Background and Objective Identification of chromosomal translocations has been historically important in elucidating evolutionary distinctions and diagnosing numerous genetic disorders. Current methods of translocation identification center on multi-color fluorescence in-situ hybridization (FISH). This provides a cost-effective, genome-wide method to screen translocations. However, FISH is limited by its inability to detect low-resolution translocations with high specificity and sensitivity, and its time efficiency is restricted by the researcher having prior knowledge of the abnormality. Computational approaches comparing sequenced genomes have shown promise in identifying low-resolution chromosomal translocations. Nevertheless, the practicality of such techniques are limited by the time and resource requirements of a high computational burden. Methods The authors developed a novel computational approach to detect translocations between members of the primate order via genomic examination of Short Interspersed Nuclear Elements (SINEs). Phylogenetic literature has validated SINEs as an effective tool for making accurate evolutionary distinctions. Specific SINEs, such as the Alu family of transposable elements, are widely conserved among primate species and exhibit unidirectional and homoplasy-free evolution. This investigation employs Smith-Waterman string distances to determine conserved SINEs across species, allowing their analysis to serve as a robust measure of loci-specific chromosome sequence homology between related species. Results The technique allowed for clear and quantitative detection of patterns displaying chromosomal translocations. Translocation events were analyzed between the Chimpanzee chromosome 3 (panTro4) and the Green Monkey (chlSab2) reference genome. In total, previously published literature utilizing chromosomal painting in conjunction with comparison of whole genome assemblies had identified 8 distinct discontinuities greater than 5 megabase pairs (Mbp), each corresponding to a translocation or change in orientation of the synteny. These translocations were validated using the novel SINE-based methodology, and each reported translocation or change in orientation was detected with a minimum z-score of 2.5 (p < 0.007) and regularly above 4 (p < 1e-4). The authors further tested the novel method by expanding to include translocations between the panTro4 chromosome 3 and the gorGor4 and Marmoset (calJac3) genomes as well. The novel method additionally identified every reported translocation or change in orientation greater than 5 Mbp in this set with a similar p value threshold. Conclusion These results show that in a limited sample, the novel methodology analyzing string distances can detect relatively low-resolution translocations with the same specificity and sensitivity of chromosomal painting in conjunction with comparison of whole genome assemblies. Further work needs to be done to determine whether this accuracy is maintained when comparing other species in the order Primates and to ascertain the exact resolution at which this technique can no longer reliably detect translocations as accurately as more resource-intensive techniques.