Table 2.

List of useful R/ Bioconductor packages that surfaced/ were improved in 2020

CRAN package name	Title	Description	Link
lilikoi	Metabolomics personalized pathway analysis tool	Helps map metabolites data into pathways and calculates pathway deregulation scores, and enables perform exploratory analysis, classification and prognosis analysis on both metabolites and pathways	https://cran.r-project.org/web/packages/lilikoi/index.html
omu	A metabolomics analysis tool for intuitive figures and convenient metadata collection	Helps generate intuitive figures for metabolomics data by using Kyoto Encyclopaedia of Genes and Genomes (KEGG) hierarchy data, and gathers functional orthology and gene data using the package 'KEGGREST' to access the 'KEGG' API	https://cran.r-project.org/web/packages/omu/index.html
eRah	Automated spectral deconvolution, alignment, and metabolite identification in GC/MS-based untargeted metabolomics	Updated to 2016 published tool eRah, that aids in automated compound deconvolution, alignment across samples, and identification of metabolites by spectral library matching in untargeted GC–MS metabolomics workflows	https://cran.r-project.org/web/packages/erah/index.html
MetaDBparse	Annotate mass over charge values with databases and formula prediction	Useful for parsing functionality for over 30 metabolomics databases, and calculates given adducts and isotope patterns and inserts into one big database which can be used to annotate unknown m/z values	https://cran.r-project.org/web/packages/MetaDBparse/index.html
MetaClean	Detection of low-quality peaks in untargeted metabolomics data	Uses 11 peak quality metrics and eight diverse machine learning algorithms to build a classifier for the automatic assessment of peak integration quality of peaks from untargeted metabolomics analyses	https://cran.r-project.org/web/packages/MetaClean/index.html
tmod	Feature set enrichment analysis for metabolomics and transcriptomics	Feature or gene set enrichment analysis in transcriptomics and metabolomics data and the allows enrichment based on ranked list of features, visualization and multivariate data analysis	https://cran.r-project.org/web/packages/tmod/index.html
ccmn	CCMN and other normalization methods for metabolomics data	Allows implementation of Cross-contribution Compensating Multiple standard Normalization (CCMN) method	https://cran.r-project.org/web/packages/crmn/index.html
LipidMS	Lipid annotation for LC–MS/MS DIA data	Aids in annotation of lipids in untargeted LC-DIA-MS lipidomics data based on fragmentation rules	https://cran.r-project.org/web/packages/LipidMS/index.html
enviGCMS	GC/LC–ms data analysis for environmental science	For environmental mass spectrometry (GC/LC-MS) data analysis for molecular isotope ratio, matrix effects and short-chain chlorinated paraffins analysis etc	https://cran.r-project.org/web/packages/enviGCMS/index.html
nontarget	Detecting isotope, adduct and homologue relations in LC–MS data	Allows screening of HRMS data set for peaks related by (1) isotope patterns, (2) different adducts of the same molecule and/or (3) homologue series; thus yielding isotopic pattern and adduct groups called 'components' with homologue series information. Further plotting, filtering of MS data for mass defects etc. are facilitated	https://cran.r-project.org/web/packages/nontarget/index.html
mosaic.find	Finding rhythmic and non-rhythmic trends in multi-omics data (MOSAIC)	MOSAIC (Multi-Omics Selection with Amplitude Independent Criteria) provides a function (mosaic_find()) designed to find rhythmic and non-rhythmic trends in multi-omics time course data using model selection and joint modelling	https://cran.r-project.org/web/packages/mosaic.find/index.html
ActivePathways	Integrative pathway enrichment analysis of multivariate omics data	A framework for analysing multiple omics datasets in the context of molecular pathways, biological processes and other types of gene sets. The tool uses p-value merging to combine gene- or protein-level signals, followed by ranked hypergeometric tests to determine enriched pathways and processes	https://cran.r-project.org/web/packages/ActivePathways/index.html
wilson	Web-based interactive omics visualization	Provides modules for creating web-based applications that use plot-based strategies to visualize and analyse multi-omics data	https://cran.r-project.org/web/packages/wilson/index.html
mixKernel	Omics data integration using kernel methods	The package aims at providing methods to combine kernel for unsupervised exploratory analysis, that can help integration of heterogenous types of data	https://cran.r-project.org/web/packages/mixKernel/index.html