• Journal of Life Science
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• v.25 no.3
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• pp.357-367
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• 2015

With the ongoing development of next-generation sequencing (NGS) platforms and advancements in the latest bioinformatics tools at an unprecedented pace, the ultimate goal of sequencing the human genome for less than $1,000 can be feasible in the near future. The rapid technological advances in NGS have brought about increasing demands for statistical methods and bioinformatics tools for the analysis and management of NGS data. Even in the early stages of the commercial availability of NGS platforms, a large number of applications or tools already existed for analyzing, interpreting, and visualizing NGS data. However, the availability of this plethora of NGS data presents a significant challenge for storage, analyses, and data management. Intrinsically, the analysis of NGS data includes the alignment of sequence reads to a reference, base-calling, and/or polymorphism detection, de novo assembly from paired or unpaired reads, structural variant detection, and genome browsing. While the NGS technologies have allowed a massive increase in available raw sequence data, a number of new informatics challenges and difficulties must be addressed to improve the current state and fulfill the promise of genome research. This review aims to provide an overview of major NGS technologies and bioinformatics tools for NGS data analyses.

• Journal of Life Science
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• v.31 no.4
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• pp.410-417
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• 2021

Next-generation sequencing (NGS) is a high-throughput technique for sequencing large numbers of DNA fragments that are prepared from a genome. This sequencing technique has been used to elucidate whole genome sequences of living organisms and to analyze complementary DNA (cDNA) or chromatin immunoprecipitated DNA (ChIPed DNA) at the genome level. After NGS, the use of proper tools is important for processing and analyzing data with reasonable parameters. However, handling large-scale sequencing data and programing for data analysis can be difficult. The Galaxy platform, a public web service system, provides many different tools for NGS data analysis, and it allows researchers to analyze their data on a web browser with no deep knowledge about bioinformatics and/or programing. In this study, we explain the procedure for preparing chromatin immunoprecipitation-sequencing (ChIP-seq) libraries and steps for analyzing ChIP-seq data using the Galaxy platform. The data analysis steps include the NGS data upload to Galaxy, quality check of the NGS data, premapping processes, read mapping, the post-mapping process, peak-calling and visualization by window view, heatmaps, average profile, and correlation analysis. Analysis of our histone H3K4me1 ChIP-seq data in K562 cells shows that it correlates with public data. Thus, NGS data analysis using the Galaxy platform can provide an easy approach to bioinformatics.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.2
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• pp.107-112
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• 2013

With the progress of NGS technologies, large genome data have been exploded recently. To analyze such data effectively, the assistance of HPC technique is necessary. In this paper, we organized a genome analysis pipeline to call SNP from NGS data. To organize the pipeline efficiently under HPC environment, we analyzed the CPU utilization pattern of each pipeline steps. We found that sequence alignment is computing centric and suitable for parallelization. We also analyzed the performance of parallel open source alignment tools and found that alignment method utilizing many-core processor can improve the performance of genome analysis pipeline.

• Korean Journal of Ecology and Environment
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• v.54 no.3
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• pp.257-264
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• 2021

In this study, we analyzed the food components in the release product that sampled Sinonovacula constricta from the foreshore littoral at Byeongnyang-myeon, Suncheon Bay. We used microscopy and next-generation sequencing (NGS) to evaluate the applicability of morphological and molecular methods to analyze release products. The higher species diversity observed in the NGS method is due to the different levels of species identification, as microscopy displays morphological and anatomical levels of plankton species identification in S. constrita. Moreover, NGS can identify the level of species in the organic matter by using the 18s_V9 primer.

• Development and Reproduction
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• v.27 no.1
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• pp.47-56
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• 2023

Despite the commercialization of Next generation sequencing (NGS) gene testing, only a few studies have addressed the various ethical and legal problems associated with NGS testing in Korea Here, we reviewed the normative issues that emerged at each stage of the wet analysis and bioinformatics analysis of NGS gene testing. In particular, it was in mind to apply various international guidelines and the principles of bioethics to actual clinical practice. Considering the characteristics of NGS testing, wet analysis of additional testing can be justified if presumptive consent is recognized. Furthermore, the medical relationship between diseases needs to be established and it should be clear that the patient would have given consent if the patient had been aware of the correlation between genes. At the stage of bioinformatics analysis, the question of unsolicited findings arises. In case of unsolicited and relevant findings, according to American College of Medical Genetics and Genomics (ACMG), a recognized relationship between genes and diseases needs to be established. In case of unsolicited and not-relevant findings, it is almost impossible to determine whether knowing or not knowing the findings is more beneficial to the patient. However, it seems to be certain that the psychological harm an individual may suffer from such information is likely to be greater if the disease is severe and if there is no cure. The list of genes for which the ACMG guidelines impose reporting obligations is a good reference for judgment.

• ALGAE
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• v.31 no.2
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• pp.137-154
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• 2016

Next generation sequencing (NGS) technologies have revolutionized many areas of biological research due to the sharp reduction in costs that has led to the generation of massive amounts of sequence information. Analysis of large genome data sets is however still a challenging task because it often requires significant computer resources and knowledge of bioinformatics. Here, we provide a guide for an uninitiated who wish to analyze high-throughput NGS data. We focus specifically on the analysis of organelle genome and metagenome data and describe the current bioinformatic pipelines suited for this purpose.

• Journal of Marine Life Science
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• v.3 no.2
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• pp.51-58
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• 2018

Variations in water temperature are known to affect almost every part of fish physiology. The rise in water temperature due to climate change can physically damage fish. This study was conducted to evaluate the health status of the Atlantic salmon (Salmo salar) at high water temperature (20℃) than the optimum water temperature (15℃). Liver tissue exerts important metabolic functions in thermal adaptation. Therefore, liver tissue was used in this study. The evaluation method is to develop the biomarker gene using NGS RNAseq analysis and to examine the expression pattern using RT-qPCR analysis. The NGS RNAseq analysis revealed 1,366 differentially expressed genes, among which 880 genes were increase expressed and 486 genes were decrease expressed. The biomarker genes are such as heat shock protein 90 alpha (Hsp90α), heat shock protein 90 beta (Hsp90β) and cytochrome P450 1A (CYP1A). The selected genes are sensitive to changes in water temperature through NGS RNAseq analysis. Expression patterns of these genes through RT-qPCR were similar to those of NGS RNAseq analysis. The results of this study can be applied to other fish species and it is considered to be useful industrially.

• The Korean Journal of Blood Transfusion
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• v.29 no.3
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• pp.310-319
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• 2018

Background: Research on next-generation sequencing (NGS)-based HLA typing is active. To resolve the phase ambiguity and long turn-around-time of conventional high resolution HLA typing, this study developed a NGS-based high resolution HLA typing method that can handle large-scale samples within an efficient testing time. Methods: For HLA NGS, the condition of nucleic acid extraction, library construction, PCR mechanism, and HLA typing with bioinformatics were developed. To confirm the accuracy of the NGS-based HLA typing method, the results of 192 samples HLA typed by SSOP and 28 samples typed by SBT compared to NGS-based HLA-A, -B and -DR typing. Results: DNA library construction through two-step PCR, NGS sequencing with MiSeq (Illumina Inc., San Diego, USA), and the data analysis platform were established. NGS-based HLA typing results were compatible with known HLA types from 220 blood samples. Conclusion: The NSG-based HLA typing method could handle large volume samples with high-throughput. Therefore, it would be useful for HLA typing of bone marrow donation volunteers.

• Plant Breeding and Biotechnology
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• v.5 no.4
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• pp.269-281
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• 2017

With the continual development of genetically modified (GM) crops, it has become necessary to develop detailed and effective molecular characterization methods to select candidate events from a large pool of transformation events. Relative to traditional molecular analysis methods such as the polymerase chain reaction (PCR) and Southern blot hybridization, next generation sequencing (NGS) technology for whole-genome sequencing of complex crop genomes had proven comparatively useful for in-depth molecular characterization. In this study, four transformation events, including one in Bacillus thuringiensis (Bt)-resistant rice, one in resveratrol-producing rice, and two in beta-carotene-enhanced soybeans, were selected for molecular characterization. To merge NGS analysis and Southern blot-hybridization results, we confirmed the transgene insertion sites, insertion construction, and insertion numbers of these four transformation events. In addition, the read-coverage depth assessed by NGS analysis for inserted genes might provide consistent results in terms of inserted T-DNA numbers in case of complex insertion structures and highly duplicated donor genomes; however, PCR-based methods can produce incorrect conclusions. Our combined method provides an effective and complete analytical approach for whole-genome visual inspection of transformation events that require biosafety assessment.

• International Journal of Contents
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• v.14 no.1
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• pp.34-38
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• 2018

With the rapid growth of genomic data, new requirements have emerged that are difficult to handle with big data storage and analysis techniques. Regardless of the size of an organization performing genomic data analysis, it is becoming increasingly difficult for an institution to build a computing environment for storing and analyzing genomic data. Recently, cloud computing has emerged as a computing environment that meets these new requirements. In this paper, we analyze and compare existing distributed and parallel NGS (Next Generation Sequencing) analysis based on cloud computing environment for future research.