| Literature DB >> 29028890 |
Javier Palarea-Albaladejo1, Kevin Mclean2, Frank Wright1, David G E Smith3.
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: javier.palarea@bioss.ac.uk.Mesh:
Year: 2018 PMID: 29028890 DOI: 10.1093/bioinformatics/btx628
Source DB: PubMed Journal: Bioinformatics ISSN: 1367-4803 Impact factor: 6.937