Spatial Transcriptomics
Showing 8 of 8 projects
A scalable Python toolkit for analyzing and visualizing spatial molecular data from tissue sections.
An open-source toolkit for scalable, standardized computational pathology analysis, enabling AI and machine learning on large imaging datasets.
A probabilistic cell segmentation method for spatial transcriptomics data from platforms like Xenium, CosMx, MERSCOPE, and Visium HD.
A deep learning-based, threshold-agnostic, subpixel-accurate 2D and 3D spot detection method for fluorescence microscopy and spatial transcriptomics.
An open-source tool for precise, interactive, fast, and scalable spot detection in 2D/3D microscopy images for FISH-based spatial genomics.
An MCP server that enables natural language conversation for analyzing spatial transcriptomics data through 60+ curated methods.
A Python library for integrating multiomic single-cell data using product-of-experts variational autoencoders.
A fast spatial deconvolution tool for transcriptomics data that scales to million-spot datasets while preserving rare cell type signals.
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