Categorization of 31 Computational Methods to Detect Spatially Variable Genes from Spatially Resolved Transcriptomics Data

Explore a comprehensive analysis of computational methods for detecting spatially variable genes in spatially resolved transcriptomics data. Delve into the categorization of 31 distinct computational approaches presented by Jingyi Jessica Li at the Computational Genomics Summer Institute (CGSI) 2024. Learn about the latest advancements in spatial transcriptomics analysis and gain insights into the various methodologies used to identify genes with spatially varying expression patterns. Understand the strengths and limitations of different computational techniques and their applications in genomics research. This 50-minute conference talk provides a valuable overview for researchers, bioinformaticians, and genomics enthusiasts interested in spatial gene expression analysis and its implications for understanding cellular heterogeneity and tissue organization.