Version: 2.0.2
Basic plotting, data manipulation and processing of MS-based Proteomics data.
MSnbase provides infrastructure for manipulation, processing and visualisation of mass spectrometry and proteomics data, ranging from raw to quantitative and annotated data.
MSnbase aims to provide a reproducible research framework for proteomics data analysis. It should allow researchers to easily mine mass spectrometry data, explore the data and its statistical properties and visually display these.
MSnbase also aims at being compatible with the infrastructure implemented in Bioconductor, in particular Biobase. As such, classes developed specifically for proteomics mass spectrometry data are based on the eSet and ExpressionSet classes. The main goal is to assure seamless compatibility with existing meta data structure, accessor methods and normalisation techniques.
- Processing LC/MS and GC/MS data
- Proteomics / Untargeted
- Proteomics / Targeted
- Metabolomics / Untargeted
- Metabolomics / Targeted
- MS / LC-MS
- MS / GC-MS
Laurent Gatto Guangchuang Yu Samuel Wieczorek Vasile-Cosmin Lazar Vladislav Petyuk Thomas Naake Richie Cotton Martina Fisher Johannes Rainer Sebastian Gibb
- Kristian Peters (IPB-Halle)
- Christoph Ruttkies
- Payam Emami
- Gatto L, Lilley K (2012): MSnbase - an R/Bioconductor package for isobaric tagged mass spectrometry data visualization, processing and quantitation. Bioinformatics 28: 288-289.
docker build -t msnbase .Alternatively, pull from repo:
docker pull container-registry.phenomenal-h2020.eu/phnmnl/msnbaseOn a PhenoMeNal Cloud Research Environment Galaxy environment, go to MS tool category or type msnbase-read-msms in the search tools text field, and then click on msnbase-read-msms and select a mzML file containing MS/MS information from the history, then press run.