In recent years, there has been a rapid development in spatial transcriptomics data analysis techniques. From data preprocessing to the identification of spatially variable genes, clustering analysis, and downstream functional analysis, these steps can now be accomplished through a plethora of computational...
In recent years, there has been a rapid development in spatial transcriptomics data analysis techniques. From data preprocessing to the identification of spatially variable genes, clustering analysis, and downstream functional analysis, these steps can now be accomplished through a plethora of computational...
(https://satijalab.org/seurat/) to define cell types. Seurat has gained widespread popularity in the field of spatial transcriptomics due to its robustness, scalability, and user-friendly interface. It offers various modules that facilitate the analysis workflow, enabling researchers to perform tasks...
Registration of slices to a common anatomical reference space via the Spatial Transcriptomics Analysis Tool (STAnly) allows the unrestricted analysis of transcriptomic data across entire brain slices Our deconvolution approach (used in Figs. 1–4) subdivides a given brain slice into different larger br...
Spatial transcriptomics technologies developed in recent years can provide various information including tissue heterogeneity, which is fundamental in biological and medical research, and have been making significant breakthroughs. Single-cell RNA sequen
Gene set variation analysis HPV: Human papillomavirus LE: Leading edge NOR: Normal tissue PCA: Principal component analysis PPI: Protein-protein interaction RNA-Seq: RNA sequencing scRNA-seq: Single-cell RNA sequencing ST: Spatial transcriptomics TC: Tumor core TCGA: The Cancer Genome...
Most existing spatial transcriptome analysis methods are limited to single-slice spatial domain analysis, as they are unable to integrate gene expression and spatial information across multiple slices. However, with the advancement of spatial transcriptomics, it has become possible to obtain multiple slice...
8C). Spatial transcriptomics cell communication analysis confirmed the interaction between NUhighepi and stromal cells (fibroblasts), primarily mediated through the COL1A1/ COL1A2. The spatial trajectory inference in intra-tumoral Within the tumor’s microenvironment, understanding the in vivo dynamics ...
Schematics of the spatial multi-omics technologies, analysis workflow, and example data. A Schematics of workflows for spatial transcriptomics, proteomics, and metabolic analyses. Upper: Spatial transcriptomics platforms are classified into those based on next-generation sequencing and those based on in ...
Overview of Bento data infrastructure for subcellular analysis In order to facilitate a flexible workflow, Bento is generally compatible with molecule-level resolution spatial transcriptomics data (Fig.1A), such as datasets produced by MERFISH [13], seqFISH + [14], CosMx (NanoString) [33], ...