OTSUCNV: an adaptive segmentation and OTSU-based anomaly classification method for CNV detection using NGS data.

ABSTRACT: Copy-number variations (CNVs), which refer to deletions and duplications of chromosomal segments, represent a significant source of variation among individuals, contributing to human evolution and being implicated in various diseases ranging from mental illness and developmental disorders to cancer. Despite the development of several methods for detecting copy number variations based on next-generation sequencing (NGS) data, achieving robust detection performance for CNVs with arbitrary coverage and amplitude remains challenging due to the inherent complexity of sequencing samples. In this paper, we propose an alternative method called OTSUCNV for CNV detection on whole genome sequencing (WGS) data. This method utilizes a newly designed adaptive sequence segmentation algorithm and an OTSU-

SUBMITTER: Xie K 

PROVIDER: S-EPMC10826217 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature