{
  "_id": "6a1b04e31d7bb097a0a02be5",
  "Package": "SCOPE",
  "Type": "Package",
  "Title": "A normalization and copy number estimation method for\nsingle-cell DNA sequencing",
  "Version": "1.24.0",
  "Author": "Rujin Wang, Danyu Lin, Yuchao Jiang",
  "Maintainer": "Rujin Wang <rujin@email.unc.edu>",
  "Description": "Whole genome single-cell DNA sequencing (scDNA-seq)\nenables characterization of copy number profiles at the\ncellular level. This circumvents the averaging effects\nassociated with bulk-tissue sequencing and has increased\nresolution yet decreased ambiguity in deconvolving cancer\nsubclones and elucidating cancer evolutionary history.\nScDNA-seq data is, however, sparse, noisy, and highly variable\neven within a homogeneous cell population, due to the biases\nand artifacts that are introduced during the library\npreparation and sequencing procedure. Here, we propose SCOPE, a\nnormalization and copy number estimation method for scDNA-seq\ndata. The distinguishing features of SCOPE include: (i)\nutilization of cell-specific Gini coefficients for quality\ncontrols and for identification of normal/diploid cells, which\nare further used as negative control samples in a Poisson\nlatent factor model for normalization; (ii) modeling of GC\ncontent bias using an expectation-maximization algorithm\nembedded in the Poisson generalized linear models, which\naccounts for the different copy number states along the genome;\n(iii) a cross-sample iterative segmentation procedure to\nidentify breakpoints that are shared across cells from the same\ngenetic background.",
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  "biocViews": "SingleCell, Normalization, CopyNumberVariation, Sequencing,\nWholeGenome, Coverage, Alignment, QualityControl, DataImport,\nDNASeq",
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  "Repository": "https://bioc-release.r-universe.dev",
  "Date/Publication": "2026-04-28 12:51:50 UTC",
  "RemoteUrl": "https://github.com/bioc/SCOPE",
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  "_published": "2026-05-30T15:40:19.728Z",
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    "email": "rujin@email.unc.edu"
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    "normalization",
    "copynumbervariation",
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    "wholegenome",
    "coverage",
    "alignment",
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      "topics": [
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      ]
    },
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      "title": "Get bam file directories, sample names, and whole genomic bins",
      "topics": [
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      ]
    },
    {
      "page": "get_coverage_scDNA",
      "title": "Get read coverage from single-cell DNA sequencing",
      "topics": [
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      ]
    },
    {
      "page": "get_gc",
      "title": "Compute GC content",
      "topics": [
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      ]
    },
    {
      "page": "get_gini",
      "title": "Compute Gini coefficients for single cells",
      "topics": [
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    },
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      "title": "Compute mappability",
      "topics": [
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    },
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      "title": "Get QC metrics for single cells",
      "topics": [
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      "title": "Visualize EM fitting for each cell.",
      "topics": [
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    },
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      "title": "Plot post-segmentation copy number profiles of integer values",
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      "source": "SCOPE_vignette.Rmd",
      "filename": "SCOPE_vignette.html",
      "title": "SCOPE: Single-cell Copy Number Estimation",
      "author": "Rujin Wang, Danyu Lin, Yuchao Jiang",
      "engine": "knitr::rmarkdown",
      "headings": [
        "1. Overview of analysis pipeline",
        "1.1 Introduction",
        "1.2 Bioinformatic pre-processing",
        "2. Pre-computation and Quality Control",
        "2.1 Pre-preparation",
        "2.2 Getting GC content and mappability",
        "2.3 Getting coverage",
        "2.4 Quality control",
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      "created": "2019-09-09 15:57:10",
      "modified": "2021-07-14 20:08:11",
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