Computational challenges and opportunities in spatially resolved transcriptomic data analysis - Lyla Atta (Nature Portfolio, 2021)
Spatially resolved transcriptomic data demand new computational analysis methods to derive biological insights. Here, we comment on these associated computational challenges as well as highlight the opportunities for standardized benchmarking metrics and data-sharing infrastructure in spurring innovation moving forward.