What is Higashi

Multiscale and integrative single-cell Hi-C analysis with Higashi

Higashi is a computational framework for scHi-C analysis with the following features:

• Higashi represents the scHi-C dataset as a hypergraph
  • Each cell and each genomic bin are represented as the cell node and the genomic bin node.
  • Each non-zero entry in the single-cell contact map is modeled as a hyperedge.
  • The read count for each chromatin interaction is used as the attribute of the hyperedge.
• Higashi uses a hypergraph neural network to unveil high-order interaction patterns within this constructed hypergraph.
• Higashi can produce the embeddings for the scHi-C for downstream analysis.
• Higashi can impute single-cell Hi-C contact maps, enabling detailed characterization of 3D genome features such as TAD-like domain boundaries and A/B compartment scores at single-cell resolution.

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There are three major parts of Higashi:

• Higashi-main, which is the core part of Higashi. It takes the input sparse scHi-C dataset and produces embeddings vectors as well as imputed contact maps.
• Higashi-analysis, which enables multi-scale and integrative analysis of the imputed contact maps.
• Higashi-vis, which is the visualization tool we developed for visualizing Higashi results or general single cell chromatin structure datasets.

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Follow the links below to get started:

• Installing Higashi
• Usage of Higashi-main
• Single cell TAD calling
• Single cell A/B compartment calling
• Usage of Higashi-vis

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Higashi is constantly being updated, see change log for the updating history

Contact

Please contact [email protected] or raise an issue in the github repo with any questions about installation or usage.