Work

MALDIrppa: quality control and robust analysis for mass spectrometry data

Year: 2017

Type: article

Abstract: Summary: This R 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 high-throughput data. Availability and implementation: MALDIrppa is implemented as a package for the R environment for data analysis and it is freely available to download from the CRAN repository at https://CRAN.R-project.org/package=MALDIrppa. Contact: [email protected].

Source: Bioinformatics

DOI: 10.1093/bioinformatics/btx628

Authors: Javier Palarea-Albaladejo, Kevin Mclean, Frank Wright, David G E Smith

Institutions: Biomathematics and Statistics Scotland, Moredun Research Institute, Heriot-Watt University

Language: English

Topic: Advanced Proteomics Techniques and Applications

Subfield: Spectroscopy

Field: Chemistry

Domain: Physical Sciences

Open Access status: bronze

Funders: Rural and Environment Science and Analytical Services Division, Scottish Government

OpenAlex ID: W2762177954