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PCA Analysis

This intuitive tool allows you to easily investigate and visualize data to answer basic research questions and can serve as a starting point for your research. Quickly identify metabolite-driven sample groups and overlay sample meta data to uncover relationships to phenotypes.

PLS-DA

PLS-DA excels at performing simultaneous dimensionality reduction and classification, allowing researchers to discern patterns associated with different experimental conditions or sample classes. This method is particularly beneficial for identifying biomarkers, distinguishing between physiological states, and predicting class membership for new samples based on their metabolite profiles.

Volcano Plot

The Volcano plot tool is a powerful visualization tool that combines statistical significance with the magnitude of change in metabolite levels to highlight the most biologically relevant metabolites in your study.

Clustering

Hierarchical clustering can identify natural groupings within metabolomic datasets by organizing samples or metabolites based on similarity, revealing underlying patterns or distinct biological phenotypes. By visualizing these clusters in dendrograms, you can intuitively interpret metabolic relationships and pinpoint specific biomarkers or metabolic pathways of interest.

Pathway Analysis

This intuitive tool allows you to easily investigate and visualize data to answer basic research questions and can serve as a starting point for your research. Quickly identify metabolite-driven sample groups and overlay sample meta data to uncover relationships to phenotypes.

Biomarker Lenses®

Biomarker Lenses® in Metabolon’s Bioinformatics Platform are tools that enhance the exploration of metabolomic data by parsing the data into more digestible pieces. Biomarker Lenses™ accomplishes this by grouping the metabolites associated with specific biological functions, pathways, or diseases, thus allowing users to focus on the most relevant areas of biology in the context of their study.

Statistics

Statistics included within Metabolon’s Integrated Bioinformatics Platform provide additional utility and control for exploring and interpreting your data. As your research grows, the statistics tool supports further hypothesis testing and analyses using key features such as outlier removal and modifying metadata and enables researchers to run additional statistical tests such as T-tests and ANOVAs, all following an easy, step-by-step process.

Multiomics

This tool allows researchers to upload, process, and analyze multiomics data and when combined with Metabolomics data offers the most complete understanding of the phenotype available.

With multiomic predictive modelling, latent factor analysis, and pathway enrichment using REACTOME, the Multiomics Tool enables users to efficiently explore relationships across different omics layers, identify key biomarkers, and rank pathway-level signals within their datasets.

Microbiome Analysis Tool

Hierarchical clustering can identify natural groupings within metabolomic datasets by organizing samples or metabolites based on similarity, revealing underlying patterns or distinct biological phenotypes. By visualizing these clusters in dendrograms, you can intuitively interpret metabolic relationships and pinpoint specific biomarkers or metabolic pathways of interest.