MagmaFlow_v10.0.4: MagmaFlow An Integrated Desktop Platform for Differential Expression Interpretation Through AI-Powered Literature Annotation and Pathway Network Analysis

MagmaFlow An Integrated Desktop Platform for Differential Expression Interpretation ThroughAI-Powered Literature Annotation and Pathway Network Analysis Overview MagmaFlow is a cross-platform desktop application combining interactive volcano plot visualization with automated annotation, integrated literature mining, and pathway-level contextual analysis. The platform retrieves relevant PubMed references, pathway memberships, and disease associations directly within an interactive visualization environment, enabling efficient, reproducible, and publication-ready analysis of transcriptomic datasets. MagmaFlow transforms volcano plot analysis from static display into dynamic biological interpretation, representing the first tool integrating AI-powered literature contextualization with enrichment analysis to convert differential expression data into actionable insights. Key Features Interactive Visualization Feature Description Double-Click Gene Selection Instantly add/remove target genes by double-clicking data points Drag & Drop Labels Reposition gene annotations with collision avoidance for publication-ready figures Smart Edge Connections Five layout modes (Auto, Left, Right, Center, Smart) to reduce overlap Advanced Zoom & Pan SHIFT+drag panning, mouse wheel zooming, one-click fit-to-viewport Real-time Hover Tooltips Live gene details displaying name, log₂FC, p-value, and adjusted p-value Target Gene Management Feature Description Checkbox Control Synchronized checkboxes for real-time activation/deactivation of annotations File Import Load target gene lists from text files Manual Entry Type or paste gene names with smart parsing Smart Positioning Auto-prevent label overlaps with intelligent spacing Color Systems Style Description Gurzov Classic Traditional blue/red coloring for down/up-regulated genes MagmaFlow Classic 1 P-value based gradients MagmaFlow Classic 2 Log₂ fold change based gradients MagmaFlow Classic 3 Combined p-value and fold change gradients Viridis & Magma Perceptually uniform, color-blind-friendly scientific palettes Custom Color Pickers Direct RGB/Hex color refinement with adjustable outlines and transparency Precision Customization Feature Description Independent Font Controls Separate sizes for title, axes, ticks, and annotations Dynamic Thresholds Real-time p-value and log₂FC cutoff adjustment Smart Tick Spacing Auto or manual axis intervals for perfect scaling Advanced Dot Styling Opacity, outlines, sizes with live preview Publication Export High-resolution PNG (72–1200 DPI) with scalable off-screen rendering Project Workflow Feature Description Smart CSV Import Automatic detection of standard columns via regular expressions; manual mapping dialog for non-standard headers Complete Project Files JSON format preserving gene data, thresholds, annotations, label positions, and display preferences Auto-save Tracking Visual indicators for unsaved changes to prevent data loss Session Persistence Remember your work across application restarts R Integration Feature Description MagmaFlowR Package Companion R package for integration with DESeq2, edgeR, limma, and Seurat pipelines mag_landragem() Launch MagmaFlow GUI and preload expression data directly from R environment Repository github.com/carlosbuss1/magmaflowR Literature Mining Module Feature Description PubTator3 Integration AI-powered named entity recognition across 36 million PubMed abstracts and 6 million PMC full-text articles Dynamic Context Definition Autocomplete for Disease/Condition (required) and Treatment/Chemical (optional) with validated MeSH identifiers Relation Types Configuration Positive/negative correlation, stimulation, inhibition, or general association to match expression patterns Dual-API Strategy PubTator3 Relations API for Total and Context papers; NCBI E-utilities for Recent papers and PMIDs Disease Synonym Expansion Automatic inclusion of abbreviations and related terms for disease-specific searches Log-Scaled Scoring Composite score (2×log(1+Total) + 8×log(1+Context) + 5×log(1+Recent) + StatsBonus) preventing highly-studied genes from dominating Clickable PMID Links Direct