MALDIquant and its associated R packages readBrukerFlexData and readMzXmlData are freely available from the R archive CRAN (http://cran.r-project.org). The software is distributed under the GNU General Public License (version 3 or later) and is accompanied by example files and data. Additional documentation is available from http://strimmerlab.org/software/maldiquant/.

We present version 2 of the MSnbase R/Bioconductor package. MSnbase provides infrastructure for the manipulation, processing and visualisation of mass spectrometry data. We focus on the new on-disk infrastructure, that allows the handling of large raw mass spectrometry experiment on commodity hardware and illustrate how the package is used for elegant data processing, method development and visualisation. .

Intact protein sequencing by tandem mass spectrometry (MS/MS), known as top-down protein sequencing, relies on efficient gas-phase fragmentation at multiple experimental conditions to achieve extensive amino acid sequence coverage. We developed the "topdownr" R-package for automated construction of multi-modal (i.e. involving CID, HCD, ETD, ETciD, EThcD and UVPD) MS/MS fragmentation methods on an orbitrap instrument platform and systematic analysis of the resultant spectra. We used topdownr to generate and analyze thousands of MS/MS spectra for five intact proteins of 10-30kDa. We achieved 90-100% coverage for the proteins tested and derived guiding principles for efficient sequencing of intact proteins. The data analysis workflow and statistical models of topdownr software and multi-modal MS/MS experiments provide a framework for optimizing MS/MS sequencing for any intact protein. Refined topdownr software will be suited for comprehensive characterization of protein pharmaceuticals and eventually also for de novo sequencing and detailed characterization of intact proteins.

Data visualization plays a key role in high-throughput biology. It is an essential tool for data exploration allowing to shed light on data structure and patterns of interest. Visualization is also of paramount importance as a form of communicating data to a broad audience. Here, we provided a short overview of the application of the R software to the visualization of proteomics data. We present a summary of R's plotting systems and how they are used to visualize and understand raw and processed MS-based proteomics data.