Structural variants (SVs) are the hidden architecture of the human genome, and are critical for us to understand diseases, evolution, and so on. The development of both sequencing technologies and... Show moreStructural variants (SVs) are the hidden architecture of the human genome, and are critical for us to understand diseases, evolution, and so on. The development of both sequencing technologies and computational tools greatly facilitates the detection of SVs, while misinterpreting or even missing complex ones. Detecting and characterizing complex events is a typical field requiring multiple disciplines, i.e., domain knowledge and computer science algorithms. In this thesis, we introduce novel algorithms to detect and validate com- plex events, and assess the reproducibility of current SV detection pipelines for clinical and research settings. Show less