access to publications sorted by date (newest first) Pathway Enrichment and Circle Plot Visualization Feature Description Enrichr API Integration Over-Representation Analysis across seven pathway databases Supported Databases Gene Ontology 2023 (BP, MF, CC), KEGG 2021, Reactome 2022, WikiPathways 2023, MSigDB Hallmark 2025 Species Support Human, Mouse, and Cow (Bos taurus, GO only) Analysis Modes All significant genes combined, or separate up/down-regulated analyses Circle Plot Visualization Multi-layer circular diagrams with pathway enrichment, gene expression, and database annotations Cross-Pathway Detection Curved lines connecting genes appearing in multiple pathways reveal functional relationships Bidirectional Workflow Pathway discovery informs gene prioritization; volcano visualization contextualizes shared pathway genes All Releases Visit our Zenodo repository for all versions and additional files. Note: MagmaFlow is distributed as a pre-built application only. Source code is not publicly available. System Requirements Specification Minimum Recommended (>30,000 genes) RAM 4 GB 8 GB Display 1280 × 720 Full HD (1920 × 1080) Platform macOS, Windows macOS, Windows Installation Step Action 1 Download the DMG (MacOs) or EXE (windows) file from the link above 2 Open the DMG and drag MagmaFlow to Applications for Mac. Doble-click in EXE in Windows system. 3 Launch MagmaFlow from Applications folder Technical Implementation Component Technology Framework JavaFX 17.0.2 Compiler JDK 17 (LTS) Architecture Model-View-Controller (MVC) Rendering JavaFX Canvas API with GPU-accelerated GraphicsContext Precision Double-precision floating-point arithmetic External API Integration API Purpose Endpoint PubTator3 AI-powered named entity recognition https://www.ncbi.nlm.nih.gov/research/pubtator3-api NCBI E-utilities Date-filtered publication queries https://eutils.ncbi.nlm.nih.gov/entrez/eutils/ Enrichr Over-Representation Analysis https://maayanlab.cloud/Enrichr/ License MagmaFlow Academic Binary – End-User License Agreement (EULA) Version Jan-2026 By downloading, installing, or using the MagmaFlow executable (the "Software") you ("Licensee") agree to the terms of this EULA with the Université libre de Bruxelles, Avenue F. Roosevelt 50, B-1050 Brussels, Belgium ("ULB"), which owns all intellectual-property rights in the Software. Definitions Term Definition Executable / Software The compiled distribution of MagmaFlow (DMG, MSI, JAR or similar) provided by ULB Academic Use Use by accredited higher-education or publicly funded research bodies, for teaching, research, or other not-for-profit scholarly purposes Non-Commercial Any activity not primarily intended for commercial gain and not carried out for the benefit of a for-profit entity License Grant Subject to this EULA, ULB grants Licensee a non-exclusive, non-transferable, royalty-free licence to download, install, and run the Software solely for Academic and Non-Commercial purposes. No right to sublicense is granted. Restrictions Licensee shall not: Use the Software for any Commercial purpose without prior written consent from ULB Modify, adapt, translate, or create derivative works of the Software Reverse-engineer, decompile, or disassemble the Software except as permitted by applicable law Offer the Software to third parties as a hosted or cloud service (SaaS) or otherwise provide remote access Publish the Software or this EULA on public repositories, websites, or mirrors Warranty Disclaimer ULB provides the Software "as is" and disclaims all warranties, express or implied, including the warranties of merchantability, fitness for a particular purpose, and non-infringement. Governing Law This EULA is governed by Belgian law. Any dispute arising under it shall be submitted to the exclusive jurisdiction of the courts of Brussels. For Commercial licensing inquiries: [email protected] Citation If you use MagmaFlow in your research, please cite: Buss, C. E. (2026). MagmaFlow_v10.0.4: MagmaFlow An Integrated Desktop Platform for Differential Expression Interpretation Through AI-Powered Literature Annotation and Pathway Network Analysis (v10.0.4). Zenodo. https://doi.org/10.5281/zenodo.18380556 Contact Purpose Contact Questions & Bug Reports Open an issue on GitHub Commercial Licensing [email protected]