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,
Kruskalâ€“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.

To install this package:

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

To install the development version:

```
if (!require("remotes", quietly = TRUE))
install.packages("remotes")
remotes::install_github("computational-metabolomics/structToolbox")
```

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