Structural variants (SVs) are genomic segments of more than 50 bp that have been rearranged in the genome. The advent of third generation sequencing technologies has increased and enhanced their study, and a great number of SVs has already been discovered in the human genome. Complementary to their discovery, the genotyping of known SVs in newly sequenced individuals is of particular interest for several applications such as trait association and clinical diagnosis. Most of the SV genotypers currently available are designed for second generation sequencing data, although third generation sequencing data is more suited to study SVs due to their large range of sizes (up to few mega bases). As such, our team previously released SVJedi, the first SV genotyper dedicated to long read data[1]. The method is based on linear representations of the allelic sequences of each SV and each SV is represented and genotyped independently of the other ones. While this is very efficient for distant SVs, the method fails to genotype some closely located or overlapping SVs due to redundancy in representative allelic sequences.