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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:

  2. 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:

  3. 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

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  4. 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:

  5. 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: