sb_corr: Signal/batch correction for mass spectrometry data

In computational-metabolomics/structToolbox: Data processing & analysis tools for Metabolomics and other omics

Signal/batch correction for mass spectrometry data

Description

Applies Quality Control Robust Spline (QC-RSC) method to correct for signal drift and batch differences in mass spectrometry data.

Usage

sb_corr(
  order_col,
  batch_col,
  qc_col,
  smooth = 0,
  use_log = TRUE,
  min_qc = 4,
  qc_label = "QC",
  spar_lim = c(-1.5, 1.5),
  ...
)

Arguments

order_col	(character) The column name of sample_meta indicating the run order of the samples.
batch_col	(character) The column name of sample_meta indicating the batch each sample was measured in.
qc_col	(character) The column name of sample_meta indicating the group each sample is a member of.
smooth	(numeric) The amount of smoothing applied (0 to 1). If set to 0 the smoothing parameter will be estimated using leave-one-out cross-validation. The default is 0.
use_log	(logical) Log tranformation. Allowed values are limited to the following: "TRUE": The data is log transformed prior to performing signal correction. "FALSE": Signal correction is applied to the input data. The default is TRUE.
min_qc	(numeric) The minimum number of QC samples required for signal correction. The default is 4.
qc_label	(character) The label used to identify QC samples. The default is "QC".
spar_lim	(numeric) A two element vector specifying the upper and lower limits when spar = 0. Allows the value of spar to be constrained within these limits to prevent overfitting. The default is c(-1.5, 1.5).
...	Additional slots and values passed to struct_class.

Details

This object makes use of functionality from the following packages:

• pmp

Value

A sb_corr object with the following output slots:

corrected	(DatasetExperiment) The DatasetExperiment after signal/batch correction has been applied.
fitted	(data.frame) The fitted splines for each feature.

struct object

Inheritance

A sb_corr object inherits the following struct classes:

⁠[sb_corr]⁠ >> ⁠[model]⁠ >> ⁠[struct_class]⁠

References

Jankevics A, Lloyd GR, Weber RJM (2023). pmp: Peak Matrix Processing and signal batch correction for metabolomics datasets. doi:10.18129/B9.bioc.pmp https://doi.org/10.18129/B9.bioc.pmp, R package version 1.14.0, https://bioconductor.org/packages/pmp.

Kirwan JA, Broadhurst DI, Davidson RL, Viant MR (2013). "Characterising and correcting batch variation in an automated direct infusion mass spectrometry (DIMS) metabolomics workflow." Analytical and Bioanalytical Chemistry, 405(15), 5147-5157.

Examples

M = sb_corr(
      order_col = character(0),
      batch_col = character(0),
      qc_col = character(0),
      smooth = 0,
      use_log = FALSE,
      min_qc = 4,
      qc_label = "QC",
      spar_lim = c(-1.5, 1.5))

M = sb_corr(order_col='run_order',batch_col='batch_no',qc_col='class')

computational-metabolomics/structToolbox documentation built on Feb. 12, 2024, 2:15 a.m.