Maser: one-stop platform for NGS big data from analysis to visualization
KAUST DepartmentBiological and Environmental Sciences and Engineering (BESE) Division
Computational Bioscience Research Center (CBRC)
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Permanent link to this recordhttp://hdl.handle.net/10754/631504
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AbstractA major challenge in analyzing the data from high-throughput next-generation sequencing (NGS) is how to handle the huge amounts of data and variety of NGS tools and visualize the resultant outputs. To address these issues, we developed a cloud-based data analysis platform, Maser (Management and Analysis System for Enormous Reads), and an original genome browser, Genome Explorer (GE). Maser enables users to manage up to 2 terabytes of data to conduct analyses with easy graphical user interface operations and offers analysis pipelines in which several individual tools are combined as a single pipeline for very common and standard analyses. GE automatically visualizes genome assembly and mapping results output from Maser pipelines, without requiring additional data upload. With this function, the Maser pipelines can graphically display the results output from all the embedded tools and mapping results in a web browser. Therefore Maser realized a more user-friendly analysis platform especially for beginners by improving graphical display and providing the selected standard pipelines that work with built-in genome browser. In addition, all the analyses executed on Maser are recorded in the analysis history, helping users to trace and repeat the analyses. The entire process of analysis and its histories can be shared with collaborators or opened to the public. In conclusion, our system is useful for managing, analyzing, and visualizing NGS data and achieves traceability, reproducibility, and transparency of NGS analysis.
CitationKinjo S, Monma N, Misu S, Kitamura N, Imoto J, et al. (2018) Maser: one-stop platform for NGS big data from analysis to visualization. Database 2018. Available: http://dx.doi.org/10.1093/database/bay027.
SponsorsThis work was partially supported by the Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT) grant [code 09002013] and by Agency for Medical Research and Development (AMED) grant [JP16am0101058j0003] and [JP17am0101001]. We would like to thank all the researchers and engineers who involved in the development of Maser, Genome Explorer and analysis pipelines. We also thank Shunsuke Yaguchi, Masafumi Nozawa, Yoshiyuki Suzuki, Kaoru Matsumoto, Yasushi Hiromi and Mitsuhiko Kurusu, for their helpful suggestions and comments that improve the article.
PublisherOxford University Press (OUP)
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