Spectral processing using spectral binning — tar_spectral

Targets for spectral processing of FIE-HRMS data using spectral binning.

Usage

tar_spectral_binning(
  name,
  mzML = NULL,
  sample_info = NULL,
  parameters = NULL,
  plots = c("chromatogram", "fingerprint", "TIC", "purity_dist", "centrality_dist"),
  verbose = TRUE,
  summary = TRUE,
  export_path = "exports/spectral_processing"
)

Arguments

name: Symbol. The name for the collection of targets. This serves as a prefix for target names.
mzML: A character vector of mzML data file paths. If NULL, target input will be expected from an existing target. See details.
sample_info: A tibble containing the sample information. See details for the specifications. If NULL, target input will be expected from an existing target. See details.
parameters: S4 object of class BinParameters. If NULL, binneR::detectParameters() will be used to detect the spectral binning parameters automatically..
plots: A character vector of plot types. Set to NULL to skip all plots.
verbose: Show spectral processing console output.
summary: Boolean. Include additional summary targets.
export_path: Destination path of export files. Set to NULL to skip exports.

Value

A list of target objects for processing mzML data files using spectral binning.

Details

Specifying arguments mzML and sample_info as NULL enables the use of one of the data file and sample information from one of the input target factories, tar_input_file_path(), tar_input_grover() or tar_input_piggyback(). See the example using tar_input_piggyback() below.

Examples

if (FALSE) {
## Perform spectral binning by specifying the file paths and sample information directly
targets::tar_dir({
    targets::tar_script({
        library(hrmtargets)
        file_paths <- metaboData::filePaths('FIE-HRMS','UrineTechnical',
                                            ask = FALSE)
        sample_info <- metaboData::runinfo('FIE-HRMS','UrineTechnical',
                                           ask = FALSE)
        
        list(
            tar_spectral_binning(example,
                                 mzML = file_paths,
                                 sample_info = sample_info)
        )
    })
    targets::tar_make()
    targets::tar_read(example_results_spectral_processing)
    targets::tar_read(example_plot_fingerprint)
})

## Perform spectral binning by using tar_input_piggyback() 
targets::tar_dir({
    targets::tar_script({
        library(hrmtargets)
        name <- rlang::expr(example)
        
        list(
            tar_input_piggyback(!!name,
                                'FIE-HRMS_BdistachyonTechnical',
                                repo = 'jasenfinch/metaboData'),
            tar_spectral_binning(!!name)
        )
    })
    targets::tar_make()
    targets::tar_read(example_results_spectral_processing)
    targets::tar_read(example_plot_fingerprint)
})
}