GeneProf: analysis of high-throughput sequencing experiments (original) (raw)

Nature Methods volume 9, pages 7–8 (2012)Cite this article

To the Editor:

The huge volume and complexity of data produced by high-throughput sequencing make it difficult for researchers in many laboratories to fully harness the potential of these data for the study of biological processes and human disease. Data processing rather than generation is now often the bottleneck for biological experiments1, and the efficient use of high-throughput sequencing data submitted to public databases such as the Sequence Read Archive remains a challenging goal for many. Workflow-based software2,3 offers an attractive approach for dealing with complex data because it allows the visual organization of software components into ordered 'workflows' (Supplementary Note). This enables complicated analyses without any need to write custom computer scripts. However, workflow engines focus on the mechanics of the computational processes involved; the primary goal is to achieve computation rather than a particular biological result. Therefore, setting up a workflow can be a daunting task for many life scientists, especially those lacking experience in the visual programming paradigm. Existing tools are hence not sufficient to make high-throughput sequencing data fully accessible to the entire research community.

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Figure 1: Overview of a GeneProf experiment and sample outputs.

References

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Acknowledgements

We thank C. Nerlov, I. Chambers and S. Skylaki for proofreading the manuscript and providing helpful suggestions. F.H. was funded by a Medical Research Council studentship. Additional funding was provided by the European Commission Seventh Framework Programme 'EuroSyStem'.

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Authors and Affiliations

  1. Institute for Stem Cell Research, Centre for Regenerative Medicine, School of Biological Sciences, University of Edinburgh, Edinburgh, UK
    Florian Halbritter, Harsh J Vaidya & Simon R Tomlinson

Authors

  1. Florian Halbritter
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  2. Harsh J Vaidya
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  3. Simon R Tomlinson
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Corresponding author

Correspondence toSimon R Tomlinson.

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Competing interests

Edinburgh Research and Innovation (University of Edinburgh) is currently investigating the commercial potential of GeneProf.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–9, Supplementary Note, Supplementary Discussion, Supplementary Methods, Supplementary Data (PDF 5119 kb)

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Halbritter, F., Vaidya, H. & Tomlinson, S. GeneProf: analysis of high-throughput sequencing experiments.Nat Methods 9, 7–8 (2012). https://doi.org/10.1038/nmeth.1809

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