Genomics Inform.  2020 Mar;18(1):e8. 10.5808/GI.2020.18.1.e8.

Bioinformatics services for analyzing massive genomic datasets

Affiliations
  • 1Korea Bioinformation Center (KOBIC), KRIBB, Daejeon 34141, Korea
  • 2Genome Editing Research Center, KRIBB, Daejeon 34141, Korea
  • 3Department of BioInformation Science, Ewha Womans University, Seoul 03760, Korea
  • 4Department of Life Sciences and Division of Integrative Biosciences & Biotechnology, Pohang University of Science & Technology (POSTECH), Pohang 37673, Korea
  • 5Department of Systems, Biology Division of Life Sciences, and Institute for Life Science and Biotechnology, Yonsei University, Seoul 03722, Korea
  • 6Bioposh Inc., Daejeon 34016, Korea
  • 7SeqGenesis, Daejeon 34016, Korea
  • 8School of Life Sciences, Ulsan National Institute of Science and Technology, Ulsan 44919, Korea
  • 9Strategic Initiative for Microbiomes in Agriculture and Food, Yonsei University, Seoul 03722, Korea
  • 10Genome Structure Research Center, KRIBB, Daejeon 34141, Korea
  • 11SysGenLab Inc., Pohang 37613, Korea

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 downstream analysis of genome data. Bio-Express web service is freely available at https://www.bioexpress.re.kr/.

Keyword

analysis pipeline; cloud computing; genomic data; web server; workflow system
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