Computational challenges and opportunities in spatially resolved transcriptomic data analysis
Lyla Atta, Jean Fan
Abstract
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.
Topics & Concepts
BenchmarkingData scienceComputer scienceTranscriptomeComputational biologyData miningBiologyBusinessGeneticsGeneMarketingGene expressionSingle-cell and spatial transcriptomicsGene expression and cancer classificationMolecular Biology Techniques and Applications