Bioinformatics services for analyzing massive genomic datasets - Gunhwan Ko; Pan-Gyu Kim; Youngbum Cho; Seongmun Jeong; Jae-Yoon Kim; Kyoung Hyoun Kim; Ho-Yeon Lee; Jiyeon Han; Namhee Yu; Seokjin Ham; Insoon Jang; Byunghee Kang; et al. (Genomics & Informatics)
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/.