lcms_spectral_sig_features: Extract significant features from a MAIT object

In sipss/NIHSlcms: Signal processing of LC-MS metabolomics

Description

Function lcms_spectral_sig_features takes a MAIT-class object and obtains which of the variables are significant given a p-value threshold. The parameters of the significant features can ve printed to an output table (TRUE by default). Depending on the number of classes in the data, the function chooses between using ANOVA test or T-Student test.

Usage

lcms_spectral_sig_features(
  MAIT.object = NULL,
  pvalue = 0.05,
  p.adj = "none",
  printCSVfile = FALSE,
  scale = FALSE,
  parametric = TRUE,
  var.equal = FALSE,
  test.fun = NULL,
  jitter = FALSE,
  jitter.factor = 1,
  jitter.amount = 0,
  namefun = NULL
)

Value

A MAIT-class object containing the significant features of the scores slot of MAIT-class object used as an input.

See Also

Other metabolite identification functions: lcms_identify_metabolites(), lcms_peak_annotation(), lcms_peak_table_boxplots(), lcms_peak_table_pca(), lcms_raw_data(), lcms_sig_peaks_table(), lcms_to_mait(), lcms_write_parameter_table()

Other dataset_peak_table functions: lcms_dataset_load(), lcms_identify_metabolites(), lcms_peak_annotation(), lcms_peak_table_boxplots(), lcms_peak_table_pca(), lcms_plot_tics(), lcms_raw_data(), lcms_sig_peaks_table(), lcms_tics(), lcms_to_mait()

Other import/export functions: lcms_convert_ipo_to_xcms(), lcms_dataset_load(), lcms_dataset_save(), lcms_identify_metabolites(), lcms_meta_export(), lcms_meta_read(), lcms_peak_annotation(), lcms_raw_data(), lcms_read_ipo_to_xcms(), lcms_read_samples(), lcms_rearrange_datafiles_by_class(), lcms_sig_peaks_table(), lcms_to_mait(), lcms_write_opt_params(), lcms_write_parameter_table(), phData()

Examples

## Not run: 
file_name <-  system.file("extdata", "peak_table_ann.rds", package = "AlpsLCMS")
peak_table <- base::readRDS(file_name)
peak_table_sig_ann <- lcms_spectral_sig_features(MAIT.object = peak_table,
                                          pvalue=0.05,
                                          p.adj="none",
                                          scale=FALSE)
print(peak_table_sig_ann)

## End(Not run)

sipss/NIHSlcms documentation built on May 13, 2021, 6:19 p.m.