Visualization for Spatial Transcriptomics Data

Abstract

Spatial Transcriptomics, proposed by Ståhl et al. in 2016, is a series of novel methods that enables transcriptomes' quantitative spatial analyses in individual tissue sections. The development of Spatial Transcriptomics has profoundly impacted research and diagnostics in many fields and opened rich possibilities for visualization and analysis. Although there exist several tools and packages now for spatial transcriptomics data, platforms with functionalities of better flexibility are in demand to satisfy the analytic needs of biological research. Therefore, this project aims to develop a novel online tool to display and examine Spatial Transcriptomic data. It seeks to create comprehensive modules for the interactions and customizations of Spatial Transcriptomic data visualization.

The visualization modules built in this project include a correlation plot, 2-D and 3-D embedding maps, a U-map, a correlation plot, a violin plot, and a deconvolution plot. The project will develop the tool based on the Oviz framework designed by Mr. Hechen Li in 2016, which adopts Typescript as its primary language. They will ultimately be implemented as an online tool collectively on https://sc.deepomics.org/ that adopts Ruby on Rails as its main framework. Furthermore, this report will include a case study to test the actual visualization power of these modules in existing transcriptomics research projects. It will also feature visualizations of ten datasets as an output of this project, including tissue slices from distinctive organs such as the human brain or the mouse kidney.

Hopefully, the tool developed in this project could serve as a novel example of web-based visualization applications based on the language TypeScript. Additionally, this new tool will provide more substantial analysis power and better flexibility for observing and analyzing Spatial Transcriptomics data and becoming a good aid for genomic research.