SeqBBS: A change-point model based algorithm and R package for searching CNV regions via the ratio of sequencing reads

Hua Li, Jim Vallandingham, Jie Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publication2013 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2013 - Proceedings
Pages40-43
Number of pages4
DOIs
StatePublished - Dec 1 2013
Externally publishedYes
Event2013 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2013 - Houston, TX, United States
Duration: Nov 17 2013Nov 19 2013

Other

Other2013 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS 2013
CountryUnited States
CityHouston, TX
Period11/17/1311/19/13

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology (miscellaneous)
  • Computational Theory and Mathematics
  • Signal Processing
  • Biomedical Engineering

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