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References
Schatz, M.C., Langmead, B. & Salzberg, S.L. Nat. Biotechnol. 28, 691–693 (2010).
Lieberman-Aiden, E. et al. Science 326, 289–293 (2009).
Pepke, S., Wold, B. & Mortazavi, A. Nat. Methods 6, S22–S32 (2009).
Wang, Z., Gerstein, M. & Snyder, M. Nat. Rev. Genet. 10, 57–63 (2009).
Stein, L. Genome Biol. 11, 207 (2010).
Langmead, B., Hansen, K.D. & Leek, J.T. Genome Biol. 11, R83 (2010).
Langmead, B., Schatz, M.C., Lin, J., Pop, M. & Salzberg, S.L. Genome Biol. 10, R134 (2009).
Schatz, M.C. Bioinformatics 25, 1363–1369 (2009).
The 1000 Genomes Project Consortium. Nature 467, 1061–1073 (2010).
Goecks, J., Nekrutenko, A. & Taylor, J. Genome Biol. 11, R86 (2010).
Afgan, E. et al. in Guide to e-Science: Next Generation Scientific Research and Discovery (ed. Yang, K.) 35 (Springer, New York, 2011).
Afgan, E. et al. BMC Bioinformatics 11 Suppl 12, S4 (2010).
DiMauro, S. Mitochondrion 4, 799–807 (2004).
Taylor, R.W. & Turnbull, D.M. Nat. Rev. Genet. 6, 389–402 (2005).
Goto, H., Dickins, B., Afgan, E., Paul, I.M., Taylor, J., Makova, K.D., Nekrutenko, A. Genome Biol. 12, R59 (2011).
Acknowledgements
The authors are grateful to J. Beiler for coordinating sample collection, to clinical nurses from Penn State College of Medicine's Pediatric Clinical Research Office for collecting the samples and to volunteers for donating the samples. Efforts of the Galaxy Team (E.A., D.B., D. Blankenberg, N.C., J. Goecks, G. Von Kuster, R. Lazarus, K. Li & K. Vincent) were instrumental for making this work happen. This work was funded by US National Institutes of Health (NIH) grants HG005133 and HG005542 to J.T. and A.N., US National Science Foundation grant DBI 0543285 and NIH grant HG004909 to A.N. and J.T., and NIH grant GM07226405S2 to K.D.M. Additional funding is provided, in part, under a grant with the Pennsylvania Department of Health using Tobacco Settlement Funds. The Department specifically disclaims responsibility for any analyses, interpretations or conclusions.
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Harnessing cloud-computing for biomedical research with Galaxy Cloud (PDF 229 kb)
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Afgan, E., Baker, D., Coraor, N. et al. Harnessing cloud computing with Galaxy Cloud. Nat Biotechnol 29, 972–974 (2011). https://doi.org/10.1038/nbt.2028
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DOI: https://doi.org/10.1038/nbt.2028
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