Clinical next generation sequencing (NGS) typically relies on limited gene panels run on bulk marrow or blood. Current computational tools for inferring clonal relationships is generally limited by the use of a small panel of pathogenic mutations to define clones. We developed an online software (CloneTracker) that uses 'incidentally-sequenced' single nucleotide polymorphisms (SNPs) in the regions of recurrent somatic mutations in addition to conventional mutation data from bulk NGS gene panels to provide detailed visualizations of clonal evolution during cancer treatment, alongside clinical data. Tested on 29 patients who underwent non-myeloablative transplantation for AML, CloneTracker successfully reconstructed the evolutionary dynamics of donor engraftment from bulk NGS and rendered intuitive visualizations of residual patient-derived hematopoiesis and relapsing malignant clones. The software does not require sequencing donor samples, as donor-derived clones are identifiable from post-HCT SNP data. This manuscript aims to introduce CloneTracker to the BMT community and make it available for those who would ascertain its clinical utility, e.g, in BMT trials leveraging molecular minimal residual disease (MRD) monitoring and targeted interventions to pre-empt relapse.