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Cloud computing tools and analyses

The next generation sequencing 'problem', namely the generation of huge datasets that are unwieldy for analyses and expensive and problematic to store, has been remedied by the advent of cloud computing, where one rents hardware or storage space. This phenomenon has revolutionized genomic analyses and brought large-scale genomics within reach of smaller labs. The following Genome Biology articles showcase tools and examples of studies that use such technologies.

  1. Recent studies generating complete human sequences from Asian, African and European subgroups have revealed population-specific variation and disease susceptibility loci. Here, choosing a DNA sample from a pop...

    Authors: Pin Tong, James GD Prendergast, Amanda J Lohan, Susan M Farrington, Simon Cronin, Nial Friel, Dan G Bradley, Orla Hardiman, Alex Evans, James F Wilson and Brendan Loftus
    Citation: Genome Biology 2010 11:R91
    Content type: Research Published on:

  4. With the continued exponential expansion of publicly available genomic data and access to low-cost, high-throughput molecular technologies for profiling patient populations, computational technologies and info...

    Authors: Joel T Dudley, Yannick Pouliot, Rong Chen, Alexander A Morgan and Atul J Butte
    Citation: Genome Medicine 2010 2:51
    Content type: Correspondence Published on:

  5. Large comparative genomics studies and tools are becoming increasingly more compute-expensive as the number of available genome sequences continues to rise. The capacity and cost of local computing infrastruct...

    Authors: Dennis P Wall, Parul Kudtarkar, Vincent A Fusaro, Rimma Pivovarov, Prasad Patil and Peter J Tonellato
    Citation: BMC Bioinformatics 2010 11:259
    Content type: Methodology article Published on:

  7. As DNA sequencing outpaces improvements in computer speed, there is a critical need to accelerate tasks like alignment and SNP calling. Crossbow is a cloud-computing software tool that combines the aligner Bow...

    Authors: Ben Langmead, Michael C Schatz, Jimmy Lin, Mihai Pop and Steven L Salzberg
    Citation: Genome Biology 2009 10:R134
    Content type: Software Published on:

  8. Life sciences make heavily use of the web for both data provision and analysis. However, the increasing amount of available data and the diversity of analysis tools call for machine accessible interfaces in or...

    Authors: Johannes Wagener, Ola Spjuth, Egon L Willighagen and Jarl ES Wikberg
    Citation: BMC Bioinformatics 2009 10:279
    Content type: Methodology article Published on: