Base J is a glycosylated nucleobase found in Trypanosomatids, a family of single celled parasites causing Sleeping Sickness, Chagas Disease, and Leishmaniasis. This modified base is thought to play an important role in transcriptional termination for these organisms. Current methods of analyzing Base J rely solely on chromatin immunoprecipitation experiments, which provide low resolution information pertaining to Base J positions. While previous studies have shown that SMRT-seq interpulse duration (IPD) is associated with the position of Base J, we still lack methods to use this information to produce a genome wide, nucleotide-level map of Base J. Here we explore analytical approaches such as dimensionality reduction, machine learning, and signal processing to determine patterns of IPD and DNA enrichment which correspond to Base J across the entire Leishmania tarentolae genome. We show that many simplified approaches such as peak calling, and dimensionality reduction do not contain enough information to accurately classify Base J. We also utilize signal decomposition with Fourier transforms, machine learning clustering and regression methods to provide a more complex treatment of the data. Our findings are an important step in producing an algorithmic approach to identifying precise locations of Base J and can yield insight into transcriptional regulation in Trypanosomatids.