2024 Volume 59 Issue 2 Pages 67-73
Advancements in gene expression analysis techniques have led to a transition in the focus of analysis from tissue and organ levels to the single-cell level. This shift enables the elucidation of the heterogeneity of cellular phenotypes within tissues and the identification of rare cellular populations based on gene expression patterns in individual cells. However, in single-cell transcriptome analysis, cells are isolated from tissues, resulting in the loss of spatial information about cellular positions within the tissue. To address this, spatial transcriptomics analysis, which preserves the spatial information of cells, has been developed and is rapidly gaining popularity. Spatial transcriptomics analysis is advancing rapidly, with new analytical methods being reported continuously. Therefore, this paper aims to classify established analysis methods based on principles, explain representative analysis methods, and discuss the selection of analysis methods according to the experimental objectives, as well as outline the general flow of data analysis. (148 words)
