nmr_normalize {AlpsNMR} | R Documentation

## Normalize nmr_dataset_1D samples

### Description

The `nmr_normalize` function is used to normalize all the samples according to a given criteria.

### Usage

    nmr_normalize(
      samples,
      method = c("area", "max", "value", "region", "pqn", "none"),
      ...
    )

    nmr_normalize_extra_info(samples)

### Arguments

`samples` | A nmr_dataset_1D object
`method` | The criteria to be used for normalization - area: Normalize to the total area - max: Normalize to the maximum intensity - value: Normalize each sample to a user defined value - region: Integrate a region and normalize each sample to that region - pqn: Use Probabalistic Quotient Normalization for normalization - none: Do not normalize at all
`...` | Method dependent arguments: - `method == "value"`: - `value`: A numeric vector with the normalization values to use - `method == "region"`: - `ppm_range`: A chemical shift region to integrate - `...`: Other arguments passed on to nmr_integrate_regions

### Details

The `nmr_normalize_extra_info` function is used to extract additional information after the normalization. Typically, we want to know what was the actual normalization factor applied to each sample. The extra information includes a plot, representing the dispersion of the normalization factor for each sample.

### Value

The nmr_dataset_1D object, with the samples normalized. Further information for diagnostic of the normalization process is also saved and can be extracted by calling `nmr_normalize_extra_info()` afterwards.

### See Also

Other nmr_dataset_1D functions: `[.nmr_dataset_1D()`, `computes_peak_width_ppm()`, `file_lister()`, `files_to_rDolphin()`, `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_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

    nmr_dataset <- nmr_dataset_load(system.file("extdata", "nmr_dataset.rds", package = "AlpsNMR"))
    nmr_dataset <- nmr_normalize(nmr_dataset, method = "area")
    norm_dataset <- nmr_normalize(nmr_dataset)
    norm_dataset$plot
    nmr_dataset <- nmr_dataset_load(system.file("extdata", "nmr_dataset.rds", package = "AlpsNMR"))
    nmr_dataset <- nmr_normalize(nmr_dataset, method = "area")
    norm_extra_info <- nmr_normalize_extra_info(nmr_dataset)
    norm_extra_info$plot

[Package AlpsNMR version 3.0.6 Index]