structToolbox (original) (raw)

This is the released version of structToolbox; for the devel version, seestructToolbox.

Data processing & analysis tools for Metabolomics and other omics

Bioconductor version: Release (3.20)

An extensive set of data (pre-)processing and analysis methods and tools for metabolomics and other omics, with a strong emphasis on statistics and machine learning. This toolbox allows the user to build extensive and standardised workflows for data analysis. The methods and tools have been implemented using class-based templates provided by the struct (Statistics in R Using Class-based Templates) package. The toolbox includes pre-processing methods (e.g. signal drift and batch correction, normalisation, missing value imputation and scaling), univariate (e.g. ttest, various forms of ANOVA, Kruskal–Wallis test and more) and multivariate statistical methods (e.g. PCA and PLS, including cross-validation and permutation testing) as well as machine learning methods (e.g. Support Vector Machines). The STATistics Ontology (STATO) has been integrated and implemented to provide standardised definitions for the different methods, inputs and outputs.

Author: Gavin Rhys Lloyd [aut, cre] , Ralf Johannes Maria Weber [aut]

Maintainer: Gavin Rhys Lloyd <g.r.lloyd at bham.ac.uk>

Citation (from within R, enter citation("structToolbox")):

Installation

To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("structToolbox")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("structToolbox")

Details

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Package Archives

Follow Installation instructions to use this package in your R session.