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Next-generation sequencing (NGS) technologies have produced large volumes ofgenomic data. One common operation on heterogeneous genomic data is genomicinterval intersection. Most of the existing tools impose restrictions such asnot allowing nested intervals or requiring intervals to be sorted when findingoverlaps in two or more interval sets. We proposed segment tree (ST) andindexed segment tree forest (ISTF) based solutions for intersection of multiplegenomic interval sets in parallel. We developed these methods as a tool, JointOverlap Analysis (JOA), which takes n interval sets and finds overlappingintervals with no constraints on the given intervals. The proposed indexedsegment tree forest is a novel composite data structure, which leverages onindexing and natural binning of a segment tree. We also presented constructionand search algorithms for this novel data structure. We compared JOA ST and JOAISTF with each other, and with other interval intersection tools forverification of its correctness and for showing that it attains comparableexecution times. We implemented JOA in Java using the fork/join framework whichspeeds up parallel processing by taking advantage of all available processorcores. We compared JOA ST with JOA ISTF and showed that segment tree andindexed segment tree forest methods are comparable with each other in terms ofexecution time and memory usage. We also carried out execution time comparisonanalysis for JOA and other tools and demonstrated that JOA has comparableexecution time and is able to further reduce its running time by using moreprocessors per node. JOA can be run using its GUI or as a command line tool.JOA is available with source code at https://github.com/burcakotlu/JOA/. A usermanual is provided at https://joa.readthedocs.org

Joint Overlap Analysis of Multiple Genomic Interval Sets