The data stored here were used for benchmarking long-read structural variant (SV) callers in the publication: Tham, CY., Tirado-Magallanes, R., Goh, Y. et al. NanoVar: accurate characterization of patients’ genomic structural variants using low-depth nanopore sequencing. Genome Biol 21, 56 (2020). https://doi.org/10.1186/s13059-020-01968-7 The data consist of six simulated SV genomes generated using various open source tools and comprise also of simulated long-read FASTA files and ground truth SV information. More information can be found in the README.md.

{"references": ["Bartenhagen, C. & Dugas, M. RSVSim: an R/Bioconductor package for the simulation of structural variations. Bioinformatics 29, 1679\u20131681 (2013).", "Yang, C., Chu, J., Warren, R. L. & Birol, I. NanoSim: nanopore sequence read simulator based on statistical characterization. Gigascience 6, 1\u20136 (2017)."]}