The high-resolution and mass accuracy of Fourier transform mass spectrometry (FT-MS) has made it an increasingly popular technique for discerning the composition of soil, plant and aquatic samples containing complex mixtures of proteins, carbohydrates, lipids, lignins, hydrocarbons, phytochemicals and other compounds. Thus, there is a growing demand for informatics tools to analyze FT-MS data that will aid investigators seeking to understand the availability of carbon compounds to biotic and abiotic oxidation and to compare fundamental chemical properties of complex samples across groups. We present ftmsRanalysis, an R package which provides an extensive collection of data formatting and processing, filtering, visualization, and sample and group comparison functionalities. The package provides a suite of plotting methods and enables expedient, flexible and interactive visualization of complex datasets through functions which link to a powerful and interactive visualization user interface, Trelliscope. Example analysis using FT-MS data from a soil microbiology study demonstrates the core functionality of the package and highlights the capabilities for producing interactive visualizations.
Author summaryHigh-resolution mass spectrometry instruments provide a mechanism for researchers to better understand the fundamental chemical composition of materials such as soil, plants, petroleum, and beverages. The large and complex data generated by analysis of these materials has led to a growing demand for software tools to aid researchers in processing, analyzing, and creating informative visualizations of these data. To move beyond existing software tools designed for specific purposes and visualizations of data from an individual sample, we present a software package, ftmsRanalysis, that provides researchers with a large collection of methods for streamlining the downstream processing high-resolution mass spectrometry data. ftmsRanalysis provides methods to compute useful chemical properties, filter data, define groups of samples, statistically compare sample groups, and PLOS COMPUTATIONAL BIOLOGY PLOS Computational Biology | https://doi.make visualizations for many samples simultaneously. In this paper, we give an overview of ftmsRanalysis' general structure and capabilities. We then apply ftmsRanalysis to a soil microbiology dataset and present some of the results and visualizations generated by using the software package. This is a PLOS Computational Biology Software paper.