frame with the first column as the sample identifiers and the rest of the columns containing the cleaned and imputed peak intensities.
Author(s)
Yaoxiang Li yl814@georgetown.edu
Georgetown University, USA
License: GPL (>= 3)
Examples
# Load the CSV data
data_file <- system.file("extdata", "example1.csv", package = "omicsTools")
data <- readr::read_csv(data_file)
# Apply the impute function
imputed_data <- omicsTools::impute(data, percent = 0.2)
# Write the imputed data to a new CSV file
readr::write_csv(imputed_data, paste0(tempdir(), "/imputed_data.csv"))