The objective of this analysis mode is to allow users to develop some understanding of the relationships among samples, features and clusters within individual omics datasets.
Users will go straight to the heatmap visualization without performing multi-omics cluster analysis. Interactive heatmaps (one for each dataset) are placed side-by-side to allow visual identification and subsequent enrichment analysis of features that correspond to either the detected clusters or the experimental groups. In particular,
- Feature clustering: users can use common hierarchical clustering methods for individual omics data
- Sample clustering: samples will be organized according to their meta-data labels by default. Users can use the “Cluster Samples” top menu to perform hierarchical clustering for a selected omics data. Note unlike feature clustering which can be performed independently for each omics data, samples are shared - the current sample clustering (even based on a single data) will affect both omics data.