Struct: an R/bioconductor-based framework for standardised metabolomics data analysis and beyond

Research output: Contribution to journalArticlepeer-review

Authors

Colleges, School and Institutes

Abstract

MOTIVATION: Implementing and combining methods from a diverse range of R/Bioconductor packages into 'omics' data analysis workflows represents a significant challenge in terms of standardisation, readability and reproducibility. Here we present an R/Bioconductor package, named struct (Statistics in R using Class-based Templates), which defines a suite of class-based templates that allows users to develop and implement highly standardised and readable statistical analysis workflows. Struct integrates with the STATistics Ontology (STATO) in order to ensure consistent reporting and maximises semantic interoperability. We also present a toolbox, named structToolbox, which includes an extensive set of commonly used data analysis methods that have been implemented using struct. This toolbox can be used to build data-analysis workflows for metabolomics and other omics technologies.

AVAILABILITY AND IMPLEMENTATION: struct and structToolbox are implemented in R, and are freely available from Bioconductor (http://bioconductor.org/packages/struct and http://bioconductor.org/packages/structToolbox), including documentation and vignettes. Source code is available and maintained at https://github.com/computational-metabolomics.

Details

Original languageEnglish
Pages (from-to)5551–5552
JournalBioinformatics
Volume36
Issue number22-23
Early online date27 Dec 2020
Publication statusPublished - Dec 2020