v2.1.0.

MetaProViz: METabolomics pre-PRocessing, functiOnal analysis and VIZualisation
This is the second package release V2.1.0. where we did:

• Updated Viz helper functions to work with the latest ggplot2 update, which affected the grid parameter adaptation
• Added Metadata analysis options and a vignette explaining these functionalities
• Added more prior knowledge options and and ID translation function to work with different ID types. There is also a new vignette for this.
• Updated the overview figure and description for MetaProViz
• Added log files

MetaProViz can analyse standard metabolomics and exometabolomics data (CoRe). It performs pre-processing including feature filtering, missing value imputation, normalisation and outlier detection. It perform functional analysis including differential metabolite analysis (DMA), clustering based on regulatory rules (MCA) and contains different visualisation methods to extract biological interpretable graphs and saves them in a publication ready format.

v2.0.2

MetaProViz: METabolomics pre-PRocessing, functiOnal analysis and VIZualisation
This is the second package release V2.0.2. where we did:

1. Added VizSuperplot function and example into vignettes
2. Updated the overview figure and description for MetaProViz
3. Made some smaller changes in VizPCA, VizVolcano helper function VizVolcano_PEA

MetaProViz can analyse standard metabolomics and exometabolomics data (CoRe). It performs pre-processing including feature filtering, missing value imputation, normalisation and outlier detection. It perform functional analysis including differential metabolite analysis (DMA), clustering based on regulatory rules (MCA) and contains different visualisation methods to extract biological interpretable graphs and saves them in a publication ready format.

MetaProViz v2.0.1

MetaProViz: METabolomics pre-PRocessing, functiOnal analysis and VIZualisation

This is the second package release V2.0.1. where we did:

• PoolEstimation: PCA plots are now saved
• PreProcessing: For CoRe data where all blank samples of a feature are NA/0, MVI is not performed but true 0 is considered.

MetaProViz can analyse standard metabolomics and exometabolomics data (CoRe). It performs pre-processing including feature filtering, missing value imputation, normalisation and outlier detection. It perform functional analysis including differential metabolite analysis (DMA), clustering based on regulatory rules (MCA) and contains different visualisation methods to extract biological interpretable graphs and saves them in a publication ready format.

MetaProViz v2.0.0

MetaProViz: METabolomics pre-PRocessing, functiOnal analysis and VIZualisation

This is the second package release V2.0.0. where we did:

1. Parameter syntax update to make the usage more intuitive and allow the user to pass any column names
2. Implementation of helper functions to ensure coherent input data checks and saving of figures and tables
3. Creating helper functions for main functions to ensure easier trouble shooting or debugging.
4. Addition of HMDB IDs to the Metadata

MetaProViz can analyse standard metabolomics and exometabolomics data (CoRe). It performs pre-processing including feature filtering, missing value imputation, normalisation and outlier detection. It perform functional analysis including differential metabolite analysis (DMA), clustering based on regulatory rules (MCA) and contains different visualisation methods to extract biological interpretable graphs and saves them in a publication ready format.

MetaProViz v1.0.1

MetaProViz: METabolomics pre-PRocessing, functiOnal analysis and VIZualisation

This is the first package release V1.0.1. where we made a small change to the DMA helper functions to enablke other column names for "Conditions" in Input_SettingsFile_Sample.

MetaProViz can analyse standard metabolomics and exometabolomics data (CoRe). It performs pre-processing including feature filtering, missing value imputation, normalisation and outlier detection. It perform functional analysis including differential metabolite analysis (DMA), clustering based on regulatory rules (MCA) and contains different visualisation methods to extract biological interpretable graphs and saves them in a publication ready format.

MetaProViz v1.0.0

MetaProViz: METabolomics pre-PRocessing, functiOnal analysis and VIZualisation

This is the first package release V1.0.0.

MetaProViz can analyse standard metabolomics and exometabolomics data (CoRe). It performs pre-processing including feature filtering, missing value imputation, normalisation and outlier detection. It perform functional analysis including differential metabolite analysis (DMA), clustering based on regulatory rules (MCA) and contains different visualisation methods to extract biological interpretable graphs and saves them in a publication ready format.