Heatmaps are an indispensible visualization tool for examining large-scale snapshots of genomic activity across various types of next-generation sequencing datasets. However, traditional heatmap software do not typically offer multi-scale insight across multiple layers of genomic analysis (e.g., differential expression analysis, principal component analysis, gene ontology analysis, and network analysis) or multiple types of next-generation sequencing datasets (e.g., ChIP-seq and RNA-seq). As such, it is natural to want to interact with a heatmap’s contents using an extensive set of integrated analysis tools applicable to a broad array of genomic data types.
Researchers from the University of Miami Miller School of Medicine propose a user-friendly ChIP-seq and RNA-seq software suite for the interactive visualization and analysis of genomic data, including integrated features to support differential expression analysis, interactive heatmap production, principal component analysis, gene ontology analysis, and dynamic network analysis.
Interactive heatmap visualization
MicroScope heatmap options showcasing the magnification feature as well as features such as: statistical parameter settings, l o g 2 data transformation, multiple heatmap color schemes, hierarchical clustering, row/column dendrogram branch coloring, row/column font size, and heatmap download button