• Genomics & Informatics
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• v.16 no.4
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• pp.29.1-29.5
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• 2018

Hybrid capture-based targeted sequencing is being used increasingly for genomic variant profiling in tumor patients. Unique molecular index (UMI) technology has recently been developed and helps to increase the accuracy of variant calling by minimizing polymerase chain reaction biases and sequencing errors. However, UMI-adopted targeted sequencing data analysis is slightly different from the methods for other types of omics data, and its pipeline for variant calling is still being optimized in various study groups for their own purposes. Due to this provincial usage of tools, our group built an analysis pipeline for global application to many studies of targeted sequencing generated with different methods. First, we generated hybrid capture-based data using genomic DNA extracted from tumor tissues of colorectal cancer patients. Sequencing libraries were prepared and pooled together, and an 8-plexed capture library was processed to the enrichment step before 150-bp paired-end sequencing with Illumina HiSeq series. For the analysis, we evaluated several published tools. We focused mainly on the compatibility of the input and output of each tool. Finally, our laboratory built an analysis pipeline specialized for UMI-adopted data. Through this pipeline, we were able to estimate even on-target rates and filtered consensus reads for more accurate variant calling. These results suggest the potential of our analysis pipeline in the precise examination of the quality and efficiency of conducted experiments.

• Genomics & Informatics
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• v.20 no.3
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• pp.28.1-28.7
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• 2022

We described a clinical, laboratory, and genetic presentation of a pathogenic variant of the CYP1B1 gene through a report of a case of primary congenital glaucoma and a trio analysis of this candidate variant in the family with the Sanger sequencing method and eventually completed our study with the secondary/incidental findings. This study reports a rare case of primary congenital glaucoma, an 8-year-old female child with a negative family history of glaucoma and uncontrolled intraocular pressure. This case's whole-exome sequencing data analysis presents a homozygous pathogenic single nucleotide variant in the CYP1B1 gene (NM_000104:exon3:c.G1103A:p.R368H). At the same time, this pathogenic variant was obtained as a heterozygous state in her unaffected father but not her mother. The diagnosis was made based on molecular findings of whole-exome sequencing data analysis. Therefore, the clinical reports and bioinformatics findings supported the relation between the candidate pathogenic variant and the disease. However, it should not be forgotten that primary congenital glaucoma is not peculiar to the CYP1B1 gene. Since the chance of developing autosomal recessive disorders with low allele frequency and unrelated parents is extraordinary in offspring. However, further data analysis of whole-exome sequencing and Sanger sequencing method were applied to obtain the type of mutation and how it was carried to the offspring.

• Journal of Genetic Medicine
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• v.20 no.1
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• pp.1-5
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• 2023

Until now, rare disease studies have mainly been carried out by detecting simple variants such as single nucleotide substitutions and short insertions and deletions in protein-coding regions of disease-associated gene panels using diagnostic next-generation sequencing in association with patient phenotypes. However, several recent studies reported that the detection rate hardly exceeds 50% even when whole-exome sequencing is applied. Therefore, the necessity of introducing whole-genome sequencing is emerging to discover more diverse genomic variants and examine their association with rare diseases. When no diagnosis is provided by whole-genome sequencing, additional omics techniques such as RNA-seq also can be considered to further interrogate causal variants. This paper will introduce a description of these multi-omics techniques and their applications in rare disease studies.

• Genomics & Informatics
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• v.20 no.1
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• pp.3.1-3.10
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• 2022

The recent development of whole-genome sequencing technologies paved the way for understanding the genomes of microorganisms. Every whole-genome sequencing (WGS) project requires a considerable cost and a massive effort to address the questions at hand. The final step of WGS is data analysis. The analysis of whole-genome sequence is dependent on highly sophisticated bioinformatics tools that the research personal have to buy. However, many laboratories and research institutions do not have the bioinformatics capabilities to analyze the genomic data and therefore, are unable to take maximum advantage of whole-genome sequencing. In this aspect, this study provides a guide for research personals on a set of bioinformatics tools available online that can be used to analyze whole-genome sequence data of bacterial genomes. The web interfaces described here have many advantages and, in most cases exempting the need for costly analysis tools and intensive computing resources.

