ncdfFlow

ncdfFlow stores, manages, and analyzes flow cytometry (FCM) data in HDF5 format to support high-throughput FCM experiments and downstream analyses.

Key Features:

• HDF5 Storage: Uses HDF5 to store large FCM datasets for efficient access and management.
• Data Management: Provides structures for organizing and maintaining flow cytometry datasets within R and the Bioconductor ecosystem.
• Quality Assessment and Normalization: Includes functions for assessing data quality and performing normalization of FCM measurements.
• Outlier Detection and Automated Gating: Implements outlier detection and automated gating to identify cell populations and remove anomalous events.
• Cluster Labeling and Feature Extraction: Supports cluster labeling and extraction of per-cluster features for downstream analysis.
• Integration with Bioconductor Packages: Integrates with other R/Bioconductor packages to leverage clustering and data mining tools for high-throughput analysis.

Scientific Applications:

• High-Throughput Screening: Facilitates analysis of automated and standardized cell-based assays in high-throughput screening workflows.
• Qualitative Research: Supports reproducible and standardized qualitative analyses of flow cytometry experiments.

Methodology:

Computational methods explicitly include HDF5-based data storage, quality assessment, normalization, outlier detection, automated gating, clustering, and feature extraction, implemented within the R/Bioconductor environment.