MALDIrppa

MALDI mass spectrometry data robust pre-processing and other helper functions

This package helps to implement a robust approach to deal with mass spectrometry (MS) data. It is aimed at alleviating reproducibility issues and pernicious effects of deviating signals on both data pre-processing and downstream data analysis. Based on robust statistical methods, it facilitates the identification and filtering of low-quality mass spectra and atypical peak profiles as well as monitoring and data handling through pre-processing, which extends existing computational tools for MS data. MALDIrppa integrates with and extends existing R packages for MS proteomics data. Helper functions are included that allow to export data into formats used for downstream analyses.

Installation

The latest version of the package is available on CRAN and can be installed from R using

install.packages("MALDIrppa")

Alternatively, it can be installed from Github through the devtools package:

# For non-windows users
devtools::install_github(repo = "Japal/MALDIrppa")
# For windows users
devtools::install_url(url="https://github.com/Japal/MALDIrppa/archive/master.zip", INSTALL_opt= "--no-multiarch")

For compatibility with previous pre-processing pipelines, a previous version of MALDIrppa can be installed from source files. For example, for v1.0.5-1:

install.packages("https://cran.r-project.org/src/contrib/Archive/MALDIrppa/MALDIrppa_1.0.5-1.tar.gz", repo=NULL, type="source")

Getting started

# Loading the library
library("MALDIrppa")

Documentation and examples are available through the help pages (?MALDIrppa).

Illustrative pipeline

The package's vignette provides a walk through the main features and functions:

• Article on website: https://japal.github.io/MALDIrppa/
• CRAN: https://cran.r-project.org/web/packages/MALDIrppa/vignettes/MALDIrppa_vignette.html

Citation

Palarea-Albaladejo J., McLean K., Wright F. and Smith (2018). MALDIrppa: quality control and robust analysis for mass spectrometry data. Bioinformatics 34(3):522–523. <doi: http://dx.doi.org/10.1093/bioinformatics/btx628>