shinyheatmap

shinyheatmap generates interactive and static heatmaps to visualize very large genomic and other -omics datasets (transcriptomics, metabolomics, metagenomics), including single-cell sequencing results, for exploratory analysis of high-dimensional numerical data.

Key Features:

• Ultra-Fast Rendering: Uses the fastheatmap high-performance plugin to plot interactive and static heatmaps from datasets containing up to 10^5–10^7 rows in seconds.
• Low Memory Footprint: Optimized to minimize memory usage and avoid extensive in-memory computation when processing large matrices.
• Customizable Heatmaps: Produces highly customizable static and interactive colored-grid representations of numerical matrices.
• R Implementation: Core methods and functionality are implemented in R.
• Designed for High-Dimensional Omics: Targets large-scale datasets typical of genomics, transcriptomics, metabolomics, metagenomics, and single-cell sequencing.

Scientific Applications:

• Genomics and Transcriptomics Visualization: Visualization of large gene expression matrices, including single-cell sequencing output.
• Metabolomics and Metagenomics Data Exploration: Representation of metabolite abundance and microbial community matrices for pattern detection.
• Exploratory Analysis of High-Dimensional Numerical Data: Transformation of large datasets into colored-grid heatmaps to facilitate identification of clusters, gradients, and outliers.

Methodology:

Implemented in R and leveraging the fastheatmap high-performance plugin for rapid plotting, with explicit optimizations to reduce memory usage and avoid large in-memory computations.