slanter contains a set of functions for reordering data, and generating hierarchical clustering for ordered data, for improved visualization.
See the published R package, the rdocumentation, or the latest github version documentation for details. Specifically, the meristems vignette explains why and how to use this package.
In general, if your data is a similarity matrix (each entry is a non-negative value that indicates how similar a pair of elements is to each other, higher is better), then use slanter::sheatmap as a drop-in replacement for pheatmap::pheatmap, and enjoy.
The lower level function slanter::slanted_orders will compute the visualization order and slanter::oclust will compute hierarchical clustering that is consistent with this order. See the published R package, the rdocumentation, or the latest github version documentation’s reference section for the list and description of the available functions.