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NGS_SNPAnalyzer: a desktop software supporting genome projects by identifying and visualizing sequence variations from next-generation sequencing data

Genes & Genomics 2020년 42권 11호 p.1311 ~ 1317
이동준, Kwon Tae-Soo, 김창국, 설영주, 박동석, Lee Tae-Ho, 안병옥,
소속 상세정보
이동준 ( Lee Dong-Jun ) - National Institute of Agricultural Science Genomics Division
 ( Kwon Tae-Soo ) - Seoul National University Interdisciplinary Program in Bioinformatics
김창국 ( Kim Chang-Kug ) - National Institute of Agricultural Science Genomics Division
설영주 ( Seol Young-Joo ) - National Institute of Agricultural Science Gene Engineering Division
박동석 ( Park Dong-Suk ) - National Institute of Agricultural Science Genomics Division
 ( Lee Tae-Ho ) - National Institute of Agricultural Science Genomics Division
안병옥 ( Ahn Byung-Ohg ) - National Institute of Agricultural Science Genomics Division

Abstract


Background: Sequence variations such as single nucleotide polymorphisms are markers for genetic diseases and breeding. Therefore, identifying sequence variations is one of the main objectives of several genome projects. Although most genome project consortiums provide standard operation procedures for sequence variation detection methods, there may be differences in the results because of human selection or error.

Objective: To standardize the procedure for sequence variation detection and help researchers who are not formally trained in bioinformatics, we developed the NGS_SNPAnalyzer, a desktop software and fully automated graphical pipeline.

Methods: The NGS_SNPAnalyzer is implemented using JavaFX (version 1.8); therefore, it is not limited to any operating system (OS). The tools employed in the NGS_SNPAnalyzer were compiled on Microsoft Windows (version 7, 10) and Ubuntu Linux (version 16.04, 17.0.4).

Results: The NGS_SNPAnalyzer not only includes the functionalities for variant calling and annotation but also provides quality control, mapping, and filtering details to support all procedures from next-generation sequencing (NGS) data to variant visualization. It can be executed using pre-set pipelines and options and customized via user-specified options. Additionally, the NGS_SNPAnalyzer provides a user-friendly graphical interface and can be installed on any OS that supports JAVA.

Conclusions: Although there are several pipelines and visualization tools available for NGS data analysis, we developed the NGS_SNPAnalyzer to provide the user with an easy-to-use interface. The benchmark test results indicate that the NGS_SNPAnayzer achieves better performance than other open source tools.

키워드

Next-generation sequencing; Whole-genome sequencing; Variant identification; Genomics; Pipeline

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