Getting Started with DATES Platform
Master the standard analytical workflow across all DATES modules — from uploading raw experimental datasets and configuring factor options to executing compute engines, customizing interactive plots, and exporting reports.
Architectural Philosophy
DATES incorporates a modular plugin-driven analysis framework. Each analysis module operates independently with standard input parameters, deterministic analytical pipelines, and clean output formats across scientific domains.
Modular Design
Modules operate as isolated plugins, ensuring deterministic execution and simple extensibility.
High Performance
Optimized statistical algorithms tailored for large-scale data streams and complex analytical queries.
Validated Outputs
Strict structural schema validation on input parameters and structured result exports (Excel, Word, PowerPoint).
1. Dataset Upload Options & File Handling
DATES modules support flexible options for loading experimental datasets into memory:
- Spreadsheet File Upload (.xlsx, .xls, .csv): Drag and drop or browse files directly from your computer. The engine automatically parses header rows, sheet names, and numerical columns.
- Built-in Demo Datasets: Every module provides pre-loaded sample datasets (e.g., Multi-Factor CRD, RCBD, Diallel, Biplot matrices) to allow instant testing and tutorial execution without importing external data.
- Data Preview & Structure Validation: Before running any calculations, inspect loaded rows, check column data types (Categorical Factors vs Quantitative Metrics), and verify missing value handling.
Tip for Tabular Datasets
Ensure your dataset uses tidy long-format layout, where each row represents a single observation unit or plot sample, and each column represents a single factor or metric variable.
2. Module Option Selection & Variable Mapping
Once data is loaded, use the sidebar control panel to map variables and set analytical parameters:
Factor & Metric Selection
Map dataset columns to required roles: Treatment Groups, Replicate Blocks, Baseline Covariates, Parent Lines, or Dependent Quantitative Metrics.
Model Settings
Configure model type (Fixed vs Random Effects), Post-Hoc Mean Separation tests (Tukey, LSD, Duncan), Data Transformations (Log, Square Root, ArcSine), and Alpha significance levels (5% or 1%).
3. Catalyzing Analysis & Computing Engine
Executing calculations in DATES is simple and real-time:
- Click "Run Analysis" / "Catalyze": Triggers the underlying WebAssembly/JS statistical engine to run ANOVA, MANOVA, SVD, or linear regression matrix calculations.
- Real-time Computation: Analyses complete instantly inside your web browser without sending private experimental datasets to remote third-party servers.
- ANOVA & Diagnostic Summary Tables: Displays structured statistical tables, F-test significance stars (* p < 0.05, ** p < 0.01), variance component breakdowns, and model fit indicators.
4. Interactive Plot Customization & Chart Exports
All generated charts (Biplots, Dendrograms, Bar Charts, Scatter Plots, Q-Q Plots, Field Layout Maps) include full customization tools:
Visual Customization Controls
Adjust color palettes, font sizes, point shapes, axis limits, gridlines, legend positions, and marker labels in real time.
Download High-Res Plots
Export publication-ready figures in Vector formats (SVG) or high-DPI Raster formats (PNG, JPEG) suitable for research manuscript submission.
Export Comprehensive Reports
Download structured statistical summary tables and reports formatted for Microsoft Excel (.xlsx), Word (.docx), or presentation slides (.pptx).
How to Use Module User Guides
Each module user guide on this portal includes standardized sections to streamline your data analysis workflow:
- Purpose & Capabilities: High-level summary of analytical methods, statistical models, and capabilities.
- Input Requirements: Tabular dataset requirements, required column structures, and data types.
- Configurable Options & Settings: Statistical parameters, alpha thresholds, factor selections, and model options.
- Statistical Principles (Plain Text): Conceptual mathematical definitions without raw code or complex equation syntax.
- Sample Results & Interpretation: Structured output summary tables with clear guidelines on interpreting statistical output.
- Best Practices & Tips: Key recommendations on data preparation, assumption checking, and avoiding analytical pitfalls.