CSI NGS Portal: An Online Platform for Automated NGS Data Analysis and Sharing.

Omer An,Kar-Tong Tan,Henry Yang,Bin Zhang,Chan-Shuo Wu,Jia Li,Leilei Chen,Ying Li

doi:10.3390/ijms21113828

Abstract

Next-generation sequencing (NGS) has been a widely-used technology in biomedical research for understanding the role of molecular genetics of cells in health and disease. A variety of computational tools have been developed to analyse the vastly growing NGS data, which often require bioinformatics skills, tedious work and a significant amount of time. To facilitate data processing steps minding the gap between biologists and bioinformaticians, we developed CSI NGS Portal, an online platform which gathers established bioinformatics pipelines to provide fully automated NGS data analysis and sharing in a user-friendly website. The portal currently provides 16 standard pipelines for analysing data from DNA, RNA, smallRNA, ChIP, RIP, 4C, SHAPE, circRNA, eCLIP, Bisulfite and scRNA sequencing, and is flexible to expand with new pipelines. The users can upload raw data in FASTQ format and submit jobs in a few clicks, and the results will be self-accessible via the portal to view/download/share in real-time. The output can be readily used as the final report or as input for other tools depending on the pipeline. Overall, CSI NGS Portal helps researchers rapidly analyse their NGS data and share results with colleagues without the aid of a bioinformatician. The portal is freely available at: https://csibioinfo.nus.edu.sg/csingsportal.

Highlights

Next-generation sequencing (NGS) has become a routine in biomedical research thanks to its proven significance and rapidly decreasing cost
An overwhelming number of sequencing protocols are available by various providers, and more of them are to be developed in the near future as the underlying technology advances
Despite the expanding applications of automated systems in the global context, not every system can be automated in perfection without human intervention; this is true for the bioinformatics systems

Summary

Introduction

Next-generation sequencing (NGS) has become a routine in biomedical research thanks to its proven significance and rapidly decreasing cost. On the other hand, emerging technologies such as supercomputers (e.g., National Supercomputing Centre Singapore, NSCC, https://www.nscc.sg/) and cloud computing (e.g., Amazon Web Services, AWS, https://aws.amazon.com/) offer large-scale parallel computations with high speed, memory and storage, to efficiently deal with the big data generated by the NGS platforms. These technologies, are still offering high-cost services, which may sometimes even exceed the cost of the sequencing itself. These options do not eliminate the necessity for a local bioinformatician to perform the downstream analysis and to interpret the results—unless paid for additional bioinformatics

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