• Genomics & Informatics
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• v.18 no.1
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• pp.10.1-10.9
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• 2020

Advancements in next generation sequencing (NGS) technologies have significantly increased the translational use of genomics data in the medical field as well as the demand for computational infrastructure capable processing that data. To enhance the current understanding of software and hardware used to compute large scale human genomic datasets (NGS), the performance and accuracy of optimized versions of GATK algorithms, including Parabricks and Sentieon, were compared to the results of the original application (GATK V4.1.0, Intel x86 CPUs). Parabricks was able to process a 50× whole-genome sequencing library in under 3 h and Sentieon finished in under 8 h, whereas GATK v4.1.0 needed nearly 24 h. These results were achieved while maintaining greater than 99% accuracy and precision compared to stock GATK. Sentieon's somatic pipeline achieved similar results greater than 99%. Additionally, the IBM POWER9 CPU performed well on bioinformatic workloads when tested with 10 different tools for alignment/mapping.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.2
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• pp.18-24
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• 1988

We consider sensitivity analysis sequencing problems, in which sequence of a finite set of expansion projects is sought to meet a deterministic demand projection in minimum discounted cost. In particular, by characterizing the underlying network structure, we find analytically the sensitivity range for a project cost such that the optimal sequencing policy remains unchanged for any value in the range. A numerical example is presented.

• Journal of Life Science
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• v.11 no.1
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• pp.19-23
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• 2001

To develop the effective microbial screening method, pyrolysis mass spectrometry (PyMS) fingerprinting was evaluated as a tool that discriminate various yeast strains. The target yeast strains were isolated from industrial wastewater. Seventeen environmental isolated yeast strains were examined by pyrolysis mass spectrometry and sequencing analysis of the large subunit rRNA gene D1/D2 region. The PyMS results were compared with those of sequencing analysis. Taxonomic correlations were observed between the PyMS data and the sequencing results. It was concluded that PyMS provides a rapid, reliable and cost-reducing method for discrimination of the yeast strains.

• Genomics & Informatics
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• v.9 no.3
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• pp.136-137
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• 2011

Methylation of cytosine is a post-synthesis modification that does not affect the primary DNA sequence but greatly influences gene expression level and phenotypes of an organism. As high-throughput sequencing of bisulfite-treated DNA is the most efficient method to identify methylated sites, several tools to map sequencing reads on a reference are available. But tools to visualize and to interpret the methylation level of methylation sites are currently insufficient. Herein, we present a novel tool to visualize the methylation level of CpG sites.

• Biomedical Science Letters
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• v.22 no.4
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• pp.150-159
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• 2016

Knowledge of the distribution and biodiversity of environmental bacteria and the ecosystem that influences them is crucial for predicting an ecosystem. However, bacterial culture methods can only analyze approximately 0.1% of the existing microorganisms, those that are readily cultured under laboratory conditions. By contrast, next-generation sequencing (NGS) has generally been known to obtain more diverse profiling of bacterial composition. We compared the bacterial communities using both a culture-dependent (MALDI-TOF) and culture-independent (NGS) methods. Environmental specimens were obtained from both freshwater and seawater. Water samples were also analyzed by both pyrosequencing and MiSeq sequencing, in order to select one NGS platform which could analyze comparatively more diverse microbiota. Bacterial distribution analyzed with MALDI-TOF showed no difference between the microbiota of freshwater and seawater, whereas the results analyzed with NGS distinguished between the two. The diversity indexes of MiSeq sequencing were higher than for Pyrosequencing. This indicated that MiSeq sequencing is capable of analyzing a comparatively wider diversity of bacteria. The genus of Flavobacterium and Planktophila were identified as being unique to freshwater, whereas EU801223 and OM43 were found in the seawater. Difference between the bacterial composition of the freshwater and seawater environments was identified by MiSeq sequencing analysis.

• Food Science and Industry
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• v.52 no.3
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• pp.220-228
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• 2019

Rapid development of next-generation sequencing (NGS) technology is available to study microbes in genomic level. This NGS has been widely used in DNA/RNA sequencing for genome sequencing, metagenomics, and transcriptomics. The food microbiology area could be categorized into three groups. Food microbes including probiotics and food-borne pathogens are studied in genomic level using NGS for microbial genomics. While food fermentation or food spoilage are more complicated, their genomic study needs to be done with metagenomics using NGS for compositional analysis. Furthermore, because microbial response in food environments are also important to understand their roles in food fermentation or spoilage, pattern analysis of RNA expression in the specific food microbe is conducted using RNA-Seq. These microbial genomics, metagenomics, and transcriptomics for food fermentation and spoilage would extend our knowledge on effective utilization of fermenting bacteria for health promotion as well as efficient control of food-borne pathogens for food safety.