files_to_rDolphin {AlpsNMR} | R Documentation

## Files to rDoplhin

### Description

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()`

Other nmr_dataset_1D functions: `[.nmr_dataset_1D()`, `computes_peak_width_ppm()`, `file_lister()`, `format.nmr_dataset_1D()`, `is.nmr_dataset_1D()`, `load_and_save_functions`, `new_nmr_dataset_1D()`, `nmr_align_find_ref()`, `nmr_baseline_removal()`, `nmr_baseline_threshold()`, `nmr_exclude_region()`, `nmr_integrate_regions()`, `nmr_interpolate_1D()`, `nmr_meta_add()`, `nmr_meta_export()`, `nmr_meta_get_column()`, `nmr_meta_get()`, `nmr_normalize()`, `nmr_pca_build_model()`, `nmr_pca_outliers_filter()`, `nmr_pca_outliers_plot()`, `nmr_pca_outliers_robust()`, `nmr_pca_outliers()`, `nmr_ppm_resolution()`, `plot.nmr_dataset_1D()`, `plot_webgl()`, `print.nmr_dataset_1D()`, `rdCV_PLS_RF_ML()`, `rdCV_PLS_RF()`, `save_files_to_rDolphin()`, `to_ChemoSpec()`, `validate_nmr_dataset_peak_table()`, `validate_nmr_dataset()`

### Examples

    ## Not run:
    # 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)

    ## End(Not run)

[Package AlpsNMR version 3.2.3 Index]