rMSIproc is an open-source R package for mass spectrometry (MS) imaging data pre-processing. The package is a multi-platform tool that has been tested on Linux and Windows systems. It provides optimized routines for a complete MSI pre-processing pipeline including: spectral smoothing, spectral alignment, mass calibration, intensity normalization, peak-picking and peak-binning. rMSIproc takes an MSI dataset as input and generates a processed MSI dataset and a peak matrix as output. The supported input formats are: imzML, rMSI format (TAR) and XMASS. The output MSI dataset is stored in rMSI format (TAR) and the peak matrix is stored in a format readable by rMSIproc. rMSIproc complements the previously released rMSI package. The rMSI package was designed to allow efficient access to large MSI datasets combined with a data visualization graphical user interface (GUI). rMSIproc takes advantage of the rMSI data handling strategy and adds a full data pre-processing pipeline designed to extract relevant m/z features from large datasets. rMSIproc’s internal processing is implemented in C++ to provide efficient memory management and highly optimized multi-threading execution. However, all the user-relevant methods are exposed as R functions following the classical structure of an R package. The package also provides a graphical user interface (GUI) to facilitate setting up the MS processing parameters.
rMSIproc needs the rMSI package to access MS data. Before installing rMSIproc, be sure to have rMSI properly installed. Please, check out rMSI github page for instructions of rMSI installation: https://github.com/prafols/rMSI. For Linux platform, you’ll need to install the fftw library using your distribution package manager. For Windows systems, the fft library is provided as re-distributable binaries inside the rMSIproc package, so no extra step is needed. To install rMSIproc you can use the devtools package to fetch it directly from github:
> devtools::install_github("prafols/rMSIproc", ref = "0.3.1")The simplest way to use rMSIproc is by using its GUI. Just run the following command to run it:
> rMSIproc::ProcessWizard()A window will appear where you can set up all the processing parameters, the input data and the output directory to store the results. When the processing finishes, use rMSIproc to load a peak matrix in to your R session.
> myPeakMat <- rMSIproc::LoadPeakMatrix("/path/to/your/peakmatrix.zip")A more detailed tutorial that describes basic R, rMSI and rMSIproc usage is available in pdf at the following link: https://github.com/prafols/rMSIproc/blob/master/tutorial/rMSI_rMSIproc_tutorial.pdf