scMODAL

scMODAL is a deep learning framework tailored for single-cell multi-omics data alignment using feature links.

scMODAL integrates datasets with limited known positively correlated features, leveraging neural networks and generative adversarial networks to align cell embeddings and preserve feature topology.

It not only advances integration tasks but also supports downstream analyses such as feature imputation and inference of feature relationships, offering a robust solution for advancing single-cell multi-omics research.

scMODAL Tutorials

• Tutorials
  • Example 1: CITE-seq PBMC data.
    • Run scMODAL on the CITE-seq PBMC dataset
  • Example 2: Integration of human bone marrow proteomics data.
    • Using scMODAL to integrate the CITE-seq and CyTOF BMC datasets
  • Example 3: TEA-seq tri-modality data.
    • Run scMODAL on the TEA-seq PBMC dataset
  • Example 4: Mouse brain scRNA-seq and scATAC-seq data.
    • Run scMODAL for the integration of mouse brain scRNA-seq and scATAC-seq datasets
  • Example 5: Integrating tonsil data.
    • Run scMODAL for the integration of tonsil datasets

scMODAL Installation

• Installation
  • Installation