AltschulerWu-Lab / MUSELinks
MUSE is a deep learning approach characterizing tissue composition through combined analysis of morphologies and transcriptional states for spatially resolved transcriptomics data.
☆35Updated 3 years ago
Alternatives and similar repositories for MUSE
Users that are interested in MUSE are comparing it to the libraries listed below
Sorting:
- Sub-cellular spatial transcriptomics Cell Segmentation☆66Updated last year
- ☆35Updated 2 months ago
- Super-resolved spatial transcriptomics by deep data fusion☆74Updated 2 years ago
- ☆39Updated last year
- Graph-based foundation model for spatial transcriptomics data. Zero-shot spatial domain inference, batch-effect correction, and many othe…☆53Updated last week
- A Python toolkit for subcellular analysis of spatial transcriptomics data☆83Updated last month
- Biologically-informed deep learning for cell segmentation of subcelluar spatial transcriptomics data☆45Updated last year
- ☆69Updated 2 years ago
- ☆57Updated this week
- Spatial Single-Cell Analysis Toolkit☆98Updated 2 months ago
- Construction of a 3D whole organism spatial atlas by joint modeling of multiple slices☆66Updated last year
- astir | Automated cell identity from single-cell multiplexed imaging and proteomics 🖥🔬✨☆55Updated 2 months ago
- Automate unsupervised machine learning cell type identification using both protein expressions and cell spatial neighborhood information …☆37Updated last year
- ClusterMap for multi-scale clustering analysis of spatial gene expression☆46Updated 3 months ago
- Integrated pipeline for multiplexed image analysis☆96Updated 5 months ago
- ☆22Updated 5 months ago
- ☆55Updated 2 years ago
- A toolkit for processing multiplexed tissue images☆63Updated last month
- A spatial omics data analysis tool that enables both unsupervised and supervised discovery of complex tissue cellular neighborhoods from …☆24Updated 5 months ago
- ☆141Updated 8 months ago
- Accessible and interoperable whole slide image analysis☆130Updated last week
- A unified approach for integrating spatial and single-cell transcriptomics data by leveraging deep generative models☆73Updated last year
- ☆52Updated 4 years ago
- SEQUOIA: Digital profiling of cancer transcriptomes with grouped vision attention☆42Updated 3 months ago
- Python tool for alignment of spatial transcriptomics (ST) data using diffeomorphic metric mapping☆88Updated last year
- Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications☆58Updated last year
- Probabilistic Alignment of Spatial Transcriptomics Experiments☆94Updated 6 months ago
- ☆65Updated 7 months ago
- Self-supervised representation learning combining GTEx histology, RNA-seq and WGS☆30Updated 5 months ago
- Spatial Transcriptomic Analysis using Reference-Free auxiliarY deep generative modeling and Shared Histology☆119Updated 3 months ago