SPADE – spatial deconvolution for domain specific cell-type estimation
In genomics, understanding how genes are expressed in different cell types within their spatial context…
Browsing: Spatial Analysis
New method tags cells with location coordinates for single-cell studies
The technique, called Slide-tags, allows scientists to map the location of cells within tissues in…
standR – spatial transcriptomic analysis for GeoMx DSP data
To gain a better understanding of the complexity of gene expression in normal and diseased…
CeLEry – leveraging spatial transcriptomics data to recover cell locations in single-cell RNA-seq
Single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cellular heterogeneity in health and disease.…
spSeudoMap – cell type mapping of spatial transcriptomics using unmatched single-cell RNA-seq data
Since many single-cell RNA-seq (scRNA-seq) data are obtained after cell sorting, such as when investigating…
SiT – spatial isoform transcriptomics
In situ capturing technologies add tissue context to gene expression data, with the potential of…
AllenDigger – spatial expression data visualization, spatial heterogeneity delineation, and single-cell registration based on the Allen Brain Atlas
Spatial transcriptomics can be used to capture cellular spatial organization and has facilitated new insights…
SRTsim – spatial pattern preserving simulations for spatially resolved transcriptomics
Spatially resolved transcriptomics (SRT)-specific computational methods are often developed, tested, validated, and evaluated in silico…
GraphST – spatially informed clustering, integration, and deconvolution of spatial transcriptomics
Spatial transcriptomics technologies generate gene expression profiles with spatial context, requiring spatially informed analysis tools…
Bulk2Space – de novo analysis of bulk RNA-seq data at spatially resolved single-cell resolution
Uncovering the tissue molecular architecture at single-cell resolution could help better understand organisms’ biological and…