Please cite the paper below for the GUIDEseq package.

Lihua Julie Zhu, Michael Lawrence, Ankit Gupta, Herve Pages, Alper Kucukural, Manuel Garber and Scot A. Wolfe. GUIDEseq: a bioconductor package to analyze GUIDE-Seq datasets for CRISPR-Cas nucleases. BMC Genomics. 2017. 18(1):379

Corresponding BibTeX entry:

  @Article{,
    title = {GUIDEseq: a bioconductor package to analyze GUIDE-Seq
      datasets for CRISPR-Cas nucleases},
    author = {Lihua Julie Zhu and Michael Lawrence and Ankit Gupta and
      Herve Pages and Alper Kucukural and Manuel Garber and Scot A.
      Wolfe},
    journal = {BMC Genomics},
    volume = {18},
    year = {2017},
    number = {1},
    url =
      {http://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-017-3746-y},
    pubmedid = {PMC5433024},
    abstract = {Genome editing technologies developed around the
      CRISPR-Cas9 nuclease system have facilitated the investigation of
      a broad range of biological questions. These nucleases also hold
      tremendous promise for treating a variety of genetic disorders.
      In the context of their therapeutic application, it is important
      to identify the spectrum of genomic sequences that are cleaved by
      a candidate nuclease when programmed with a particular guide RNA,
      as well as the cleavage efficiency of these sites. Powerful new
      experimental approaches, such as GUIDE-seq, facilitate the
      sensitive, unbiased genome-wide detection of nuclease cleavage
      sites within the genome. Flexible bioinformatics analysis tools
      for processing GUIDE-seq data are needed. Here, we describe an
      open source, open development software suite, GUIDEseq, for
      GUIDE-seq data analysis and annotation as a Bioconductor package
      in R. The GUIDEseq package provides a flexible platform with more
      than 60 adjustable parameters for the analysis of datasets
      associated with custom nuclease applications. These parameters
      allow data analysis to be tailored to different nuclease
      platforms with different length and complexity in their guide and
      PAM recognition sequences or their DNA cleavage position. They
      also enable users to customize sequence aggregation criteria, and
      vary peak calling thresholds that can influence the number of
      potential off-target sites recovered. GUIDEseq also annotates
      potential off-target sites that overlap with genes based on
      genome annotation information, as these may be the most important
      off-target sites for further characterization. In addition,
      GUIDEseq enables the comparison and visualization of off-target
      site overlap between different datasets for a rapid comparison of
      different nuclease configurations or experimental conditions. For
      each identified off-target, the GUIDEseq package outputs mapped
      GUIDE-Seq read count as well as cleavage score from a user
      specified off-target cleavage score prediction algorithm
      permitting the identification of genomic sequences with
      unexpected cleavage activity. The GUIDEseq package enables
      analysis of GUIDE-data from various nuclease platforms for any
      species with a defined genomic sequence. This software package
      has been used successfully to analyze several GUIDE-seq datasets.
      The software, source code and documentation are freely available
      at
      http://www.bioconductor.org/packages/release/bioc/html/GUIDEseq.html.},
  }