Accurate Identification of Structural Variations from Cancer Samples

Overview

Journal Brief Bioinform

Publisher Oxford University Press

Specialty Biology

Date 2024 Jan 17

PMID 38233091

Authors

Le Li

Chenyang Hong

Jie Xu

Claire Yik-Lok Chung

Alden King-Yung Leung

Delbert Almerick T Boncan

Lixin Cheng

Kwok-Wai Lo

Paul B S Lai

John Wong

Jingying Zhou

Alfred Sze-Lok Cheng

Ting-Fung Chan

Feng Yue

Kevin Y Yip

Affiliations

Soon will be listed here.

Abstract

Structural variations (SVs) are commonly found in cancer genomes. They can cause gene amplification, deletion and fusion, among other functional consequences. With an average read length of hundreds of kilobases, nano-channel-based optical DNA mapping is powerful in detecting large SVs. However, existing SV calling methods are not tailored for cancer samples, which have special properties such as mixed cell types and sub-clones. Here we propose the Cancer Optical Mapping for detecting Structural Variations (COMSV) method that is specifically designed for cancer samples. It shows high sensitivity and specificity in benchmark comparisons. Applying to cancer cell lines and patient samples, COMSV identifies hundreds of novel SVs per sample.

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