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    Diversity and enterotype in gut bacterial community of adults in Taiwan
    (2017-01-01)
    Liang, Chao
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    Tseng, Han-Chi
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    Chen, Hui-Mei
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    Wang, Wei-Chi
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    Chiu, Chih-Min
    Background: Gastrointestinal microbiota, particularly gut microbiota, is associated with human health. The biodiversity of gut microbiota is affected by ethnicities and environmental factors such as dietary habits or medicine intake, and three enterotypes of the human gut microbiome were announced in 2011. These enterotypes are not significantly correlated with gender, age, or body weight but are influenced by long-term dietary habits. However, to date, only two enterotypes (predominantly consisting of Bacteroides and Prevotella) have shown these characteristics in previous research; the third enterotype remains ambiguous. Understanding the enterotypes can improve the knowledge of the relationship between microbiota and human health. Results: We obtained 181 human fecal samples from adults in Taiwan. Microbiota compositions were analyzed using next-generation sequencing (NGS) technology, which is a culture-independent method of constructing microbial community profiles by sequencing 16S ribosomal DNA (rDNA). In these samples, 17,675,898 sequencing reads were sequenced, and on average, 215 operational taxonomic units (OTUs) were identified for each sample. In this study, the major bacteria in the enterotypes identified from the fecal samples were Bacteroides, Prevotella, and Enterobacteriaceae, and their correlation with dietary habits was confirmed. A microbial interaction network in the gut was observed on the basis of the amount of short-chain fatty acids, pH value of the intestine, and composition of the bacterial community (enterotypes). Finally, a decision tree was derived to provide a predictive model for the three enterotypes. The accuracies of this model in training and independent testing sets were 97.2 and 84.0%, respectively. Conclusions: We used NGS technology to characterize the microbiota and constructed a predictive model. The most significant finding was that Enterobacteriaceae, the predominant subtype, could be a new subtype of enterotypes in the Asian population.
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    Evaluation of whole exome sequencing by targeted gene sequencing and Sanger sequencing
    (2017-08-01)
    Chang, Ya-Sian
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    Huang, Hsien-Da
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    Yeh, Kun-Tu
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    Chang, Jan-Gowth
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    生物科技學系
    Background: Targeted gene sequencing (TGS) and whole exome sequencing (WES) are being used in clinical testing in laboratories. We compared the performances of TGS and WES using the same DNA samples. Methods: DNA was extracted from 10 endometrial tumor tissue specimens. Sequencing were performed with an Illumina HiSeq 2000. We randomly selected variants to confirm through Sanger sequencing or mutant-enriched PCR with Sanger sequencing. Results: We found that the variants identified in both TGS and WES were true positives (47/47), regardless of the sequencing depth. Most variants found in TGS only were true positives (34/40), and most of the variants found by WES only were false positives (8/18). From these results, we suggest that the sequencing depth may not play important role in the accuracy of NGS-based methods. After analysis, we found that WES had a sensitivity of 72.70%, specificity of 96.27%, precision of 99.44%, and accuracy of 75.03%. Conclusions: The results of NGS-based methods must currently be validated, especially for important reported variants regardless of the methods used, and for the use of WES in cancers a higher false negative rate must be considered. More sensitive methods should be used to confirm the NGS results in uneven cancer tissues.
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    Detecting exact breakpoints of deletions with diversity in hepatitis B viral genomic DNA from next-generation sequencing data
    (2017-10-01)
    Cheng, Ji-Hong
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    Liu, Wen-Chun
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    Chang, Ting-Tsung
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    Hsieh, Sun-Yuan
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    Tseng, Vincent S.
