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PocaCNV: A Tool to Detect Copy Number Variants from Population-Scale Genome Sequencing Data

  • School of Computer Science and Technology, Harbin Institute of Technology

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

Abstract

Among the procedures of modern genome analysis, the variation calling is a crucial part. Copy Number Variation(CNV) is an important variation type, many algorithms are developed to detect them. As the scale of samples in genome projects growing, it's wise to use data from multiple samples jointly to call variants. We present PocaCNV, a population caller of CNVs that can call CNVs from multiple samples of the same population. PocaCNV can produce many unique results with good precision and sensitivity, and can be a good supplement to other modern SV calling procedures. PocaCNV can be openly accessed from https://github.com/CoREse/PocaCNV.

Original languageEnglish
Title of host publicationProceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021
EditorsYufei Huang, Lukasz Kurgan, Feng Luo, Xiaohua Tony Hu, Yidong Chen, Edward Dougherty, Andrzej Kloczkowski, Yaohang Li
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1912-1918
Number of pages7
ISBN (Electronic)9781665401265
DOIs
StatePublished - 2021
Externally publishedYes
Event2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021 - Virtual, Online, United States
Duration: 9 Dec 202112 Dec 2021

Publication series

NameProceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021

Conference

Conference2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021
Country/TerritoryUnited States
CityVirtual, Online
Period9/12/2112/12/21

Keywords

  • NGS data
  • copy number variant
  • variant detection

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