imageHTS

imageHTS analyzes high-throughput microscopy-based screens by providing cell segmentation, quantitative feature extraction, and cell type prediction within an R/Bioconductor framework.

Key Features:

• R/Bioconductor integration: Implemented as an R package that integrates with the Bioconductor project.
• Modular and extensible framework: Modular design enabling composition and extension of analysis workflows.
• Cell Segmentation: Robust algorithms for accurate segmentation of cells within microscopy images.
• Quantitative Feature Extraction: Extraction of detailed quantitative features from segmented cells, including morphology and other phenotypic traits.
• Cell Type Prediction: Prediction of cell types based on extracted features.
• Distributed environments and remote data access: Operation in distributed environments with standardized access to remote data sources.
• Interoperability: Interoperates with other Bioconductor packages, leveraging the project's suite of 934 packages.

Scientific Applications:

• Genomics and molecular biology: Analysis of cellular responses in genomics and molecular biology experiments using microscopy-based screens.
• Drug discovery: Phenotypic screening to assess compound effects on cellular phenotypes.
• Phenotypic screening: High-throughput identification and quantification of phenotype changes across conditions.
• Exploration of gene function: Investigation of gene function via imaging-derived cellular phenotypes.

Methodology:

Methods explicitly include cell segmentation, quantitative feature extraction from segmented cells, and cell type prediction; the package operates within distributed environments providing standardized access to remote data sources and interoperability with other Bioconductor packages.