ClusterGVis

ClusterGVis streamlines clustering and visualization of gene expression patterns from time-series RNA-Seq and single-cell experiments within the Bioconductor ecosystem.

Key Features:

• Bioconductor Integration: Operates directly on standard Bioconductor data classes including `SummarizedExperiment` and `SingleCellExperiment`.
• Clustering Algorithms: Implements common clustering algorithms including k-means and fuzzy c-means for gene expression data.
• Publication-Ready Visualizations: Generates a suite of publication-ready visualizations to explore co-expressed gene modules.
• External Tool Compatibility: Includes functions to facilitate visualization of clustering results derived from other popular tools.

Scientific Applications:

• Time-Series RNA-Seq Analysis: Clusters and visualizes gene expression patterns from time-series RNA-Seq experiments.
• Single-Cell Analysis: Clusters and visualizes gene expression patterns from single-cell experiments.
• Co-Expressed Gene Module Exploration: Enables identification and visualization of co-expressed gene modules through clustering.

Methodology:

The package implements common clustering algorithms including k-means and fuzzy c-means, and operates directly on standard Bioconductor data classes such as `SummarizedExperiment` and `SingleCellExperiment`.