    Many studies have suggested that deletions of Hepatitis B Viral (HBV) are associated with the development of progressive liver diseases, even ultimately resulting in hepatocellular carcinoma (HCC). Among the methods for detecting deletions from next-generation sequencing (NGS) data, few methods considered the characteristics of virus, such as high evolution rates and high divergence among the different HBV genomes. Sequencing high divergence HBV genome sequences using the NGS technology outputs millions of reads. Thus, detecting exact breakpoints of deletions from these big and complex data incurs very high computational cost. We proposed a novel analytical method named VirDelect (Virus Deletion Detect), which uses split read alignment base to detect exact breakpoint and diversity variable to consider high divergence in single-end reads data, such that the computational cost can be reduced without losing accuracy. We use four simulated reads datasets and two real pair-end reads datasets of HBV genome sequence to verify VirDelect accuracy by score functions. The experimental results show that VirDelect outperforms the state-of-the-art method Pindel in terms of accuracy score for all simulated datasets and VirDelect had only two base errors even in real datasets. VirDelect is also shown to deliver high accuracy in analyzing the single-end read data as well as pair-end data. VirDelect can serve as an effective and efficient bioinformatics tool for physiologists with high accuracy and efficient performance and applicable to further analysis with characteristics similar to HBV on genome length and high divergence. The software program of VirDelect can be downloaded at https://sourceforge.net/projects/virdelect/. (C) 2017 Published by Elsevier Inc.
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    DeF-GPU: Efficient and effective deletions finding in hepatitis B viral genomic DNA using a GPU architecture
    (2016-12-01)
    Cheng, Chun-Pei
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    Lan, Kuo-Lun
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    Liu, Wen-Chun
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    Chang, Ting-Tsung
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    Tseng, Vincent S.
    Hepatitis B viral (HBV) infection is strongly associated with an increased risk of liver diseases like cirrhosis or hepatocellular carcinoma (HCC). Many lines of evidence suggest that deletions occurring in HBV genomic DNA are highly associated with the activity of HBV via the interplay between aberrant viral proteins release and human immune system. Deletions finding on the HBV whole genome sequences is thus a very important issue though there exist underlying the challenges in mining such big and complex biological data. Although some next generation sequencing (NGS) tools are recently designed for identifying structural variations such as insertions or deletions, their validity is generally committed to human sequences study. This design may not be suitable for viruses due to different species. We propose a graphics processing unit (GPU)-based data mining method called DeF-GPU to efficiently and precisely identify HBV deletions from large NGS data, which generally contain millions of reads. To fit the single instruction multiple data instructions, sequencing reads are referred to as multiple data and the deletion finding procedure is referred to as a single instruction. We use Compute Unified Device Architecture (CUDA) to parallelize the procedures, and further validate DeF-GPU on 5 synthetic and 1 real datasets. Our results suggest that DeF-GPU outperforms the existing commonly-used method Pindel and is able to exactly identify the deletions of our ground truth in few seconds. The source code and other related materials are available at https://sourceforge.net/projectsidefgpui. (C) 2016 Elsevier Inc. All rights reserved.
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    Genetic alterations in endometrial cancer by targeted next-generation sequencing
    (2016-02)
    Chang, Ya-Sian
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    Huang, Hsien-Da
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    Yeh, Kun-Tu
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    Chang, Jan-Gowth
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    生物科技學系
    Many genetic factors play important roles in the development of endometrial cancer. The aim of this study was to investigate genetic alterations in the Taiwanese population with endometrial cancer. DNA was extracted from 10 cases of fresh-frozen endometrial cancer tissue. The exomes of cancer-related genes were captured using the NimbleGen Comprehensive Cancer Panel (578 cancer-related genes) and sequenced using the Illumina Genomic Sequencing Platform. Our results revealed 120 variants in 99 genes, 21 of which were included in the Oncomine Cancer Research Panel used in the National Cancer Institute Match Trial. The 21 genes comprised 8 tumor suppressor candidates (AIM, MSH2, PIK3R1, PTCH1, PTEN, TET2, TP53, and TSC1) and 13 oncogene candidates (ALK, BCL9, CTNNB1, ERBB2, FGFR2, FLT3, HNF1A, KIT, MTOR, PDGFRA, PPP2R1A, PTPN11, and SF3B1). We identified a high frequency of mutations in PTEN (50%) and genes involved in the endometrial cancer-related molecular pathway, which involves the IL-7 signaling pathway (PIK3R1, n = 1; AKT2, n = 1; FOXO1, n = 1). We report the mutational landscape of endometrial cancer in the Taiwanese population. We believe that this study will shed new light on fundamental aspects for understanding the molecular pathogenesis of endometrial cancer and may aid in the development of new targeted therapies. (C) 2015 Elsevier Inc. All rights reserved.