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Next-generation sequencing data interpretation: enhancing reproducibility and accessibility

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NATURE REVIEWS GENETICS
卷 13, 期 9, 页码 667-U93

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NATURE PUBLISHING GROUP
DOI: 10.1038/nrg3305

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资金

  1. Galaxy Team
  2. US National Institutes of Health [HG005133, HG004909, HG006620]
  3. US National Science Foundation [DBI 0850103]
  4. Huck Institutes for the Life Sciences at Penn State
  5. Institute for Cyberscience at Penn State
  6. Pennsylvania Department of Health using Tobacco Settlement Funds
  7. Direct For Biological Sciences
  8. Div Of Biological Infrastructure [0850103] Funding Source: National Science Foundation

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Areas of life sciences research that were previously distant from each other in ideology, analysis practices and toolkits, such as microbial ecology and personalized medicine, have all embraced techniques that rely on next-generation sequencing instruments. Yet the capacity to generate the data greatly outpaces our ability to analyse it. Existing sequencing technologies are more mature and accessible than the methodologies that are available for individual researchers to move, store, analyse and present data in a fashion that is transparent and reproducible. Here we discuss currently pressing issues with analysis, interpretation, reproducibility and accessibility of these data, and we present promising solutions and venture into potential future developments.

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