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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2015.1
- 수록면
- 489 - 501 (13page)
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With the advent of next-generation sequencing (NGS), including whole genome sequencing (WGS), RNA sequencing (RNA-seq), and chromatin immunoprecipitation followed by sequencing (ChIP-seq), many biologists and computer scientists are highlighting the urgent need for computing power, storage, and various bioinformatics software for analyzing large quantities of sequence data. Currently, building the computational infrastructure required for massive data processing and providing maintenance services are among the most important tasks. However, technology platforms for handling large amounts of information pose multiple challenges for data access and processing. To overcome these challenges, cloud computing technologies are emerging as a possible infrastructure for tackling the intensive use of computing power and communication resources in NGS data analysis. Thus, in this review, we explain the concepts and key technologies of cloud computing, such as Map and Reduce, and discuss the problem of data transfer. To reveal the performance and usefulness of these technologies, we analyzed NGS data using cloud platforms and compared them with a local cluster. From the benchmark results, we concluded that cloud computing is still more expensive than local cluster, but provides reasonable performance for NGS data analysis with acceptable prices and could be a good alternative to local cluster systems.
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참고문헌 (36)
참고문헌 신청
Abecasis GR / 2010 / Amap of human genome variation from population-scale sequencing / Nature 467:1061~1073
Afgan E / 2010 / Galaxy CloudMan: delivering cloud compute clusters / BMC Bioinform 11(Suppl 12):S4
Angiuoli SV / 2011 / CloVR: a virtual machine for automated and portable sequence analysis from the desktop using cloud computing / BMC Bioinform 12:356
Asmann YW / 2012 / TREAT: a bioinformatics tool for variant annotations and visualizations in targeted and exome sequencing data / Bioinformatics 28:277~278
Baker M / 2010 / Next-generation sequencing: adjusting to data overload / Nat Methods 7:495~499
Afgan E / 2010 / Galaxy CloudMan: delivering cloud compute clusters / BMC Bioinform 11(Suppl 12):S4
Angiuoli SV / 2011 / CloVR: a virtual machine for automated and portable sequence analysis from the desktop using cloud computing / BMC Bioinform 12:356
Asmann YW / 2012 / TREAT: a bioinformatics tool for variant annotations and visualizations in targeted and exome sequencing data / Bioinformatics 28:277~278
Baker M / 2010 / Next-generation sequencing: adjusting to data overload / Nat Methods 7:495~499
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