Spatial Single Cell Analysis in Python

Tools for computational pathology

DANCE: a deep learning library and benchmark platform for single-cell analysis

Spatiotemporal modeling of spatial transcriptomics

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.

HEST: Bringing Spatial Transcriptomics and Histopathology together - NeurIPS 2024

Technology-invariant pipeline for spatial omics analysis that scales to millions of cells (Xenium / Visium HD / MERSCOPE / CosMx / PhenoCycler / MACSima / etc)

Spatial-Linked Alignment Tool

ST Pipeline contains the tools and scripts needed to process and analyze the raw files generated with the Spatial Transcriptomics method in FASTQ format.

Construction of a 3D whole organism spatial atlas by joint modeling of multiple slices

Interactive software tool for the assignment of cell types in single-cell studies.

Detection of allele-specific subclonal copy number alterations from single-cell transcriptomic data.

A Python implementation of the model described in our publication "A convolutional neural network for common-coordinate registration of high-resolution histology images" developed principally for applications to registration of spatial transcriptomics image data.

A probabilistic cell typing algorithm for spatial transcriptomics.

HoloNet. Reveal the holograph of functional communication events in spatial transcriptomics. Help understand how microenvironments shaping cellular phenotypes

A plugin to visualise 3D spatial single cell omics

Generate the UMI count matrix from CEL-Seq2 sequencing data

A toolset for analysis and visualisation of Spatial Transcriptomics datasets.

simplified cellranger for long-read data