A dynamic pooling approach to extract complete allele signal information in somatic copy number alternations detection

Long Cheng, Pengfei Yao, Jianwei Lu, Ke Hao, Zhongyang Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Accurately characterizing somatic copy number alterations (SCNAs) in cancers are of great importance in both deciphering tumorigenesis and progression and improving clinical diagnosis/treatment. Many computational methods in detecting SCNAs were proposed in recent years, and saas-CNV is among the best performers evaluated with empirical datasets. However, saas-CNV method inefficiently uses the allele dosage information in next-generation sequencing or microarray data. To this regard, we proposed and implemented a novel approach to extract the complete allele signal information for SCNA detection. Evaluated in an empirical dataset of hepatocellular carcinoma, we demonstrated the novel approach enhanced data signal-to-noise ratio, and resulted in improved detection of copy number alternations especially focal genome changes.

Original languageEnglish
Title of host publicationProceedings of 2018 6th International Conference on Bioinformatics and Computational Biology, ICBCB 2018
PublisherAssociation for Computing Machinery
Pages1-6
Number of pages6
ISBN (Electronic)9781450363488
DOIs
StatePublished - 12 Mar 2018
Event6th International Conference on Bioinformatics and Computational Biology, ICBCB 2018 - Chengdu, China
Duration: 12 Mar 201814 Mar 2018

Publication series

NameACM International Conference Proceeding Series

Conference

Conference6th International Conference on Bioinformatics and Computational Biology, ICBCB 2018
Country/TerritoryChina
CityChengdu
Period12/03/1814/03/18

Keywords

  • Complete allele signal information
  • Dynamic pooling
  • Joint segmentation
  • Signal-to-noise ratio
  • Somatic copy number alternations

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