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Published on: January 10, 2019
scDIFF: automatic cell type annotation using scATAC-seq data by incorporating bulk-level genomic and epigenomic
Hao-Yu Wang1, Hao Dong1, Pu-Feng Du1
1College of Intelligence and Computing, Tianjin University, Tianjin 300350, China.
Abstract:
Single-cell assay for transposase-accessible chromatin sequencing (scATAC-seq) provides an opportunity to look deeply into the gene regulation mechanism at the single-cell resolution. With the rapid accumulation of scATAC-seq data, there is an urgent need for automatic cell type annotations using scATAC-seq data. Most existing methods rely on creating artificial gene activity matrix, due to the extreme sparsity nature of the scATAC-seq data. However, these methods fail to exploit the intrinsic information inherent in the scATAC-seq peaks. We present scDIFF, a diffusive transformer-based method that integrates bulk-level genomic and epigenomic information with scATAC-seq data to annotate cell types without creating artificial gene activity matrix. Our scDIFF performed constantly better than state-of-the-art methods on all 46 benchmarking pairs of reference and query datasets across different sequencing platforms. The complete implementation of scDIFF is well-documented and freely available on GitHub (https://github.com/haoyu-wangg/scDIFF).
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