DNA Structural variation Tools

CNVkit is a software toolkit to infer and visualize copy number from targeted DNA sequencing data.

A tool for control-free copy number alteration (CNA) and allelic imbalances (LOH) detection using deep-sequencing data, particularly useful for cancer studies.

Integrated structural variant prediction method that can discover, genotype and visualize deletions, tandem duplications, inversions and translocations at single-nucleotide resolution in short-read massively parallel sequencing data. It uses paired-ends and split-reads to sensitively and accurately delineate genomic rearrangements throughout the genome. Structural variants can be visualized using Delly-maze and Delly-suave.

Automated identification of insertion sequence elements in prokaryotic genomes.

Calls structural variants (SVs) and indels from mapped paired-end sequencing reads.

An algorithm for structural variation detection from third generation sequencing alignment.

Long Read based Human Genomic Structural Variation Detection with cuteSV | Long-read sequencing technologies enable to comprehensively discover structural variations (SVs). However, it is still non-trivial for state-of-the-art approaches to detect SVs with high sensitivity or high performance or both. Herein, we propose cuteSV, a sensitive, fast and lightweight SV detection approach. cuteSV uses tailored methods to comprehensively collect various types of SV signatures, and a clustering-and-refinement method to implement a stepwise SV detection, which enables to achieve high sensitivity without loss of accuracy. Benchmark results demonstrate that cuteSV has better yields on real datasets. Further, its speed and scalability are outstanding and promising to large-scale data analysis