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Bioinformatics services for analyzing massive genomic datasets
- Title
- Bioinformatics services for analyzing massive genomic datasets
- Authors
- Ko G.; Kim P.-G.; Cho Y.; Jeong S.; Kim J.-Y.; Kim K.H.; Lee H.-Y.; Han J.; Yu N.; Ham S.; Jang I.; Kang B.; Shin S.; Kim L.; Lee S.-W.; Nam D.; Kim J.F.; Kim N.; Kim S.-Y.; Lee S.; Roh T.-Y.; Lee B.
- Ewha Authors
- 이상혁
- SCOPUS Author ID
- 이상혁
- Issue Date
- 2020
- Journal Title
- Genomics and Informatics
- ISSN
- 2234-0742
- Citation
- Genomics and Informatics vol. 18, no. 1
- Keywords
- Analysis pipeline; Cloud computing; Genomic data; Web server; Workflow system
- Publisher
- Korea Genome Organization
- Indexed
- SCOPUS
- Document Type
- Article
- Abstract
- The explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and ensuing computational problems. In Korea, the amount of genomic data has been increasing rapidly in the recent years. Leveraging these big data requires researchers to use large-scale computational resources and analysis pipelines. A promising solution for addressing this computational challenge is cloud computing, where CPUs, memory, storage, and programs are accessible in the form of virtual machines. Here, we present a cloud computing-based system, Bio-Express, that provides user-friendly, cost-effective analysis of massive genomic datasets. Bio-Express is loaded with predefined multi-omics data analysis pipelines, which are divided into genome, transcriptome, epigenome, and metagenome pipelines. Users can employ predefined pipelines or create a new pipeline for analyzing their own omics data. We also developed several web-based services for facilitating down-stream analysis of genome data. Bio-Express web service is freely available at https://www. bioexpress.re.kr/. © 2020, Korea Genome Organization.
- DOI
- 10.5808/GI.2020.18.1.e8
- Appears in Collections:
- 자연과학대학 > 생명과학전공 > Journal papers
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