standR – spatial transcriptomic analysis for GeoMx DSP data
To gain a better understanding of the complexity of gene expression in normal and diseased…
Browsing: Spatial Transcriptomics
Demystifying Single-Cell Spatial Biology with CosMx SMI
By Patrick Danaher, PhD – Principal Biostatistician, NanoString Technologies While admitting to some bias, I’ll…
Celloscope – a probabilistic model for marker-gene-driven cell type deconvolution in spatial transcriptomics data
Spatial transcriptomics maps gene expression across tissues, posing the challenge of determining the spatial arrangement…
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…
STRIDE – a topic-model-based method to deconvolve spatial transcriptomics using scRNA-seq
The recent advances in spatial transcriptomics have brought unprecedented opportunities to understand the cellular heterogeneity…
Spacemake – processing and analysis of large-scale spatial transcriptomics data
Spatial sequencing methods increasingly gain popularity within RNA biology studies. State-of-the-art techniques quantify messenger RNA…
PASTE – alignment and integration of spatial transcriptomics data
Spatial transcriptomics (ST) measures mRNA expression across thousands of spots from a tissue slice while…