v.3.99.1

MetaProViz: METabolomics pre-PRocessing, functiOnal analysis and VIZualisation
This is a small package release V3.99.1. where we added:

• BioC timeout was fixed
• code refactoring for BioC checks

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.

v.3.99.0

MetaProViz: METabolomics pre-PRocessing, functiOnal analysis and VIZualisation
This is a small package release V3.99.0. where we added:

In this release we:

• general refactoring to meet Bioconductor checks
• general refactoring for RCMD checks
• general refactoring of the github actions

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.

v3.0.3

MetaProViz: METabolomics pre-PRocessing, functiOnal analysis and VIZualisation
This is a small package release V3.0.3. where we added:

In this release we:

• Made changes in the processing function to enable= passing of any column name not only "Condition"
• Fixed a bug in the MVI part of the processing function, which would lead to errors in the missing value imputation function, when samples are not naturally ordered alphabetically as it changes the sample order.
• Updated the links in the readme to the vignette 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.

v3.0.2

MetaProViz: METabolomics pre-PRocessing, functiOnal analysis and VIZualisation
This is a small package release V3.0.2. where we added:

In this release we:

1. Extended the sample-metadata vignette
2. Revamped the prior knowledge vignette part for matching prior knowledge with data for clarity.

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.

v3.0.1

MetaProViz: METabolomics pre-PRocessing, functiOnal analysis and VIZualisation
This is a small package release V3.0.1. where we added:

In this release we increase the major version since many parameters and functios have been renamed for a cleaner and more uniform API.

• We extended the prior knwoledge vignette to showcase more pittfalls and how to deal with them.
• We have extended the documentation and removed some dependencies.
• We have also extended the CoRe and Standard vignette, and updated the overview figures.
• We have removed loading via ToyData and made the built in data to comply the R-packages book guidelines
• We have renamed functions to follow snake case names
• We have renamed parameters to follow snake case names

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.

v2.1.7

MetaProViz: METabolomics pre-PRocessing, functiOnal analysis and VIZualisation
This is a small package release V2.1.7. where we added:

• We extended the prior knwoledge vignette to showcase more pittfalls and how to deal with them.
• We have extended the documentation and removed some dependencies.
• We have also extended the CoRe and Standard vignette, and updated the overview figures.
• We have added more example data.

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.

v2.1.6.

MetaProViz: METabolomics pre-PRocessing, functiOnal analysis and VIZualisation
This is a small package release V2.1.6. where we added:

• Bug Fix in MetaProViz::DMA() for CoRe=FALSE.

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.

v2.1.5

MetaProViz: METabolomics pre-PRocessing, functiOnal analysis and VIZualisation
This is a small package release V2.1.4. where we added:

• Some issues were fixed (user requests and bugs)
• Added new function for CheckIDMatch.

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.

v2.1.4

MetaProViz: METabolomics pre-PRocessing, functiOnal analysis and VIZualisation
This is a small package release V2.1.4. where we added:

• New prior knowledge for enrichment analysis such as chemical classes for chemical class enrichment or pathways from gaude et al.
• New example data (proteomics and transcriptomics from ccRCC patients)

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.

v2.1.3

MetaProViz: METabolomics pre-PRocessing, functiOnal analysis and VIZualisation
This is a small package release V2.1.3. where we did:

• Updated parameter description and dependencies
• Updated translateID function and added MappingAmbiguity
• Fixed some small issues in PreProcessing() (e.g. plots were not all saved)

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.