SpatialCPie: an R/Bioconductor package for spatial transcriptomics cluster evaluation

BMC Bioinformatics. 2020 Apr 29;21(1):161. doi: 10.1186/s12859-020-3489-7.

Abstract

Background: Technological developments in the emerging field of spatial transcriptomics have opened up an unexplored landscape where transcript information is put in a spatial context. Clustering commonly constitutes a central component in analyzing this type of data. However, deciding on the number of clusters to use and interpreting their relationships can be difficult.

Results: We introduce SpatialCPie, an R package designed to facilitate cluster evaluation for spatial transcriptomics data. SpatialCPie clusters the data at multiple resolutions. The results are visualized with pie charts that indicate the similarity between spatial regions and clusters and a cluster graph that shows the relationships between clusters at different resolutions. We demonstrate SpatialCPie on several publicly available datasets.

Conclusions: SpatialCPie provides intuitive visualizations of cluster relationships when dealing with Spatial Transcriptomics data.

Keywords: Cluster analysis; Data visualization; R package; Spatial transcriptomics.

MeSH terms

  • Cluster Analysis
  • Gene Expression Regulation, Developmental
  • Heart / embryology
  • Humans
  • Software*
  • Transcriptome / genetics*