spatial-transcriptomics
There are 188 repositories under spatial-transcriptomics topic.
scverse/squidpy
Spatial Single Cell Analysis in Python
jinworks/CellChat
R toolkit for inference, visualization and analysis of cell-cell communication from single-cell and spatially resolved transcriptomics
Dana-Farber-AIOS/pathml
Tools for computational pathology
dmcable/spacexr
Spatial-eXpression-R: Cell type identification (including cell type mixtures) and cell type-specific differential expression for spatial transcriptomics
smorabit/hdWGCNA
High dimensional weighted gene co-expression network analysis
OmicsML/dance
DANCE: a deep learning library and benchmark platform for single-cell analysis
aristoteleo/spateo-release
Spatiotemporal modeling of spatial transcriptomics
mahmoodlab/HEST
Integrating histology and spatial transcriptomics - NeurIPS 2024
jianhuupenn/SpaGCN
SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network
gustaveroussy/sopa
Technology-invariant pipeline for spatial omics analysis that scales to millions of cells (Xenium / Visium HD / MERSCOPE / CosMx / PhenoCycler / MACSima / etc)
kharchenkolab/Baysor
Bayesian Segmentation of Spatial Transcriptomics Data
kharchenkolab/numbat
Haplotype-aware CNV analysis from single-cell RNA-seq
saezlab/decoupler-py
Python package to perform enrichment analysis from omics data.
JianYang-Lab/gsMap
Integrating GWAS and spatial transcriptomics for spatially resolved mapping of cells associated with human complex traits.
theMILOlab/SPATA2
A Toolbox for Spatial Transcriptomics Analysis
ZJUFanLab/bulk2space
a spatial deconvolution method based on deep learning frameworks, which converts bulk transcriptomes into spatially resolved single-cell expression profiles
rajewsky-lab/openst
Open-ST: profile and analyze tissue transcriptomes in 3D with high resolution in your lab
LieberInstitute/spatialLIBD
Code for the spatialLIBD R/Bioconductor package and shiny app
pachterlab/voyager
From geospatial to spatial -omics
gao-lab/SLAT
Spatial-Linked Alignment Tool
lmweber/OSTA
"Orchestrating Spatial Transcriptomics Analysis with Bioconductor" book
jfnavarro/st_pipeline
ST Pipeline contains the tools and scripts needed to process and analyze the raw files generated with the Spatial Transcriptomics method in FASTQ format.
LieberInstitute/HumanPilot
Spatial Transcriptomics human DLPFC pilot study part of the spatialLIBD project
alexisvdb/singleCellHaystack
Finding surprising needles (=genes) in haystacks (=single cell transcriptome data).
JEFworks-Lab/MERINGUE
characterizing spatial gene expression heterogeneity in spatially resolved single-cell transcriptomics data with nonuniform cellular densities
ZJUFanLab/SpaTalk
Knowledge-graph-based cell-cell communication inference for spatially resolved transcriptomic data
ma-compbio/SpiceMix
spatial transcriptome, single cell
saezlab/mistyR
Multiview Intercellular SpaTial modeling framework
nf-core/spatialvi
Pipeline for processing spatially-resolved gene counts with spatial coordinates and image data. Designed for 10x Genomics Visium transcriptomics.
ccruizm/GBmap
Code used to create the core and extended GBmap, including downstream analyses (cell-cell interactions, spatial transcriptomics deconvolution) and how to produce the figures.
YangLabHKUST/STitch3D
Construction of a 3D whole organism spatial atlas by joint modeling of multiple slices
genecell/COSGR
Accurate and fast cell marker gene identification with COSG
10XGenomics/HumanColonCancer_VisiumHD
Associated code to the manuscript "Characterization of immune cell populations in the tumor microenvironment of colorectal cancer using high definition spatial profiling"
cnio-bu/beyondcell
Beyondcell is a computational methodology for identifying tumour cell subpopulations with distinct drug responses in single-cell RNA-seq and Spatial Transcriptomics data.
jianhuupenn/TESLA
Deciphering tumor ecosystems at super-resolution from spatial transcriptomics with TESLA
PMBio/segger
a cutting-edge cell segmentation model specifically designed for single-molecule resolved spatial omics datasets. It addresses the challenge of accurately segmenting individual cells in complex imaging datasets, leveraging a unique approach based on graph neural networks (GNNs).