LSnet: detecting and genotyping deletions using deep learning network.

ABSTRACT: The role and biological impact of structural variation (SV) are increasingly evident. Deletion accounts for 40% of SV and is an important type of SV. Therefore, it is of great significance to detect and genotype deletions. At present, high accurate long reads can be obtained as HiFi reads. And, through a combination of error-prone long reads and high accurate short reads, we can also get accurate long reads. These accurate long reads are helpful for detecting and genotyping SVs. However, due to the complexity of genome and alignment information, detecting and genotyping SVs remain a challenging task. Here, we propose LSnet, an approach for detecting and genotyping deletions with a deep learning network. Because of the ability of deep learning to learn complex features in labeled datasets,

SUBMITTER: Luo J 

PROVIDER: S-EPMC10301831 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature