Accurate identification of structural variations from cancer samples
Publication in refereed journal
CUHK Authors
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AbstractStructural 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.
Acceptance Date18/12/2023
All Author(s) ListLe Li, Chenyang Hong, Jie Xu, Claire Yik-Lok Chung, Alden King-Yung Leung, Delbert Almerick T Boncan, Lixin Cheng, Kwok-Wai Lo, Paul BS Lai, John Wong, Jingying Zhou, Alfred Sze-Lok Cheng, Ting-Fung Chan, Feng Yue, Kevin Y Yip
Journal nameBriefings in Bioinformatics
Year2024
Month1
Volume Number25
Issue Number1
PublisherOxford University Press
Article numberbbad520
ISSN1467-5463
eISSN1477-4054
LanguagesEnglish-United States
