In biochemical analysis, high-throughput mass spectrometry has been widely adopted for various metabolite analyses. However, despite the availability of numerous advanced metabolomics data visualisation tools and reporting methods, extracting meaningful insights from extensive and complex datasets within intricate biological systems remains a significant challenge, especially for practitioners without specialised metabolomics expertise.
To tackle the challenge, we are excited to introduce "MAD.VB" a robust software solution developed in-house by Metabolomics Australia UoM Node. “MAD.VB” is fully customizable, expandable, and interactive, designed specifically to analyse polar metabolites across not only gas and liquid chromatography platforms but also lipidomics.
The design philosophy of the software focuses on seamlessly integrating outputs from various metabolomics tools and databases, such as MetaboAnalyst and HMDB, into a streamlined and automated workflow. This can be performed independently via its graphical user interface or alongside other established bioinformatics workflow tools, such as NextFlow and CWL. The software can generate comprehensive summary reports featuring user-friendly, interactive visualisations, which are easily accessible on web pages. This allows analysts to navigate complex datasets effortlessly using intuitive drag-and-click interactions.
The resulting reports are highly customisable for advanced users, with built-in modules that can be enabled or modules tailored to their specific goals that can be created and plugged in following protocols. Additionally, we have developed comprehensive algorithms that combine statistical analyses with biological insights, allowing users to visually identify metabolites exhibiting differential behaviours across various experimental groups while providing deeper insights into biological pathways.
Understanding the importance of collaboration, we have ensured that sharing output reports with stakeholders is easy. Users can package their reports into Zip-Archive or configure them as Git-Page. This feature promotes accessibility through widely used platforms like GitHub and GitLab, ensuring critical findings can be effectively communicated and disseminated within the scientific community.