Spatial transcriptomics
SpaHDmap
Interpretable, high-resolution dimension reduction through the integration of spatial transcriptomics and histology images.
- Multimodal learning
- Multiple spatial datasets
Research / Open-source tools
Research software
Tools for exploring biological data, from single cells to spatial tissues.
Single-cell integration
scINSIGHT
A matrix factorization model for analyzing single-cell samples from different biological conditions, including disease phases, treatment groups, and developmental stages.
- Shared and condition-specific patterns
- Batch correction
- Automated parameter selection
Adaptive clustering
scAce
Jointly learns cell embeddings and cluster assignments with a variational autoencoder and adaptive cluster merging.
- Adaptive embedding and clustering
- Large-scale scRNA-seq
Graph representation learning
scBiG
Learns cell and gene embeddings from a cell–gene bipartite graph using a graph autoencoder.
- Cell–gene relationships
- Biological structure preservation