STmut: a framework for visualizing somatic alterations in spatial transcriptomics data of cancer
Limin Chen, Darwin Chang, Bishal Tandukar, Delahny Deivendran, Joanna Poźniak, Noel Cruz‐Pacheco, Raymond J. Cho, Jeffrey B. Cheng, Iwei Yeh, Jean‐Christophe Marine, Boris C. Bastian, Andrew L. Ji, A. Hunter Shain
Abstract
Spatial transcriptomic technologies, such as the Visium platform, measure gene expression in different regions of tissues. Here, we describe new software, STmut, to visualize somatic point mutations, allelic imbalance, and copy number alterations in Visium data. STmut is tested on fresh-frozen Visium data, formalin-fixed paraffin-embedded (FFPE) Visium data, and tumors with and without matching DNA sequencing data. Copy number is inferred on all conditions, but the chemistry of the FFPE platform does not permit analyses of single nucleotide variants. Taken together, we propose solutions to add the genetic dimension to spatial transcriptomic data and describe the limitations of different datatypes.