OmicEZ is a lightweight graphical tool designed for rapid visualization of differential expression and omics datasets. The software enables users to generate publication-quality heatmaps and volcano plots through an intuitive graphical interface without requiring programming knowledge. The tool is particularly useful for researchers working with RNA-seq, methylation, proteomics, or other high-throughput omics datasets, where quick exploratory visualization and figure preparation are essential. OmicEZ integrates customizable visualization options, hierarchical clustering, pathway highlighting, and flexible plotting parameters to streamline data interpretation. Key Features 1. Heatmap Visualization OmicEZ supports advanced heatmap generation with multiple customization options. Clustering Options Hierarchical clustering of rows (genes) and/or columns (samples) Multiple clustering linkage methods: Average Single Complete Ward Centroid Visualization Controls Multiple color palettes for data representation Optional square cells for compact figure layout Automatic figure scaling based on number of genes and samples Adjustable clustering options for row and column dendrograms Non-overlapping color legends positioned outside the heatmap Output Publication-ready heatmaps suitable for manuscripts and presentations High-resolution figure export 2. Volcano Plot Visualization The volcano plot module provides a flexible framework for visualizing differential expression results. Statistical Classification Genes are automatically classified into four categories: Category Description Not significant Does not meet p-value or fold-change thresholds P-value significant Significant p-value but fold change below threshold Fold-change significant Fold change above threshold but p-value not significant P-value + Fold-change significant Both thresholds satisfied Each category is represented with a distinct color for clear interpretation. Adjustable Thresholds Users can define: Fold change cutoff P-value significance cutoff These thresholds dynamically update the volcano plot. Gene Highlighting Specific genes can be highlighted by entering gene names. Highlighted genes are visually emphasized for easier interpretation. Pathway Highlighting OmicEZ supports highlighting of genes belonging to specific biological pathways. Features include: Multiple pathway selection Unique marker shapes for each pathway Non-overlapping pathway legends Automatic detection of genes belonging to selected pathways Visual Customization Additional customization options include: Dot shape selection Adjustable plot size External legends for improved readability Enhanced plot layout suitable for publication figures Graphical User Interface (GUI) OmicEZ provides a simple graphical interface built using PyQt, enabling users to perform visualization tasks without writing code. The GUI contains two primary modules: Heatmap Module Options available: Load expression data file Select color palette Enable row clustering Enable column clustering Choose clustering method Enable square heatmap cells Plot heatmap Volcano Module Options available: Load differential expression file Define fold-change threshold Define p-value threshold Select dot shape Highlight specific genes Highlight biological pathways Generate volcano plot Input Data Format Heatmap Input The heatmap module expects a gene expression matrix where rows represent genes and columns represent samples. Example format: Gene Sample1 Sample1 Sample1 GeneA 2.1 3.4 1.8 GeneB 4.3 2.2 3.1 GeneC 1.5 2.7 3.9 Requirements: First column must contain gene names Remaining columns must contain numeric expression values Supported formats: CSV TSV Volcano Plot Input The volcano module expects a differential analysis table with at least three columns. Example format: Gene log2FC pvalue GeneA 2.1 0.001 GeneB -1.5 0.04 GeneC 0.3 0.8 Required columns: Column Description Gene Gene identifier log2FC Log2 fold change pvalue Statistical p-value Typical Workflow Prepare a gene expression or differential expression dataset. Download and unzip the file. Launch OmicEZ.exe by double click. It will open a terminal window and GUI window. (Do not close any window until done) Load the dataset into the appropriate module. Configure visualization parameters. Generate the heatmap or volcano plot. Export the figure for publication or presentation. Intended Use BioViz is designed primarily for: Exploratory omics data analysis Differential expression visualization Figure generation for manuscripts Laboratory data interpretation The tool is optimized for academic research environments. Future Development Potential future enhancements include: Interactive volcano plots with gene hover information Integrated pathway enrichment analysis Multi-omics visualization support Sample annotation tracks for heatmaps Direct integration with RNA-seq analysis pipelines Export to vector graphics formats (PNG/TIFF/SVG/PDF) License This software is intended for academic and research use. Citation If you use BioViz in your research, please cite: OmicEZ: A GUI Tool for Heatmap and Volcano Plot Visualization.Sharma Lab, Johns Hopkins School of Medicine.