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Related Concept Videos

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Benchmarking undedicated cloud computing providers for analysis of genomic datasets.

Seyhan Yazar1, George E C Gooden1, David A Mackey2

  • 1Centre for Ophthalmology and Visual Science, University of Western Australia, Lions Eye Institute, Perth, Western Australia, Australia.

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Google Compute Engine (GCE) significantly outperforms Amazon Web Services Elastic MapReduce (EMR) for genomic data analysis. GCE offers faster processing times and lower costs, making cloud computing a viable option for biological discovery.

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Genomics

Background:

  • Computational demands in biological discovery are increasing.
  • Cloud computing provides scalable computational resources for research labs.
  • Amazon Web Services Elastic MapReduce (EMR) and Google Compute Engine (GCE) are leading cloud platforms.

Purpose of the Study:

  • To benchmark the performance and cost-effectiveness of EMR and GCE for genomic data analysis.
  • To compare wall-clock time and expenses for assembling genomic datasets on both platforms.
  • To provide practical scripts for setting up Hadoop environments on cloud platforms.

Main Methods:

  • Benchmarking EMR and GCE using publicly available E.coli and human genome datasets.
  • Utilizing a standard bioinformatics pipeline on a Hadoop-based platform.
  • Analyzing wall-clock time and computational costs for genome assembly.

Main Results:

  • GCE demonstrated superior efficiency, with E.coli assembly 52.9% faster and human genome assembly 53.5% faster than EMR.
  • EMR was significantly more expensive, costing 257.3% more for E.coli and 173.9% more for human genome assemblies.
  • GCE outperformed EMR in both processing speed and cost-effectiveness.

Conclusions:

  • Cloud computing, particularly GCE, offers an efficient and cost-effective solution for analyzing large genomic datasets.
  • The findings support the adoption of cloud platforms to overcome computational bottlenecks in biological discovery.
  • Ready-to-use scripts are provided to facilitate the implementation of Hadoop on EMR and GCE.