Technology-invariant pipeline for spatial omics analysis (Xenium / MERSCOPE / CosMx / PhenoCycler / MACSima / Hyperion) that scales to millions of cells
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Updated
Jul 12, 2024 - Python
Technology-invariant pipeline for spatial omics analysis (Xenium / MERSCOPE / CosMx / PhenoCycler / MACSima / Hyperion) that scales to millions of cells
Integrated pipeline for multiplexed image analysis
astir | Automated cell identity from single-cell multiplexed imaging and proteomics 🖥🔬✨
Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications
Probabilistic topic model for identifying cellular micro-environments.
HistoJS: Web-Based Analytical Tool for Multiplexed Images. Limited Github Online Demo 👇
MIAAIM: Multi-omics Image Alignment and Analysis by Information Manifolds
An end-to-end processing pipeline that transforms multi-channel whole-slide images into single-cell data.
Rust library for reading imaging mass cytometry (IMC) data stored in .mcd files.
High-dimensional image preparation module for MIAAIM
SpatialVisVR is a VR platform tailored for advanced visualization and analysis of medical images in immuno-oncology. It allows real-time capture and comparison of mIF and mIHC images via mobile devices. Leveraging deep learning, it matches and displays similar images, supporting up to 100 protein channels.
Code to compare and assess several techniques to denoise Imaging Mass cytometry
High-dimensional image registration workflow as part of the MIAAIM framework. Hdi-reg is written in Python, and utilizes the Elastix library for computations.
Code to compare and assess several techniques to denoise Imaging Mass cytometry
Multi-omics image alignment and analysis by information manifolds (MIAAIM)
A workflow designed to perform multiplexed image analysis, specialising in (but not limited to) analysis of metal distribution in LA-ICP-TOFMS data.
Perform RESTORE normalization on multiplexed imaging data.
General importing and utility functions for high-dimensional image data
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