Andrea C, Giulio S, Giulia P (2026). Analyze gene therapy vector insertion sites data identified from genomics next generation sequencing reads for clonal tracking studies. doi:10.18129/B9.bioc.ISAnalytics. https://github.com/calabrialab/ISAnalytics - R package version 1.23.0, http://www.bioconductor.org/packages/ISAnalytics.

Giulia P, Giulio S, Eugenio M, Andrea C (2022). “ISAnalytics enables longitudinal and high-throughput clonal tracking studies in hematopoietic stem cell gene therapy applications.” Briefings in Bioinformatics, 24(1). ISSN -2577. doi:10.1093/bib/bbac551. https://academic.oup.com/bib/article-pdf/24/1/bbac551/48782955/bbac551.pdf, https://doi.org/10.1093/bib/bbac551.

Corresponding BibTeX entries:

  @Manual{,
    title = {Analyze gene therapy vector insertion sites data
      identified from genomics next generation sequencing reads for
      clonal tracking studies},
    author = {Calabria Andrea and Spinozzi Giulio and Pais Giulia},
    year = {2026},
    url = {http://www.bioconductor.org/packages/ISAnalytics},
    note = {https://github.com/calabrialab/ISAnalytics - R package
      version 1.23.0},
    doi = {10.18129/B9.bioc.ISAnalytics},
  }

  @Article{,
    title = {ISAnalytics enables longitudinal and high-throughput
      clonal tracking studies in hematopoietic stem cell gene therapy
      applications},
    author = {Pais Giulia and Spinozzi Giulio and Montini Eugenio and
      Calabria Andrea},
    year = {2022},
    journal = {Briefings in Bioinformatics},
    volume = {24},
    number = {1},
    doi = {10.1093/bib/bbac551},
    url = {https://doi.org/10.1093/bib/bbac551},
    abstract = {Longitudinal clonal tracking studies based on
      high-throughput sequencing technologies supported safety and
      long-term efficacy and unraveled hematopoietic reconstitution in
      many gene therapy applications with unprecedented resolution.
      However, monitoring patients over a decade-long follow-up entails
      a constant increase of large data volume with the emergence of
      critical computational challenges, unfortunately not addressed by
      currently available tools. Here we present ISAnalytics, a new R
      package for comprehensive and high-throughput clonal tracking
      studies using vector integration sites as markers of cellular
      identity. Once identified the clones externally from ISAnalytics
      and imported in the package, a wide range of implemented
      functionalities are available to users for assessing the safety
      and long-term efficacy of the treatment, here described in a
      clinical trial use case for Hurler disease, and for supporting
      hematopoietic stem cell biology in vivo with longitudinal
      analysis of clones over time, proliferation and differentiation.
      ISAnalytics is conceived to be metadata-driven, enabling users to
      focus on biological questions and hypotheses rather than on
      computational aspects. ISAnalytics can be fully integrated within
      laboratory workflows and standard procedures. Moreover,
      ISAnalytics is designed with efficient and scalable data
      structures, benchmarked with previous methods, and grants
      reproducibility and full analytical control through interactive
      web-reports and a module with Shiny interface. The implemented
      functionalities are flexible for all viral vector-based clonal
      tracking applications as well as genetic barcoding or cancer
      immunotherapies.},
    issn = {-2577},
    eprint =
      {https://academic.oup.com/bib/article-pdf/24/1/bbac551/48782955/bbac551.pdf},
  }