Genomic structural variations are closely associated with the evolution of diverse biological traits and the manifestation of severe disease phenotypes. Research on variations in various genetic diseases and cancers requires genome-wide comparative analysis of genomic variations across multiple samples to identify de novo and somatic structural variants truly associated with disease progression. Currently, commonly used stepwise strategies in the field, such as "detect-then-compare," involve multiple computational steps after genome detection. The complexity of these multistep processes can lead to rapid accumulation of errors and high false positives, making it challenging to accurately decipher de novo and somatic structural variations.

To address this challenge, Professor Ye Kai's team from Xi'an Jiaotong University (XJTU) recently made breakthroughs in the identification of de novo and somatic structural variations. Their related research achievement, titled "De novo and somatic structural variant discovery with SVision-pro," was published on March 22, 2024 in the journal Nature Biotechnology.

This marks yet another achievement in interdisciplinary collaboration at XJTU's Biomedical Informatics and Genomics Research Center.

Wang Songbo, a doctoral student at the School of Telecommunications and Automation Engineering, is the first author of the paper, with Professor Ye Kai as the sole corresponding author.