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用于分析海量基因组数据集的生物信息学服务。

Bioinformatics services for analyzing massive genomic datasets.

作者信息

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

机构信息

Korea Bioinformation Center (KOBIC), KRIBB, Daejeon 34141, Korea.

Genome Editing Research Center, KRIBB, Daejeon 34141, Korea.

出版信息

Genomics Inform. 2020 Mar;18(1):e8. doi: 10.5808/GI.2020.18.1.e8. Epub 2020 Mar 31.

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/.

摘要

下一代测序数据的爆炸式增长产生了超大规模数据集以及随之而来的计算问题。在韩国,近年来基因组数据量一直在迅速增加。利用这些大数据要求研究人员使用大规模计算资源和分析流程。应对这一计算挑战的一个有前景的解决方案是云计算,在云计算中,中央处理器、内存、存储和程序都可以通过虚拟机的形式进行访问。在此,我们展示了一个基于云计算的系统Bio-Express,它能对海量基因组数据集进行用户友好且经济高效的分析。Bio-Express加载了预定义的多组学数据分析流程,这些流程分为基因组、转录组、表观基因组和宏基因组流程。用户可以使用预定义流程或创建新的流程来分析自己的组学数据。我们还开发了几个基于网络的服务,以促进基因组数据的下游分析。Bio-Express网络服务可在https://www.bioexpress.re.kr/免费获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7577/7120352/9df55cb09829/gi-2020-18-1-e8f1.jpg

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