A Density Peak-Based Method to Detect Copy Number Variations From Next-Generation Sequencing Data.

ABSTRACT: Copy number variation (CNV) is a common type of structural variations in human genome and confers biological meanings to human complex diseases. Detection of CNVs is an important step for a systematic analysis of CNVs in medical research of complex diseases. The recent development of next-generation sequencing (NGS) platforms provides unprecedented opportunities for the detection of CNVs at a base-level resolution. However, due to the intrinsic characteristics behind NGS data, accurate detection of CNVs is still a challenging task. In this article, we propose a new density peak-based method, called dpCNV, for the detection of CNVs from NGS data. The algorithm of dpCNV is designed based on density peak clustering algorithm. It extracts two features, i.e., local density and minimum distance,

SUBMITTER: Xie K 

PROVIDER: S-EPMC7838601 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature