Bioinformatics services for analyzing massive genomic datasets

• Published in: Genomics & informatics Vol. 18; no. 1; p. e8
• Main Authors: Ko, Gunhwan, Kim, Pan-Gyu, Cho, Youngbum, Jeong, Seongmun, Kim, Jae-Yoon, Kim, Kyoung Hyoun, Lee, Ho-Yeon, Han, Jiyeon, Yu, Namhee, Ham, Seokjin, Jang, Insoon, Kang, Byunghee, Shin, Sunguk, Kim, Lian, Lee, Seung-Won, Nam, Dougu, Kim, Jihyun F, Kim, Namshin, Kim, Seon-Young, Lee, Sanghyuk, Roh, Tae-Young, Lee, Byungwook
• Format: Journal Article
• Language: English
• Published: Korea (South) Korea Genome Organization 01.03.2020
• Subjects: analysis pipeline; cloud computing; genomic data; Original; web server; workflow system; workflow system; analysis pipeline; cloud computing; genomic data; web server
• ISSN: 1598-866X; 2234-0742; 2234-0742
• DOI: 10.5808/GI.2020.18.1.e8

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/.