spatialHeatmap: Visualizing spatial assays in anatomical images and network graphs
Year: 2021
Type: other
Abstract: The spatialHeatmap package provides functionalities for visualizing cell-, tissue- and organ-specific data of biological assays by coloring the corresponding spatial features defined in anatomical images according to a numeric color key. The color scheme used to represent the assay values can be customized by the user. This core functionality of the package is called a spatial heatmap (SHM) plot. It is enhanced with visualization tools for groups of measured items (e.g. gene modules) sharing related abundance profiles, including matrix heatmaps combined with hierarchical clustering dendrograms and network representations. The environment also allows to co-visualize single cell assay data with various embedding algorithms of high-dimensional data. Automated detection of spatially enriched abundance differences is also supported, such as genes expressed in specific tissues. The functionalities of spatialHeatmap can be used either in a command-driven mode from within R or a graphical user interface (GUI) provided by a Shiny App that is also part of this package. While the R-based mode provides flexibility to customize and automate analysis routines, the Shiny App includes a variety of convenience features that will appeal to experimentalists and other users less familiar with R. Moreover, the Shiny App can be used on both local computers as well as centralized server-based deployments (e.g. cloud-based or custom servers) that can be accessed remotely as a public web service for using spatialHeatmap's functionalities with community and/or private data.
Authors: Jianhai Zhang, Jordan Hayes, Le Zhang, Bing Yang, Wolf B Frommer, Julia Bailey-Serres, Thomas Girke
Institution: University of California, Riverside
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
OpenAlex ID: W3190052239