BreakDancer is an algorithm designed to detect and characterize genomic structural variations, including indels, inversions, and translocations. The algorithm consists of two complementary components: BreakDancerMax and BreakDancerMini. BreakDancerMax identifies a wide range of structural variants, while BreakDancerMini focuses on detecting small indels (10-100 bp) that are often missed by BreakDancerMax. The performance of BreakDancer was evaluated through simulations, comparisons with other methods, and real data analysis, including an acute myeloid leukemia sample and the 1,000 Genomes trio individuals. The results showed that BreakDancer significantly improved the detection of small and intermediate-sized indels, with a substantial reduction in false positives. The algorithm's performance was also compared with other structural variant detection tools, showing comparable or better accuracy in detecting large fosmid deletions and known deletion polymorphisms. In a tumor-normal paired study, BreakDancer enhanced the specificity of somatic variant prediction by effectively eliminating inherited variants. The study highlights the potential of BreakDancer for high-resolution mapping of genomic structural variations, particularly in complex diseases such as cancer.BreakDancer is an algorithm designed to detect and characterize genomic structural variations, including indels, inversions, and translocations. The algorithm consists of two complementary components: BreakDancerMax and BreakDancerMini. BreakDancerMax identifies a wide range of structural variants, while BreakDancerMini focuses on detecting small indels (10-100 bp) that are often missed by BreakDancerMax. The performance of BreakDancer was evaluated through simulations, comparisons with other methods, and real data analysis, including an acute myeloid leukemia sample and the 1,000 Genomes trio individuals. The results showed that BreakDancer significantly improved the detection of small and intermediate-sized indels, with a substantial reduction in false positives. The algorithm's performance was also compared with other structural variant detection tools, showing comparable or better accuracy in detecting large fosmid deletions and known deletion polymorphisms. In a tumor-normal paired study, BreakDancer enhanced the specificity of somatic variant prediction by effectively eliminating inherited variants. The study highlights the potential of BreakDancer for high-resolution mapping of genomic structural variations, particularly in complex diseases such as cancer.