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.
Keywords: Barcoding; Clonal tracking; Gene therapy; Hematopoietic stem cells; Lineage tracking; Vector integration sites.
© The Author(s) 2022. Published by Oxford University Press.