Spatial Single Cell Analysis in Python
Tools for computational pathology
High dimensional weighted gene co-expression network analysis
R toolkit for inference, visualization and analysis of cell-cell communication from single-cell and spatially resolved transcriptomics
Spatial-eXpression-R: Cell type identification (including cell type mixtures) and cell type-specific differential expression for spatial transcriptomics
DANCE: a deep learning library and benchmark platform for single-cell analysis
Spatiotemporal modeling of spatial transcriptomics
Integrating histology and spatial transcriptomics - NeurIPS 2024
SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network
Python package to perform enrichment analysis from omics data.
Technology-invariant pipeline for spatial omics analysis that scales to millions of cells (Xenium / Visium HD / MERSCOPE / CosMx / PhenoCycler / MACSima / etc)
Haplotype-aware CNV analysis from single-cell RNA-seq
Bayesian Segmentation of Spatial Transcriptomics Data
A Toolbox for Spatial Transcriptomics Analysis
Integrating GWAS and spatial transcriptomics for spatially resolved mapping of cells associated with human complex traits.
a spatial deconvolution method based on deep learning frameworks, which converts bulk transcriptomes into spatially resolved single-cell expression profiles
Open-ST: profile and analyze tissue transcriptomes in 3D with high resolution in your lab
Code for the spatialLIBD R/Bioconductor package and shiny app
From geospatial to spatial -omics
Spatial-Linked Alignment Tool
Add a description, image, and links to the spatial-transcriptomics topic page so that developers can more easily learn about it.
To associate your repository with the spatial-transcriptomics topic, visit your repo's landing page and select "manage topics."