Struct: an R/bioconductor-based framework for standardised metabolomics data analysis and beyond
Research output: Contribution to journal › Article › peer-review
Colleges, School and Institutes
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.
|Early online date||27 Dec 2020|
|Publication status||Published - Dec 2020|