Bioinformatics services for analyzing massive genomic datasets
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...
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| Format: | Article |
| Language: | English |
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BioMed Central
2020-03-01
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| Series: | Genomics & Informatics |
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| Online Access: | http://genominfo.org/upload/pdf/gi-2020-18-1-e8.pdf |
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| author | 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 Sunguk Shin Lian Kim Seung-Won Lee Dougu Nam Jihyun F. Kim Namshin Kim Seon-Young Kim Sanghyuk Lee Tae-Young Roh Byungwook Lee |
| author_facet | 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 Sunguk Shin Lian Kim Seung-Won Lee Dougu Nam Jihyun F. Kim Namshin Kim Seon-Young Kim Sanghyuk Lee Tae-Young Roh Byungwook Lee |
| author_sort | Gunhwan Ko |
| collection | DOAJ |
| description | 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/. |
| format | Article |
| id | doaj-art-cedf9d54a4f84b7d80e78b149c2bcf1a |
| institution | Kabale University |
| issn | 2234-0742 |
| language | English |
| publishDate | 2020-03-01 |
| publisher | BioMed Central |
| record_format | Article |
| series | Genomics & Informatics |
| spelling | doaj-art-cedf9d54a4f84b7d80e78b149c2bcf1a2025-02-02T03:20:36ZengBioMed CentralGenomics & Informatics2234-07422020-03-0118110.5808/GI.2020.18.1.e8599Bioinformatics services for analyzing massive genomic datasetsGunhwan Ko0Pan-Gyu Kim1Youngbum Cho2Seongmun Jeong3Jae-Yoon Kim4Kyoung Hyoun Kim5Ho-Yeon Lee6Jiyeon Han7Namhee Yu8Seokjin Ham9Insoon Jang10Byunghee Kang11Sunguk Shin12Lian Kim13Seung-Won Lee14Dougu Nam15Jihyun F. Kim16Namshin Kim17Seon-Young Kim18Sanghyuk Lee19Tae-Young Roh20Byungwook Lee21 Korea Bioinformation Center (KOBIC), KRIBB, Daejeon 34141, Korea Korea Bioinformation Center (KOBIC), KRIBB, Daejeon 34141, Korea Genome Editing Research Center, KRIBB, Daejeon 34141, Korea Genome Editing Research Center, KRIBB, Daejeon 34141, Korea Genome Editing Research Center, KRIBB, Daejeon 34141, Korea Genome Editing Research Center, KRIBB, Daejeon 34141, Korea Genome Editing Research Center, KRIBB, Daejeon 34141, Korea Department of BioInformation Science, Ewha Womans University, Seoul 03760, Korea Department of BioInformation Science, Ewha Womans University, Seoul 03760, Korea Department of Life Sciences and Division of Integrative Biosciences & Biotechnology, Pohang University of Science & Technology (POSTECH), Pohang 37673, Korea Department of Life Sciences and Division of Integrative Biosciences & Biotechnology, Pohang University of Science & Technology (POSTECH), Pohang 37673, Korea Department of Life Sciences and Division of Integrative Biosciences & Biotechnology, Pohang University of Science & Technology (POSTECH), Pohang 37673, Korea Department of Systems, Biology Division of Life Sciences, and Institute for Life Science and Biotechnology, Yonsei University, Seoul 03722, Korea Bioposh Inc., Daejeon 34016, Korea SeqGenesis, Daejeon 34016, Korea School of Life Sciences, Ulsan National Institute of Science and Technology, Ulsan 44919, Korea Department of Systems, Biology Division of Life Sciences, and Institute for Life Science and Biotechnology, Yonsei University, Seoul 03722, Korea Genome Editing Research Center, KRIBB, Daejeon 34141, Korea Genome Structure Research Center, KRIBB, Daejeon 34141, Korea Department of BioInformation Science, Ewha Womans University, Seoul 03760, Korea Department of Life Sciences and Division of Integrative Biosciences & Biotechnology, Pohang University of Science & Technology (POSTECH), Pohang 37673, Korea Korea Bioinformation Center (KOBIC), KRIBB, Daejeon 34141, KoreaThe 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/.http://genominfo.org/upload/pdf/gi-2020-18-1-e8.pdfanalysis pipelinecloud computinggenomic dataweb serverworkflow system |
| spellingShingle | 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 Sunguk Shin Lian Kim Seung-Won Lee Dougu Nam Jihyun F. Kim Namshin Kim Seon-Young Kim Sanghyuk Lee Tae-Young Roh Byungwook Lee Bioinformatics services for analyzing massive genomic datasets Genomics & Informatics analysis pipeline cloud computing genomic data web server workflow system |
| title | Bioinformatics services for analyzing massive genomic datasets |
| title_full | Bioinformatics services for analyzing massive genomic datasets |
| title_fullStr | Bioinformatics services for analyzing massive genomic datasets |
| title_full_unstemmed | Bioinformatics services for analyzing massive genomic datasets |
| title_short | Bioinformatics services for analyzing massive genomic datasets |
| title_sort | bioinformatics services for analyzing massive genomic datasets |
| topic | analysis pipeline cloud computing genomic data web server workflow system |
| url | http://genominfo.org/upload/pdf/gi-2020-18-1-e8.pdf |
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