An improved de novo genome assembly of the common marmoset genome yields improved contiguity and increased mapping rates of sequence data |
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Authors: | Jayakumar Vasanthan Ishii Hiromi Seki Misato Kumita Wakako Inoue Takashi Hase Sumitaka Sato Kengo Okano Hideyuki Sasaki Erika Sakakibara Yasubumi |
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Affiliation: | 1.Taiwan International Graduate Program (TIGP) on Bioinformatics, Academia Sinica, Taipei, Taiwan ;2.Institute of Information Science, Academia Sinica, Taipei, Taiwan ;3.Institute of Biomedical Informatics, National Yang-Ming University, Taipei, Taiwan ;4.Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli, Taiwan ;5.Institute of Plant and Microbial Biology, Academia Sinica, Taipei, Taiwan ;6.TMU Research Center of Cancer Translational Medicine, Taipei Medical University, Taipei, Taiwan ;7.Institute of Fisheries Science, College of Life Science, National Taiwan University, Taipei, Taiwan ; |
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Abstract: | Background DNA methylation is a crucial epigenomic mechanism in various biological processes. Using whole-genome bisulfite sequencing (WGBS) technology, methylated cytosine sites can be revealed at the single nucleotide level. However, the WGBS data analysis process is usually complicated and challenging. ResultsTo alleviate the associated difficulties, we integrated the WGBS data processing steps and downstream analysis into a two-phase approach. First, we set up the required tools in Galaxy and developed workflows to calculate the methylation level from raw WGBS data and generate a methylation status summary, the mtable. This computation environment is wrapped into the Docker container image DocMethyl, which allows users to rapidly deploy an executable environment without tedious software installation and library dependency problems. Next, the mtable files were uploaded to the web server EpiMOLAS_web to link with the gene annotation databases that enable rapid data retrieval and analyses. ConclusionTo our knowledge, the EpiMOLAS framework, consisting of DocMethyl and EpiMOLAS_web, is the first approach to include containerization technology and a web-based system for WGBS data analysis from raw data processing to downstream analysis. EpiMOLAS will help users cope with their WGBS data and also conduct reproducible analyses of publicly available data, thereby gaining insights into the mechanisms underlying complex biological phenomenon. The Galaxy Docker image DocMethyl is available at https://hub.docker.com/r/lsbnb/docmethyl/. EpiMOLAS_web is publicly accessible at http://symbiosis.iis.sinica.edu.tw/epimolas/. |
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