DTDHM: detection of tandem duplications based on hybrid methods using next-generation sequencing data.

ABSTRACT:

Background

Tandem duplication (TD) is a common and important type of structural variation in the human genome. TDs have been shown to play an essential role in many diseases, including cancer. However, it is difficult to accurately detect TDs due to the uneven distribution of reads and the inherent complexity of next-generation sequencing (NGS) data.

Methods

This article proposes a method called DTDHM (detection of tandem duplications based on hybrid methods), which utilizes NGS data to detect TDs in a single sample. DTDHM builds a pipeline that integrates read depth (RD), split read (SR), and paired-end mapping (PEM) signals. To solve the problem of uneven distribution of normal and abnormal samples, DTDHM uses the K-nearest neighbor (KNN) algorithm for multi-feature classi

SUBMITTER: Yuan T 

PROVIDER: S-EPMC11285389 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature