DeviCNV: detection and visualization of exon-level copy number variants in targeted next-generation sequencing data.

ABSTRACT:

Background

Targeted next-generation sequencing (NGS) is increasingly being adopted in clinical laboratories for genomic diagnostic tests.

Results

We developed a new computational method, DeviCNV, intended for the detection of exon-level copy number variants (CNVs) in targeted NGS data. DeviCNV builds linear regression models with bootstrapping for every probe to capture the relationship between read depth of an individual probe and the median of read depth values of all probes in the sample. From the regression models, it estimates the read depth ratio of the observed and predicted read depth with confidence interval for each probe which is applied to a circular binary segmentation (CBS) algorithm to obtain CNV candidates. Then, it assigns confidence scores to those candidat

SUBMITTER: Kang Y 

PROVIDER: S-EPMC6192323 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature