논문 (학술지)
NGSpop: A desktop software that supports population studies by identifying sequence variations from next-generation sequencing data
등록번호 | - | SCI 구분
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※구분 : SCI(SCIE포함), 비SCI |
SCI |
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저자명 (주·공동저자) | 이동준; 이태호; 김진현; 권태수; 이혜진; 오윤호 ※ 과제 참여정보와 일치하는 연구자 상세정보로 정확하지 않을 수 있습니다. 동일저자 논문보기 |
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논문구분 | 국외전문학술지 | 학술지명 | PLoS One |
ISSN | 1932-6203 | 학술지 출판일자 | 2022-11-17 |
학술지 볼륨번호 | 1(2) | 논문페이지 | 10 ~ 20 |
학술지 임팩트팩터 | 3.24 | 기여율 | 100 % |
DOI | https://doi.org/10.1371/journal.pone.0260908 | ||
초록 | Next-generation sequencing (NGS) is widely used in all areas of genetic research, such as for genetic disease diagnosis and breeding, and it can produce massive amounts of data. The identification of sequence variants is an important step when processing large NGS datasets; however, currently, the process is complicated, repetitive, and requires concentration, which can be taxing on the researcher. Therefore, to support researchers who are not familiar with bioinformatics in identifying sequence variations regularly from large datasets, we have developed a fully automated desktop software, NGSpop. NGSpop includes functionalities for all the variant call and visualization procedures used when processing NGS data, such as quality control, mapping, filtering details, and variant calling. In the variant calling step, the user can select the GATK or DeepVariant algorithm for variant calling. These algorithms can be executed using pre-set pipelines and options or customized with the user-specified options. NGSpop is implemented using JavaFX (version 1.8) and can thus be run on Unix like operating systems such as Ubuntu Linux (version 16.04, 18.0.4). Although there are several pipelines and visualization tools available for NGS data analysis, most integrated environments do not support batch processes; thus, variant detection cannot be automated for population-level studies. The NGSpop software, developed in this study, has an easy-to-use interface and helps in rapid analysis of multiple NGS data from population studies. |
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