SpriteHyper2vec: A SCSPRITE Data Completion Method Based on Hypergraph Random Walk

scSPRITE is an emerging method to capture multi-way chromatin interaction and generate high-resolution, genome-wide three dimensional (3D) genome organization in single cells. However, the data obtained from scSPRITE often contain missing values and exhibit sparsity, making it difficult to directly observe local structures of the 3D genome at the level of single cells or even small cell populations. Additionally, comprehending the chromatin conformation composition entails a large number of cell populations by scSPRITE with huge cost. Therefore, it is valuable to impute these missing values and extract higher-order structures using computational methods. Here, we propose SpriteHyper2vec, a single-cell imputation algorithm based on hypergraph, specifically designed for scSPRITE datasets, which effectively capture local and global topological structures by generalizing Node2vec method. When compared with original method, SpriteHyper2vec significantly improves the similarity between small cell populations and the benchmark data. Furthermore, the completion capability of SpriteHyper2vec enables the identification of A/B compartment-like structures even in small cell populations. In summary, SpriteHyper2vec effectively enhances the visualization and comparison of 3D organization in small cell populations based on scSPRITE data.