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Description

Correction of Preprocessed MS Data.

An 'R' implementation of the 'python' program Metabolomics Peak Analysis Computational Tool ('MPACT') (Robert M. Samples, Sara P. Puckett, and Marcy J. Balunas (2023) <doi:10.1021/acs.analchem.2c04632>). Filters in the package serve to address common errors in tandem mass spectrometry preprocessing, including: (1) isotopic patterns that are incorrectly split during preprocessing, (2) features present in solvent blanks due to carryover between samples, (3) features whose abundance is greater than user-defined abundance threshold in a specific group of samples, for example media blanks, (4) ions that are inconsistent between technical replicates, and (5) in-source fragment ions created during ionization before fragmentation in the tandem mass spectrometry workflow.

mpactr

R-CMD-check test-coverage lint pkgdown

Overview

mpactr is a collection of filters for the purpose of identifying high quality MS1 features by correcting peak selection errors introduced during the pre-processing of tandem mass spectrometry data.

Filters in this package address the following issues:

  • filter_mispicked_ions(): removal of mispicked peaks, or those isotopic patterns that are incorrectly split during preprocessing.
  • filter_group(): removal of features overrepresented in a specific group of samples; for example removal of features present in solvent blanks due to carryover between samples.
  • filter_cv(): removal of non-reproducible features, or those that are inconsistent between technical replicates.
  • filter_insource_ions(): removal of fragment ions created during the first ionization in the tandem MS/MS workflow.

All filters are independent, meaning they can be used to create a project-specific workflow, or you can learn more in the Filter vignette.

Installation

You can install the CRAN version with:

install.packages("mpactr")

You can install the development version of mpactr from GitHub with:

# install.packages("devtools")
devtools::install_github("SchlossLab/mpactr")

Get started

See the Filter vignette to get started.

Getting help

If you encounter an issue, please file an issue on GitHub. Please include a minimal reproducible example with your issue.

Contributing

Is there a feature you’d like to see included, please let us know! Pull requests are welcome on GitHub.

Metadata

Version

0.1.0

License

Unknown

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