![]() ![]() The main steps involve using a normal mixture model to cluster samples into different groups, followed by simple kernel-based approaches to maximize information obtained from read-depth and split-read approaches, after which common breakpoints of groups are inferred. The pipeline combines read-depth and split-read information to infer breakpoints, using information from multiple samples to allow an imputation approach to be taken. Here, based on HTS data, we have developed a pipeline to identify approximate breakpoints (☑0 bp) relating to different ancestral events within a specific CNVR. It has been shown, however, that pipelines which integrate multiple approaches are able to report more reliable breakpoints. Various approaches have been proposed for detecting CNV breakpoints, but currently it is still challenging for tools based on a single analysis method to identify breakpoints of CNVs. This helps in understanding genome structure as well as their evolution process. High-throughput sequencing (HTS) technologies facilitate the detection of copy-number variable regions (CNVRs) and their breakpoints. 4Department of Mathematics, Cao Thang College of Technology, Ho Chi Minh City, VietnamĬopy-number variation (CNV) has been associated with increased risk of complex diseases.3Department of Psychiatry, Mount Sinai School of Medicine, New York, NY, USA. ![]() 2Virtual Institute of Statistical Genetics, Dunedin, New Zealand.1Department of Biochemistry, University of Otago, Dunedin, New Zealand. ![]()
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