A Modular and Expandable Ecosystem for Metabolomics Data Annotation in R

Abstract

Liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics experiments have become increasingly popular because of the wide range of metabolites that can be analyzed and the possibility to measure novel compounds. LC-MS instrumentation and analysis conditions can differ substantially among laboratories and experiments, thus resulting in non-standardized datasets demanding customized annotation workflows. We present an ecosystem of R packages, centered around the MetaboCoreUtils, MetaboAnnotation and CompoundDb packages that together provide a modular infrastructure for the annotation of untargeted metabolomics data. Initial annotation can be performed based on MS1 properties such as m/z and retention times, followed by an MS2-based annotation in which experimental fragment spectra are compared against a reference library. Such reference databases can be created and managed with the CompoundDb package. The ecosystem supports data from a variety of formats, including, but not limited to, MSP, MGF, mzML, mzXML, netCDF as well as MassBank text files and SQL databases. Through its highly customizable functionality, the presented infrastructure allows to build reproducible annotation workflows tailored for and adapted to most untargeted LC-MS-based datasets. All core functionality, which supports base R data types, is exported, also facilitating its re-use in other R packages. Finally, all packages are thoroughly unit-tested and documented and are available on GitHub and through Bioconductor.

TidyMass an object-oriented reproducible analysis framework for LC–MS data

“…For example, all the functions used for metabolite annotation were combined as one package metID 24 in tidyMass. The modular architecture makes tidyMass flexible and extensible, which is popular for R package design 23,25 . Users can choose either package from tidyMass according to their own pipeline.…”

“…The "SummarizedExperiment" class in the Summar-izedExperiment package presents a popular data structure for multiple omics data analysis packages in the R environment, especially for RNA-seq data analysis tools 29 . Some R packages developed for metabolomics also support this data structure, such as the "MetaboAnnotation" package (metabolite annotation) from the RforMassSpectrometry project 23 . So users can convert from the "mass_dataset" class to the "SummarizedExperiment" class and then annotate metabolites using the "MetaboAnnotation" package.…”

“…3). The modular design makes it easy for the user to find appropriate functions, and for developers to debug and extend it 23 . Briefly, the workflow begins from the package massConverter, which converts MS raw data from different vendors to other formats (Fig.…”

TidyMass: An Object-oriented Reproducible Analysis Framework for LC-MS Data

“…TidyMass project is an ecosystem of R packages that share an underlying design philosophy, grammar, and data structure, which utilizes the concept of tidyverse 19 . To address the challenges of data sharing, reproducible analysis, and extensibility, we adopted the object-oriented and modular design concepts, which are also leveraged by other tools 7,14 .…”

“…2 ). The modular design makes it easy for the user to find appropriate functions, and for developers to debug and extend it 7 . Briefly, the workflow begins from the package massConverter, which converts MS raw data from different vendors to other formats ( Fig.…”