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Integrative genomics viewer

Nature Biotechnology volume 29, pages 24–26 (2011)Cite this article

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To the Editor:

Rapid improvements in sequencing and array-based platforms are resulting in a flood of diverse genome-wide data, including data from exome and whole-genome sequencing, epigenetic surveys, expression profiling of coding and noncoding RNAs, single nucleotide polymorphism (SNP) and copy number profiling, and functional assays. Analysis of these large, diverse data sets holds the promise of a more comprehensive understanding of the genome and its relation to human disease. Experienced and knowledgeable human review is an essential component of this process, complementing computational approaches. This calls for efficient and intuitive visualization tools able to scale to very large data sets and to flexibly integrate multiple data types, including clinical data. However, the sheer volume and scope of data pose a significant challenge to the development of such tools.

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Figure 1: Copy number, expression and mutation data grouped by tumor subtype.
Figure 2: View of aligned reads at 20-kb resolution.

References

  1. Cancer Genome Atlas Research Network. Nature 455, 1061–1068 (2008).

  2. Durbin, R.M. et al. Nature 467, 1061–1073 (2010).

    Article  CAS  Google Scholar 

  3. The ENCODE Project Consortium. Science 306, 636–640 (2004).

  4. Verhaak, R.G. et al. Cancer Cell 17, 98–110 (2010).

    Article  CAS  Google Scholar 

  5. Guttman, M. et al. Nature 458, 223–227 (2009).

    Article  CAS  Google Scholar 

  6. Berger, M.F. et al. Genome Res. 20, 413–427 (2010).

    Article  CAS  Google Scholar 

  7. Nielsen, C., Cantor, M., Dubchak, I., Gordon, D. & Wang, T. Nat. Methods 7, S5–S15 (2010).

    Article  CAS  Google Scholar 

  8. Rutherford, K. et al. Bioinformatics 16, 944–945 (2000).

    Article  CAS  Google Scholar 

  9. Huang, W. & Marth, G. Genome Res. 18, 1538–1543 (2008).

    Article  CAS  Google Scholar 

  10. Bao, H. et al. Bioinformatics 25, 1554–1555 (2009).

    Article  CAS  Google Scholar 

  11. Milne, I. et al. Bioinformatics 26, 401–402 (2010).

    Article  CAS  Google Scholar 

  12. Fiume, M., Williams, V., Brook, A. & Brudno, M. Bioinformatics 26, 1938–1944 (2010).

    Article  CAS  Google Scholar 

  13. Lewis, S.E. et al. Genome Biol. 3, RESEARCH0082.1–0082.14 (2002).

  14. Nicol, J.W., Helt, G.A., Blanchard, S.G. Jr., Raja, A. & Loraine, A.E. Bioinformatics 25, 2730–2731 (2009).

    Article  CAS  Google Scholar 

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Acknowledgements

Thanks to M.-D. Nazaire, IGV software developer, J. Boehm, M. DePristo, M. Garber, M. Reich and B. Weir, who worked closely with the development team with suggestions for features and usability, and J. Bistline for expert assistance with figures. M. Garber provided source code for multiple alignment tracks. This work was supported by The National Institute of General Medical Sciences (R01GM074024), National Cancer Institute (R21CA135827) and National Human Genome Research Institute (U54HG003067).

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Authors and Affiliations

  1. Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts, USA

    James T Robinson, Helga Thorvaldsdóttir, Wendy Winckler, Mitchell Guttman, Eric S Lander, Gad Getz & Jill P Mesirov

  2. Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA

    Mitchell Guttman & Eric S Lander

  3. Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA

    Eric S Lander

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  1. James T Robinson
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  2. Helga Thorvaldsdóttir
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  6. Gad Getz
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  7. Jill P Mesirov
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Correspondence to James T Robinson or Jill P Mesirov.

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Supplementary Figs. 1–9, Supplementary Table 1 and Supplementary Notes (PDF 8477 kb)

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Robinson, J., Thorvaldsdóttir, H., Winckler, W. et al. Integrative genomics viewer. Nat Biotechnol 29, 24–26 (2011). https://doi.org/10.1038/nbt.1754

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