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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "ISAnalytics" in publications use:'
type: software
license: CC-BY-4.0
title: 'ISAnalytics: Analyze gene therapy vector insertion sites data identified from
  genomics next generation sequencing reads for clonal tracking studies'
version: 1.15.0
doi: 10.18129/B9.bioc.ISAnalytics
abstract: In gene therapy, stem cells are modified using viral vectors to deliver
  the therapeutic transgene and replace functional properties since the genetic modification
  is stable and inherited in all cell progeny. The retrieval and mapping of the sequences
  flanking the virus-host DNA junctions allows the identification of insertion sites
  (IS), essential for monitoring the evolution of genetically modified cells in vivo.
  A comprehensive toolkit for the analysis of IS is required to foster clonal trackign
  studies and supporting the assessment of safety and long term efficacy in vivo.
  This package is aimed at (1) supporting automation of IS workflow, (2) performing
  base and advance analysis for IS tracking (clonal abundance, clonal expansions and
  statistics for insertional mutagenesis, etc.), (3) providing basic biology insights
  of transduced stem cells in vivo.
authors:
- family-names: Pais
  given-names: Giulia
  email: giuliapais1@gmail.com
  orcid: https://orcid.org/0009-0005-5621-4803
- family-names: Calabria
  given-names: Andrea
  email: calabria.andrea@hsr.it
- family-names: Spinozzi
  given-names: Giulio
  email: spinozzi.giulio@hsr.it
preferred-citation:
  type: manual
  title: Analyze gene therapy vector insertion sites data identified from genomics
    next generation sequencing reads for clonal tracking studies
  authors:
  - family-names: Andrea
    given-names: Calabria
  - family-names: Giulio
    given-names: Spinozzi
  - family-names: Giulia
    given-names: Pais
  year: '2024'
  url: http://www.bioconductor.org/packages/ISAnalytics
  notes: https://github.com/calabrialab/ISAnalytics - R package version 1.15.0
  doi: 10.18129/B9.bioc.ISAnalytics
repository: https://bioc.r-universe.dev
repository-code: https://github.com/calabrialab/ISAnalytics
url: https://calabrialab.github.io/ISAnalytics
date-released: '2020-07-03'
contact:
- family-names: Pais
  given-names: Giulia
  email: giuliapais1@gmail.com
  orcid: https://orcid.org/0009-0005-5621-4803
references:
- type: article
  title: ISAnalytics enables longitudinal and high-throughput clonal tracking studies
    in hematopoietic stem cell gene therapy applications
  authors:
  - family-names: Giulia
    given-names: Pais
  - family-names: Giulio
    given-names: Spinozzi
  - family-names: Eugenio
    given-names: Montini
  - family-names: Andrea
    given-names: Calabria
  year: '2022'
  journal: Briefings in Bioinformatics
  volume: '24'
  issue: '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'
identifiers:
- type: url
  value: https://github.com//calabrialab/isanalytics
- type: url
  value: https://calabrialab.github.io/ISAnalytics/