ABSTRACT
Structural variation (SV) is a vital part of biological genetic diversity. The simulation and identification with high efficiency and accuracy are considered to be very important. With the continuous development and wide application of various technologies, computer simulation of genomic data has attracted wide attention due to its intuitive and convenient advantages. Meanwhile, there are several high-quality methods used for structural variation identification based on second-generation (short-read) and third-generation (long-read) data. These methods utilize various strategies and compatible aligners and exhibit specific characteristics. In addition, genomic visualization tools use graphical interfaces to visualize the data, which are convenient for data observation, validation, and even for the manual curation of several questionable data. The present study summarized the methods of simulation, identification, and visualization tools for structural variation in the context of sequencing technology development. Overall, this review aimed to offer a more comprehensive understanding of the impact of SV.
