Instruct: Identify the main category of Biorxiv papers based on the titles and abstracts
Query: Single-cell Gene Regulation Network Interference by Large-scale Data Integration Single-cell ATAC-seq (scATAC-seq) has proven to be a state-of-art approach to investigating gene regulation at the single-cell level. However, existing methods cannot precisely uncover cell-type-specific binding of transcription regulators (TRs) and construct gene regulation networks (GRNs) in single-cell. ChIP-seq has been widely used to profile TR binding sites in various species, tissues, and samples in the past decades. Here, we developed SCRIP, an integrative method to infer single-cell TR activities and targets based on the integration of scATAC-seq and public bulk ChIP-seq datasets. Our method showed improved performance in evaluating TR binding activities with similar motif information and higher consistency with matched TR expressions. Besides, our method helps in identifying TR-regulated target genes as well as building gene regulation networks (GRN) at single-cell resolution. We demonstrate SCRIPs utility in accurate cell-type clustering, lineage tracing, and inferring cell-type-specific GRNs in multiple biological systems.
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The categories of this paper are: animal
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The categories of this paper are: education
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The categories of this paper are: developmental
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The categories of this paper are: pharmacology
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The categories of this paper are: neuroscience
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The categories of this paper are: microbiology
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The categories of this paper are: behavior
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The categories of this paper are: communication
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The categories of this paper are: biochemistry
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The categories of this paper are: systems
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The categories of this paper are: toxicology
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The categories of this paper are: immunology
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The categories of this paper are: scientific
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The categories of this paper are: cognition
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The categories of this paper are: physiology
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The categories of this paper are: cancer