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Files to rDoplhin

Source: R/to_rDolphin_blood.R
files_to_rDolphin.Rd

The rDolphin family functions are introduced to perform automatic targeted metabolite profiling. Therefore, ensure that you interpolated from -0.1 ppm in order to consider the TSP/DSS signal at 0.0 ppm. The function generates a list with the files required by to_rDolphin function. Then, it is required to save them with the save_files_to_rDolphin. to_rDolphin function will read the generated "parameters.csv" file. function.

Usage

files_to_rDolphin(nmr_dataset, biological_origin)

Arguments

nmr_dataset

An nmr_dataset object

biological_origin

String specify the type of sample (blood, urine, cell)

Value

a list containing:

  • meta_rDolphin: metadata in rDolphin format,

  • NMR_spectra: spectra matrix

  • ROI: ROI template

  • Parameters: parameters file

See also

Other import/export functions: Pipelines, load_and_save_functions, nmr_data(), nmr_meta_export(), nmr_read_bruker_fid(), nmr_read_samples(), nmr_zip_bruker_samples(), save_files_to_rDolphin(), save_profiling_output(), to_ChemoSpec()

Examples

if (FALSE) { # \dontrun{
# Set the directory in which rDolphin files will be saved
output_dir_10_rDolphin <- file.path(your_path, "10-rDolphin")
fs::dir_create(output_dir_10_rDolphin)

# Generate the files (for plasma/serum)
files_rDolphin <- files_to_rDolphin(nmr_dataset_0_10_ppm, blood)

# Save the files
save_files_to_rDolphin(files_rDolphin, output_dir_10_rDolphin)

# Build the rDolphin object. Do not forget to set the directory
setwd(output_dir_10_rDolphin)
rDolphin_object <- to_rDolphin("Parameters.csv")

# Visualize your spectra
rDolphin_plot(rDolphin_object)

# Run the main profiling function (it takes a while)
targeted_profiling <- Automatic_targeted_profiling(rDolphin_object)

# Save results
save_profiling_output(targeted_profiling, output_dir_10_rDolphin)

save_profiling_plots(
    output_dir_10_rDolphin, targeted_profiling$final_output,
    targeted_profiling$reproducibility_data
)

# Additionally, you can run some stats
intensities <- targeted_profiling$final_output$intensity
group <- as.factor(rDolphin_object$Metadata$type)
model_PLS <- rdCV_PLS_RF(X = intensities, Y = group)
} # }