BIOSZEN

BIOSZEN enables reproducible analysis and visualization of experimental biological data from Excel or CSV files, including statistical testing, normalization, quality control, and customizable scientific plotting with microbial growth-curve parameter extraction.

Key Features:

• Statistical Testing: Performs normality tests including Shapiro-Wilk, Kolmogorov-Smirnov, and Anderson-Darling, and significance tests including ANOVA, Kruskal-Wallis, t-test, and Wilcoxon.
• Data Normalization: Supports control-based normalization with normalized-data workflows.
• Quality Control: Implements replicate-aware quality control.
• Scientific Plotting: Generates boxplots, bar plots, violin plots, stacked plots, heatmaps, correlation plots between parameters, and concentration-response (dose-response) curves with configurable multi-strain visualization and raw or normalized responses.
• IC50 Estimation: Estimates IC50 with model diagnostics and statistical comparisons for dose-response curves.
• Microbial Growth-Curve Analysis: Analyzes optical-density time series and extracts quantitative growth parameters including maximum specific growth rate (uMax), doubling time (doub_time), lag time (lag_time), maximum optical density (ODmax), time to maximum growth (max_time, max_percap_time), area under the curve (AUC), and initial optical density (OD0) from fixed-interval or irregular/discontinuous numeric time points.
• Reproducibility: Includes metadata-based reproducibility.
• Export Capabilities: Exports processed datasets, statistical summaries, analysis metadata, scientific graphics, and editable vector PowerPoint figures for individual plots and multi-plot composition panels.

Scientific Applications:

• Experimental Biological Data Analysis: Processes and visualizes experimental biological data from Excel or CSV files for reproducible research workflows.
• Microbial Growth Kinetics: Quantifies microbial growth dynamics by extracting growth parameters from optical-density time-series data.
• Dose-Response Studies: Analyzes concentration-response relationships with IC50 estimation and multi-strain comparisons.
• Statistical Comparison: Compares experimental groups through parametric and non-parametric statistical tests.
• Data Quality Assessment: Evaluates replicate consistency and data distribution characteristics prior to downstream analysis.

Methodology:

BIOSZEN is implemented as an R package with modular Shiny application architecture. The microbial growth-curve module processes optical-density time series to automatically extract quantitative growth parameters. Statistical workflows incorporate normality testing followed by appropriate parametric or non-parametric significance tests. Dose-response analysis includes IC50 estimation with model diagnostics and configurable visualization of raw or normalized responses across multiple strains.