SCCharacterizePeaks: R6 Class Controlling Peak Characterization

In MoseleyBioinformaticsLab/ScanCentricPeakCharacterization: Functionality for Characterizing Peaks in Mass Spectrometry in a Scan-Centric Manner

R6 Class Controlling Peak Characterization

Description

Peak characterization control

Details

Peak characterization associates data with the SCZip, SCPeakRegionFinder, and controls their execution.

Public fields

found_peaks

peaks found by a function

id

a holder for the ID of the sample

frequency_fit_description

the model for conversion to frequency

mz_fit_description

the model for converting back to m/z

calculate_peak_area

whether to calculate peak area or not

sc_peak_region_finder

the peak finder object

sc_zip

the SCZip that represents the final file

in_file

the input file

metadata_file

the metadata file

out_file

where everything gets saved

temp_loc

where intermediates get saved

Methods

Public methods

• SCCharacterizePeaks$load_file()

• SCCharacterizePeaks$filter_scans()

• SCCharacterizePeaks$choose_frequency_model()

• SCCharacterizePeaks$prepare_mzml_data()

• SCCharacterizePeaks$set_frequency_fit_description()

• SCCharacterizePeaks$set_mz_fit_description()

• SCCharacterizePeaks$generate_filter_scan_function()

• SCCharacterizePeaks$generate_choose_frequency_model_function()

• SCCharacterizePeaks$predict_frequency()

• SCCharacterizePeaks$check_frequency_model()

• SCCharacterizePeaks$get_frequency_data()

• SCCharacterizePeaks$scan_info()

• SCCharacterizePeaks$find_peaks()

• SCCharacterizePeaks$summarize()

• SCCharacterizePeaks$save_peaks()

• SCCharacterizePeaks$write_zip()

• SCCharacterizePeaks$run_all()

• SCCharacterizePeaks$prep_data()

• SCCharacterizePeaks$add_regions()

• SCCharacterizePeaks$run_splitting()

• SCCharacterizePeaks$new()

• SCCharacterizePeaks$clone()

---

Method load_file()

Loads the mzml data into the SCZip

Usage

SCCharacterizePeaks$load_file()

---

Method filter_scans()

Filter the scans in data.

Usage

SCCharacterizePeaks$filter_scans()

---

Method choose_frequency_model()

Choose the single frequency model.

Usage

SCCharacterizePeaks$choose_frequency_model()

---

Method prepare_mzml_data()

Prepare the mzml data.

Usage

SCCharacterizePeaks$prepare_mzml_data()

---

Method set_frequency_fit_description()

Set the frequency fit description

Usage

SCCharacterizePeaks$set_frequency_fit_description(frequency_fit_description)

Arguments

frequency_fit_description

the frequency model description

---

Method set_mz_fit_description()

Set the mz fit description

Usage

SCCharacterizePeaks$set_mz_fit_description(mz_fit_description)

Arguments

mz_fit_description

the m/z model description

---

Method generate_filter_scan_function()

Sets the scan filtering and check for outlier function.

Usage

SCCharacterizePeaks$generate_filter_scan_function(
  rtime = NA,
  y.freq = NA,
  f_function = NULL
)

Arguments

rtime

retention time limits of scans to keep

y.freq

y-frequency coefficient limits of scans to keep (NA)

f_function

a full function to set as the filtering function

---

Method generate_choose_frequency_model_function()

Sets the function for choosing a single frequency model

Usage

SCCharacterizePeaks$generate_choose_frequency_model_function(f_function = NULL)

Arguments

f_function

the function for choosing a single model

---

Method predict_frequency()

Run frequency prediction

Usage

SCCharacterizePeaks$predict_frequency()

---

Method check_frequency_model()

Check the frequency model

Usage

SCCharacterizePeaks$check_frequency_model()

---

Method get_frequency_data()

Get the frequency data from the SCMzml bits

Usage

SCCharacterizePeaks$get_frequency_data()

---

Method scan_info()

Get the SCMzml$scan_info out

Usage

SCCharacterizePeaks$scan_info()

---

Method find_peaks()

Do the peak characterization without saving

Usage

SCCharacterizePeaks$find_peaks(stop_after_initial_detection = FALSE)

Arguments

stop_after_initial_detection

should it stop after the initial peak finding

---

Method summarize()

Generates the JSON output summary.

Usage

SCCharacterizePeaks$summarize()

---

Method save_peaks()

Saves the peaks and JSON to the temp file

Usage

SCCharacterizePeaks$save_peaks()

---

Method write_zip()

Write the zip file

Usage

SCCharacterizePeaks$write_zip()

---

Method run_all()

Runs all of the pieces for peak characterization in order

Usage

SCCharacterizePeaks$run_all(
  filter_scan_function = NULL,
  choose_frequency_model_function = NULL
)

Arguments

filter_scan_function

the scan filtering function

choose_frequency_model_function

the function for choosing a frequency model

---

Method prep_data()

Loads and preps the data for characterization

Usage

SCCharacterizePeaks$prep_data()

---

Method add_regions()

Adds initial regions for finding real peak containing regions

Usage

SCCharacterizePeaks$add_regions()

---

Method run_splitting()

Does initial region splitting and peak finding in scans

Usage

SCCharacterizePeaks$run_splitting()

---

Method new()

Creates a new SCCharacterizePeaks class

Usage

SCCharacterizePeaks$new(
  in_file,
  metadata_file = NULL,
  out_file = NULL,
  temp_loc = tempfile("scpcms"),
  frequency_fit_description = NULL,
  mz_fit_description = NULL,
  filter_remove_outlier_scans = NULL,
  choose_single_frequency_model = NULL,
  sc_peak_region_finder = NULL,
  calculate_peak_area = FALSE
)

Arguments

in_file

the mass spec data file to use (required)

metadata_file

a json metadata file (optional)

out_file

where to save the final zip container

temp_loc

a specified temporary location

frequency_fit_description

mz -> frequency model

mz_fit_description

frequency -> mz model

filter_remove_outlier_scans

function for scan filtering

choose_single_frequency_model

function to choose a single frequency model

sc_peak_region_finder

a blank SCPeakRegionFinder to use instead of the default

calculate_peak_area

should peak areas be returned as well as height?

---

Method clone()

The objects of this class are cloneable with this method.

Usage

SCCharacterizePeaks$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

## Not run: 
  lipid_sample = system.file("extdata",
     "lipid_example.mzML",
     package = "ScanCentricPeakCharacterization")
  sc_char = SCCharacterizePeaks$new(lipid_sample)

  # prep data and check model
  library(ggplot2)
  library(patchwork)
  sc_char$load_file()
  sc_char$generate_filter_scan_function()
  sc_char$generate_choose_frequency_model_function()
  sc_char$prepare_mzml_data()
  sc_char$check_frequency_model()

  # run characterization
  save_loc = "test.zip"
  sc_char = SCCharacterizePeaks$new(lipid_sample,
                                    out_file = save_loc)
  sc_char$run_all()

## End(Not run)

MoseleyBioinformaticsLab/ScanCentricPeakCharacterization documentation built on March 29, 2024, 11:32 p.m.