Mass Dynamics

Mass Dynamics is a cloud-based proteomics data processing and analysis platform designed for researchers working with mass spectrometry (MS) data. It supports workflows aimed at discovering biological biomarkers, identifying changes in protein levels, uncovering disease mechanisms, and finding new drug targets from carefully designed experiments.

The platform is built around an automated, repeatable proteomics workflow that accepts raw MS files or pre-processed data as input. It supports Label-Free Quantitative (LFQ-DDA) and Tandem Mass Tag (TMT) methods, and offloads heavy computational processing to the cloud to allow experiments to be processed and analysed at scale.

Core Workflow Capabilities

• Accepts raw input files or pre-processed data, giving users flexibility in how they enter the workflow.
• Supports LFQ-DDA and TMT quantification methods.
• Scales to handle large experiments by pushing computationally intensive processing to the cloud.
• Applies machine learning and unbiased MS1 data extraction for every detected feature to reduce missing values, maximise data completeness, and provide a measure of feature confidence.
• Provides quality control graphics covering overall experiment health, feature quality, and data completeness.
• Accessible from any location via the cloud, enabling analysis outside of the laboratory environment.

Analysis Modules

Mass Dynamics uses a modular workspace structure where individual visualisation and analysis components, called analysis modules, can be selected, dragged into a workspace, repositioned, and resized. Available modules include:

• Experiment Design: A table listing groupings of conditions and filenames.
• Volcano Plot: A plot for exploring pairwise differential expression analysis.
• List Table: A table listing selected proteins, associated genes, and descriptions.
• Data Table: A table showing differences between conditions, including associated genes, descriptions, log2 ratios, p-values, and adjusted p-values.
• Violin Plot: Shows the probability density distribution of intensities of selected proteins by condition.
• Dot Plot: Shows the distribution of intensities of selected proteins by condition.
• Reactome ORA Table: Lists potentially over-represented pathways including estimated False Discovery Rate (FDR) and number of associated proteins.
• Reactome ORA Strip: A scatter plot of potentially over-represented pathways ordered by -log10 estimated FDR.
• Reactome ORA Bar: A bar plot showing the top n potentially over-represented pathways ordered by -log10 estimated FDR.
• GSEA Volcano Plot: Explores pairwise Gene Set Enrichment Analysis (GSEA) results using the CAMERA method, including average fold change and statistical confidence metrics.
• GSEA List Table: Lists selected enriched gene sets.
• GSEA Results Table: Lists full GSEA results using the CAMERA method.
• Upset Plot: Shows intersections of elements across user-defined protein lists.
• Intensity Heatmap: Displays log2 intensities (original or imputed) of selected proteins across selected runs.
• Correlation Heatmap: A symmetric matrix showing protein-protein Pearson's correlations using log2 intensities (original or imputed) of selected proteins.
• Text: Allows users to write and format text to record insights and notes.
• Checklist: Supports writing, formatting, and managing tasks.

Pre-Built Analysis Templates

Mass Dynamics provides pre-defined sets of analysis modules grouped into templates that pre-populate the workspace for common analysis types. Users can add or remove modules from any template. Available templates include:

• Quality Control Report: Helps assess multiple aspects of experiment quality before investing time in results interpretation.
• Upset: Shows set intersections between user-created protein lists.
• Reactome ORA: Combines visualisations and a summary table to perform Over Representation Analysis with user-selected protein lists to identify relevant pathways.
• Gene Set Enrichment Analysis (GSEA): Allows users to run and explore enrichment results using the CAMERA method across pairwise comparisons and knowledge databases.
• Pairwise Analysis: Combines volcano plots, intensity distribution plots, and a protein list table for interactive exploration of differential expression results.
• Heatmap: Combines intensity and correlation heatmaps to visualise protein expression patterns and cluster proteins with similar expression across samples.

Mass Dynamics is designed to support ongoing, iterative experimentation, allowing researchers to build up evidence across multiple experiments over time and communicate biological findings through shared workspaces and analysis outputs.