SIMBA: SIngle-cell eMBedding Along with features

SIMBA is a method to embed cells along with their defining features such as gene expression, transcription factor binding sequences and chromatin accessibility peaks into the same latent space. The joint embedding of cells and features allows SIMBA to perform various types of single cell tasks, including but not limited to single-modal analysis (e.g. scRNA-seq and scATAC-seq analysis), multimodal analysis, batch correction, and multi-omic integration.

SIMBA primer

• Basic concepts
• Output

Tutorials

• scRNA-seq analysis
• scATAC-seq analysis
• Multimodal analysis
• Multimodal gene regulatory network
• Batch correction (two batches)
• Batch correction (multiple batches)
• Multiomics integration
• Generalized graph generation
• Use edge weigthts
• SIMBA on 1.3 million cells