Accurate identification of structural variations from cancer samples
Publication in refereed journal

替代計量分析
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其它資訊
摘要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.
出版社接受日期18.12.2023
著者Le 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
期刊名稱Briefings in Bioinformatics
出版年份2024
月份1
卷號25
期次1
出版社Oxford University Press
文章號碼bbad520
國際標準期刊號1467-5463
電子國際標準期刊號1477-4054
語言美式英語

上次更新時間 2024-16-10 於 14:12