nmr_pca_outliers: Compute PCA residuals and score distance for each sample

In AlpsNMR: Automated spectraL Processing System for NMR

Description

Compute PCA residuals and score distance for each sample

Usage

nmr_pca_outliers(
  nmr_dataset,
  pca_model,
  ncomp = NULL,
  quantile_critical = 0.975
)

Arguments

nmr_dataset	An nmr_dataset_1D object
pca_model	A pca model returned by nmr_pca_build_model
ncomp	Number of components to use. Use NULL for 90% of the variance
quantile_critical	critical quantile

Value

A list with:

• outlier_info: A data frame with the NMRExperiment, the Q residuals and T scores

• ncomp: Number of components used to compute Q and T

• Tscore_critical, QResidual_critical: Critical values, given a quantile, for both Q and T.

See Also

Other PCA related functions: nmr_pca_build_model(), nmr_pca_outliers_filter(), nmr_pca_outliers_plot(), nmr_pca_outliers_robust(), nmr_pca_plots

Other outlier detection functions: Pipelines, nmr_pca_outliers_filter(), nmr_pca_outliers_plot(), nmr_pca_outliers_robust()

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_normalize(), nmr_pca_build_model(), nmr_pca_outliers_filter(), nmr_pca_outliers_plot(), nmr_pca_outliers_robust(), 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

dir_to_demo_dataset <- system.file("dataset-demo", package = "AlpsNMR")
dataset <- nmr_read_samples_dir(dir_to_demo_dataset)
dataset_1D <- nmr_interpolate_1D(dataset, axis = c(min = -0.5, max = 10, by = 2.3E-4))
model <- nmr_pca_build_model(dataset_1D)
outliers_info <- nmr_pca_outliers(dataset_1D, model)

AlpsNMR documentation built on April 1, 2021, 6:02 p.m.