Comprehensive assessment of long-read sequencing platforms and calling algorithms for detection of copy number variation.

ABSTRACT: Copy number variations (CNVs) play pivotal roles in disease susceptibility and have been intensively investigated in human disease studies. Long-read sequencing technologies offer opportunities for comprehensive structural variation (SV) detection, and numerous methodologies have been developed recently. Consequently, there is a pressing need to assess these methods and aid researchers in selecting appropriate techniques for CNV detection using long-read sequencing. Hence, we conducted an evaluation of eight CNV calling methods across 22 datasets from nine publicly available samples and 15 simulated datasets, covering multiple sequencing platforms. The overall performance of CNV callers varied substantially and was influenced by the input dataset type, sequencing depth, and CNV type, among

SUBMITTER: Yuan N 

PROVIDER: S-EPMC11387058 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature