Demo our Data Analysis Tools

Principal Component Analysis (PCA)

The PCA tool is a valuable tool for exploring and interpreting complex metabolomics datasets, aiding in the identification of biologically relevant markers and the understanding of metabolic mechanisms. This intuitive tool allows you to easily investigate and visualize data to answer basic research questions and can serve as a starting point for researchers. The PCA tool offers customizable features to meet your needs and allows you to be autonomous in investigating data in line with your research goals. With this tool, you have holistic control to better interpret and form hypotheses of the metabolomic profile from the study groups and identify patterns or metabolites of interest from the visualization and data exports.

Partial Least-Squares Discriminant Analysis (PLS-DA)

PLS-DA plays a pivotal role in metabolomics analysis, providing a powerful statistical framework for unraveling complex relationships within high-dimensional datasets. PLS-DA is a supervised dimensionality reduction method that, unlike PCA, incorporates class labels in the analysis. It discovers latent variables (components) that maximize the separation between different predefined groups (e.g., healthy vs diseased) in the data. By projecting the data onto these latent variables, PLS-DA captures the variance and correlation structure in the data most relevant to group differentiation. Given its supervised nature, PLS-DA requires careful parameterization and an understanding of the underlying data.

Volcano Plot

The volcano plot 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. Metabolon’s volcano plot allows you to download high-resolution graphics that are publication-ready and offers customizable features to meet your specific needs.

Clustering Analysis

Clustering is a staple method in the field of data analytics and bioinformatics, used for grouping entities based on their similarities. This technique is crucial in revealing the inherent structures within data, often leading to insightful discoveries in various scientific domains. Grasping the nuances of clustering can significantly enhance your understanding of your data’s hidden patterns and relationships. Our clustering analysis tool intelligently identifies the optimal grouping parameters, enabling easier analysis of complex data.

Pathway Enrichment

Pathway analysis is a powerful tool in bioinformatics and systems biology. It provides context and interpretation of various biological pathways to understand the complex interplay of genes, proteins, metabolites, and other molecular entities. By analyzing these pathways, researchers can uncover how different biological processes operate and interact, leading to new insights into disease mechanisms, therapeutic targets, and more. In essence, pathway analysis in metabolomics is indispensable for extracting meaningful biological knowledge from intricate metabolite networks, contributing to advancements in both basic science and translational research.

Biomarker Lenses™

The Biomarker Lenses™ tool applies advanced analytical filters that enhance the exploration of metabolomic data by focusing on metabolites associated with specific biological functions, pathways, or diseases. The filters act as a magnifying glass, highlighting relevant subsets of data for in-depth analysis. The approach allows you to sift through the vast array of metabolites and concentrate on those that are pertinent to a particular biological inquiry. There are three types of Biomarker Lenses™ available in Metabolon’s Bioinformatics Platform: Pathway Biomarker Lenses™, Disease Biomarker Lenses™, and Custom Biomarker Lenses™.

Statistics

The Statistics tools in Metabolon’s Integrated Bioinformatics Platform provide additional utility and control for exploring and interpreting your data. The tools let researchers build and compare different statistical models, manage metadata and sample data, and remove outliers to identify new data insights. The new statistics tools help uncover insights that may be masked by outliers, ensuring that your analyses are accurate and aligned with your research goals. Everything is seamlessly integrated with other visualization tools within the Integrated Bioinformatics Platform.

The Discovery Panel Report

Within the Discovery Panel Report, you can visualize all detected metabolites in a bubble plot. You can select statistical comparisons, adjust the p-value, flip the fold change, and search for a metabolite of interest from the toolbar at the top. You can also explore the significantly up- and- down-regulated metabolites. Within the bubble plot, quickly identify metabolites of significance and click those metabolites to learn more. The user can also download an image of the bubble plot repurposed for redistribution outside the MyMetabolon portal.

Impact Explorer

Impact Explorer is the next step in diving deeper into your Discovery Panel data. Select up to six statistical comparisons to view within the heliogram visualization, which is a reimagining of a heatmap of metabolite fold changes grouped by pathway and organized in a circular view. You can click on specific metabolites or associations and view the relationship between the groups. Additionally, you can download an image file for any view you find interesting in the heliogram.

Metabolite Profile Finder

The Metabolite Profile Finder can be used to explore a specific metabolite or pathway of interest. Both can be accessed by clicking the Profile Finder tab, or by navigating from the Discovery Panel Report tab. In the Metabolite Profile Finder, you can see an overview of the metabolite of interest. This page includes links to PubChem, KEGG, and HMDB for further education. You can also view how that metabolite was statistically represented in each of the study comparisons. Finally, you can also see the associations linked to a given metabolite.