SpheroidAnalyseR

SpheroidAnalyseR analyzes high-throughput imaging datasets of three-dimensional spheroids and organoids grown in 96-well plates to quantify growth and treatment responses over time.

Key Features:

• Implementation: Implemented as an R Shiny application for data analysis and visualization.
• Imaging integration: Processes image measurement datasets produced by bespoke software for the Nikon A1R Confocal Laser Scanning Microscope.
• Automated outlier detection and removal: Identifies and removes outlier measurements automatically during data processing.
• Graphical visualization: Generates graphical representations of spheroid measurements across parameters including time, cell type, and treatment conditions.
• High-throughput longitudinal quantification: Supports quantification of 3D spheroid growth and changes over time across large 96-well plate datasets.
• Automated data processing: Automates multiple analysis steps to accelerate processing of spheroid imaging data from input to results.

Scientific Applications:

• Tumor biology and oncology: Quantifies spheroid growth and treatment responses relevant to tumor models.
• Disease modeling: Analyzes organoid and spheroid datasets to model disease-relevant phenotypes.
• Drug discovery and pharmacology: Assesses treatment effects and longitudinal responses for screening compounds.
• Cell migration and treatment-response studies: Facilitates analysis of migration and response dynamics in spheroid experiments.
• Single-cell type and complex organoid studies: Handles data from both single-cell type spheroids and more complex organoid structures.

Methodology:

Image datasets are acquired using bespoke software for the Nikon A1R Confocal Laser Scanning Microscope and analyzed with SpheroidAnalyseR, which automates data input processing, outlier identification/removal, and visualization.