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ChimericSeq: An open-source, user-friendly interface for analyzing NGS data to identify and characterize viral-host chimeric sequences.


ABSTRACT: Identification of viral integration sites has been important in understanding the pathogenesis and progression of diseases associated with particular viral infections. The advent of next-generation sequencing (NGS) has enabled researchers to understand the impact that viral integration has on the host, such as tumorigenesis. Current computational methods to analyze NGS data of virus-host junction sites have been limited in terms of their accessibility to a broad user base. In this study, we developed a software application (named ChimericSeq), that is the first program of its kind to offer a graphical user interface, compatibility with both Windows and Mac operating systems, and optimized for effectively identifying and annotating virus-host chimeric reads within NGS data. In addition, ChimericSeq's pipeline implements custom filtering to remove artifacts and detect reads with quantitative analytical reporting to provide functional significance to discovered integration sites. The improved accessibility of ChimericSeq through a GUI interface in both Windows and Mac has potential to expand NGS analytical support to a broader spectrum of the scientific community.

SUBMITTER: Shieh FS 

PROVIDER: S-EPMC5567911 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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ChimericSeq: An open-source, user-friendly interface for analyzing NGS data to identify and characterize viral-host chimeric sequences.

Shieh Fwu-Shan FS   Jongeneel Patrick P   Steffen Jamin D JD   Lin Selena S   Jain Surbhi S   Song Wei W   Su Ying-Hsiu YH  

PloS one 20170822 8


Identification of viral integration sites has been important in understanding the pathogenesis and progression of diseases associated with particular viral infections. The advent of next-generation sequencing (NGS) has enabled researchers to understand the impact that viral integration has on the host, such as tumorigenesis. Current computational methods to analyze NGS data of virus-host junction sites have been limited in terms of their accessibility to a broad user base. In this study, we deve  ...[more]

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