SeqBBS: a change-point model based algorithm and R package for searching CNV regions via the ratio of sequencing reads. Following the breakthrough of the microarray technology, the next generation sequencing (NGS) technology further advanced approaches in modern biomedical research. The high-throughput NGS technology is now frequently used in profiling tumor and control samples for the study of DNA copy number variants (CNVs). In particular, the ratio of read count of the tumor sample to that of the control sample is popularly used for identifying CNV regions. We illustrate that a change-point (or a breakpoint) detection method, along with a Bayesian approach, is particularly suitable for identifying CNVs in the reads ratio data. We have written our algorithm into a user friendly R-package, SeqBBS (stands for Bayesian breakpoints search for sequencing data) and applied our method to the sequencing data of reads ratio between the breast tumor cell lines HCC1954 and its matched normal cell line BL1954. Breakpoints that separate different CNV regions are successfully identified.
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References in zbMATH (referenced in 2 articles )
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- Lee, J.; Chen, J.: A modified information criterion for tuning parameter selection in 1d fused LASSO for inference on multiple change points (2020)
- Chen, Jie; Li, Hua: A statistical change-point analysis approach for modeling the ratio of next generation sequencing reads (2016)