Interrogation of clonal tracking data using barcodetrackR

Diego A. Espinoza, Ryland D. Mortlock, Samson J. Koelle, Chuanfeng Wu, Cynthia E. Dunbar

Abstract: Clonal tracking methods provide quantitative insights into the cellular output of genetically labeled progenitor cells across time and cellular compartments. In the context of gene and cell therapies, clonal tracking methods have enabled the tracking of progenitor cell output both in humans receiving therapies and in corresponding animal models, providing valuable insight into lineage reconstitution, clonal dynamics and vector genotoxicity. However, the absence of a toolbox for analysis of clonal tracking data has precluded the development of standardized analytical frameworks within the field. Thus, we developed barcodetrackR, an R package and accompanying Shiny app containing diverse tools for the analysis and visualization of clonal tracking data. We demonstrate the utility of barcodetrackR in exploring longitudinal clonal patterns and lineage relationships in a number of clonal tracking studies of hematopoietic stem and progenitor cells (HSPCs) in humans receiving HSPC gene therapy and in animals receiving lentivirally transduced HSPC transplants or tumor cells. The R package barcodetrackR facilitates the analysis and visualization of clonal tracking data, and it includes a graphical user interface to allow researchers without programming experience to utilize various quantitative tools.

External IDs:dblp:journals/ncs/EspinozaMKWD21