Evaluation of Somatic Copy Number Variation Detection by NGS Technologies and Bioinformatics Tools on a Hyper-diploid Cancer Genome

Overview

Journal Genome Biol

Specialties Biology
Genetics

Date 2024 Jun 20

PMID 38902799

Authors

Daniall Masood

Luyao Ren

Cu Nguyen

Francesco G Brundu

Lily Zheng

Yongmei Zhao

Erich Jaeger

Yong Li

Seong Won Cha

Aaron Halpern

Sean Truong

Michael Virata

Chunhua Yan

Qingrong Chen

Andy Pang

Reyes Alberto

Chunlin Xiao

Zhaowei Yang

Wanqiu Chen

Charles Wang

Frank Cross Jr

Severine Catreux

Leming Shi

Julia A Beaver

Wenming Xiao

Daoud M Meerzaman

Affiliations

Soon will be listed here.

Abstract

Background: Copy number variation (CNV) is a key genetic characteristic for cancer diagnostics and can be used as a biomarker for the selection of therapeutic treatments. Using data sets established in our previous study, we benchmark the performance of cancer CNV calling by six most recent and commonly used software tools on their detection accuracy, sensitivity, and reproducibility. In comparison to other orthogonal methods, such as microarray and Bionano, we also explore the consistency of CNV calling across different technologies on a challenging genome.

Results: While consistent results are observed for copy gain, loss, and loss of heterozygosity (LOH) calls across sequencing centers, CNV callers, and different technologies, variation of CNV calls are mostly affected by the determination of genome ploidy. Using consensus results from six CNV callers and confirmation from three orthogonal methods, we establish a high confident CNV call set for the reference cancer cell line (HCC1395).

Conclusions: NGS technologies and current bioinformatics tools can offer reliable results for detection of copy gain, loss, and LOH. However, when working with a hyper-diploid genome, some software tools can call excessive copy gain or loss due to inaccurate assessment of genome ploidy. With performance matrices on various experimental conditions, this study raises awareness within the cancer research community for the selection of sequencing platforms, sample preparation, sequencing coverage, and the choice of CNV detection tools.

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