DELLY is a structural variant (SV) discovery tool that integrates paired-end mapping and split-read analysis to detect SVs at single-nucleotide resolution. It can identify various types of SVs, including deletions, tandem duplications, inversions, and translocations, across a wide range of sizes. DELLY is particularly effective in detecting complex SVs that are not easily identified by split-read methods alone. The tool uses a combination of paired-end mapping and split-read analysis to improve both sensitivity and specificity. Paired-end mapping helps identify potential SVs by detecting discordantly mapped read pairs, while split-read analysis refines these calls by examining gapped alignments. DELLY constructs a graph of paired-end reads to identify potential SVs and then uses split-read data to precisely map breakpoints. The tool is validated on simulated data and real-world datasets, including the 1000 Genomes Project and cancer genomes, showing high specificity and accuracy. DELLY is available for use and has been shown to outperform other SV detection methods in terms of sensitivity and specificity. The method is suitable for a variety of sequencing data, including whole-genome sequencing and low-pass mate-pair sequencing. DELLY is a versatile tool for analyzing SVs in MPS data from various sources, including deep whole-genome sequencing and low-pass mate-pair sequencing. The tool is also applicable to exome capture data sequenced with paired-ends. DELLY's ability to integrate paired-end and split-read data makes it a powerful tool for analyzing SVs in a wide range of sequencing applications.DELLY is a structural variant (SV) discovery tool that integrates paired-end mapping and split-read analysis to detect SVs at single-nucleotide resolution. It can identify various types of SVs, including deletions, tandem duplications, inversions, and translocations, across a wide range of sizes. DELLY is particularly effective in detecting complex SVs that are not easily identified by split-read methods alone. The tool uses a combination of paired-end mapping and split-read analysis to improve both sensitivity and specificity. Paired-end mapping helps identify potential SVs by detecting discordantly mapped read pairs, while split-read analysis refines these calls by examining gapped alignments. DELLY constructs a graph of paired-end reads to identify potential SVs and then uses split-read data to precisely map breakpoints. The tool is validated on simulated data and real-world datasets, including the 1000 Genomes Project and cancer genomes, showing high specificity and accuracy. DELLY is available for use and has been shown to outperform other SV detection methods in terms of sensitivity and specificity. The method is suitable for a variety of sequencing data, including whole-genome sequencing and low-pass mate-pair sequencing. DELLY is a versatile tool for analyzing SVs in MPS data from various sources, including deep whole-genome sequencing and low-pass mate-pair sequencing. The tool is also applicable to exome capture data sequenced with paired-ends. DELLY's ability to integrate paired-end and split-read data makes it a powerful tool for analyzing SVs in a wide range of sequencing applications.