Spatial Single Cell Analysis in Python
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Updated
Aug 16, 2024 - Python
Spatial Single Cell Analysis in Python
Tools for computational pathology
DANCE: a deep learning library and benchmark platform for single-cell analysis
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.
Spatiotemporal modeling of spatial transcriptomics
Technology-invariant pipeline for spatial omics analysis (Xenium / MERSCOPE / CosMx / PhenoCycler / MACSima / Hyperion) that scales to millions of cells
HEST: Bringing Spatial Transcriptomics and Histopathology together
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.
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.
A plugin to visualise 3D spatial single cell omics
HoloNet. Reveal the holograph of functional communication events in spatial transcriptomics. Help understand how microenvironments shaping cellular phenotypes
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
Develop custom oligo design pipelines.
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