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Computational resources for high-dimensional immune analysis from the Human Immunology Project Consortium

Nature Biotechnology volume 32, pages 146–148 (2014)Cite this article

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The human immune system forms a complex network of tissues, cells and molecules that protect against a wide variety of pathogens. It is sophisticated and adaptive in that it can distinguish self from non-self, and once it responds to a particular pathogen it exhibits 'memory', or heightened responsiveness, to that particular pathogen. This sophistication is facilitated in large part by the enormous diversity and large numbers of immune cell types, antigen receptors and cytokines. Although experiments in inbred mice housed in pathogen-free conditions have provided major insights into the mechanistic workings of the immune system, if we wish to understand how the immune system as a whole responds to a wide variety of pathogens, especially in outbred human populations, computational methods must be developed and databases created to track the many components and variables at play.

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Figure 1: HIPC data exchange workflow.

References

  1. Taylor, C.F., Field, D., Sansone, S.A. & Aerts, J. Nat. Biotechnol. 26, 889–896 (2008).

    Article  CAS  Google Scholar 

  2. Britten, C.M. et al. Immunity 37, 1–2 (2012).

    Article  CAS  Google Scholar 

  3. Brazma, A. et al. Nat. Genet. 29, 365–371 (2001).

    Article  CAS  Google Scholar 

  4. Lee, J.A. et al. Cytometry A 73A, 926–930 (2008).

    Article  Google Scholar 

  5. Ceusters, W. & Smith, B. Stud. Health Technol. Inform. 160, 1050–1054 (2010).

    PubMed  PubMed Central  Google Scholar 

  6. Siebert, J.C., Munsil, W., Rosenberg-Hasson, Y., Davis, M.M. & Maecker, H.T. J. Transl. Med. 10, 62 (2012).

    Article  Google Scholar 

  7. Maecker, H.T., McCoy, J.P. & Nussenblatt, R. Nat. Rev. Immunol. 12, 191–200 (2012).

    Article  CAS  Google Scholar 

  8. Aghaeepour, N. et al. Nat. Methods 10, 228–238 (2013).

    Article  CAS  Google Scholar 

  9. Lo, K., Brinkman, R.R. & Gottardo, R. Cytometry A 73A, 321–332 (2008).

    Article  Google Scholar 

  10. Newell, E.W., Sigal, N., Bendall, S.C., Nolan, G.P. & Davis, M.M. Immunity 36, 142–152 (2012).

    Article  CAS  Google Scholar 

  11. Horowitz, H. et al. Sci. Transl. Med. 5:208ra145 (2013).

    Article  Google Scholar 

  12. Amir, E.-A.D. et al. Nat. Biotechnol. 31, 545–552 (2013).

    Article  CAS  Google Scholar 

  13. Wang, C. et al. Proc. Natl. Acad. Sci. USA 109, 8676–8681 (2012).

    Article  CAS  Google Scholar 

  14. Lank, S.M. et al. BMC Genomics 13, 378 (2012).

    Article  CAS  Google Scholar 

  15. Reinhold, B., Keskin, D.B. & Reinherz, E.L. Anal. Chem. 82, 9090–9099 (2010).

    Article  CAS  Google Scholar 

  16. Nelson, E.K. et al. BMC Bioinformatics 12, 71 (2011).

    Article  Google Scholar 

  17. Ihaka, R. & Gentleman, R.R. J. Comput. Graph. Stat. 5, 299 (1996).

    Google Scholar 

  18. Gentleman, R.C. et al. Genome Biol. 5, R80 (2004).

    Article  Google Scholar 

  19. Xie, Y. Dynamic Report Generation with R and knitr (Chapman & Hall, 2013).

    Google Scholar 

Download references

Author information

Author notes

  1. Vladimir Brusic, Raphael Gottardo and Bali Pulendran: These authors contributed equally to this work.

Authors and Affiliations

  1. Cancer Vaccine Center, Dana-Farber Cancer Institute, Boston, Massachusetts, USA

    Vladimir Brusic & Ellis L Reinherz

  2. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA

    Raphael Gottardo

  3. Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, USA

    Steven H Kleinstein

  4. Department of Pathology, Yale School of Medicine, New Haven, Connecticut, USA

    Steven H Kleinstein

  5. and The Department of Microbiology and Immunology, The Howard Hughes Medical Institute, The Institute for Immunity, Transplantation and Infection, Stanford University, Stanford, California, USA

    Mark M Davis & Mark M Davis

  6. Departments of Neurology and Immunobiology, Yale University, New Haven, Connecticut, USA

    David A Hafler

  7. National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland, USA

    Helen Quill & Alkis Togias

  8. Baylor Institute for Immunology Research, Baylor Research Institute, Dallas, Texas, USA

    A Karolina Palucka

  9. Division of General Internal Medicine, Mayo Vaccine Research Group, Mayo Clinic, Rochester, Minnesota, USA

    Gregory A Poland

  10. Department of Pathology and Laboratory Medicine, Emory University, Atlanta, Georgia, USA

    Bali Pulendran

  11. Seattle Biomed, Seattle, USA

    Kenneth D Stuart

Authors
  1. Vladimir Brusic
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  2. Raphael Gottardo
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  3. Steven H Kleinstein
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  4. Mark M Davis
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Consortia

HIPC steering committee

  • Mark M Davis
  • , David A Hafler
  • , Helen Quill
  • , A Karolina Palucka
  • , Gregory A Poland
  • , Bali Pulendran
  • , Ellis L Reinherz
  • , Kenneth D Stuart
  •  & Alkis Togias

Corresponding authors

Correspondence to Vladimir Brusic or Raphael Gottardo.

Ethics declarations

Competing interests

G.A.P. is the chair of a Safety Evaluation Committee for novel investigational vaccine trials being conducted by Merck Research Laboratories. G.A.P. offers consultative advice on vaccine development to Merck & Co. Inc., CSL Biotherapies, Avianax, Sanofi Pasteur, Dynavax, Novartis Vaccines and Therapeutics, PAXVAX Inc. and Emergent Biosolutions. G.A.P. holds two patents related to vaccinia peptide research. These activities and the research published here have been reviewed by the Mayo Clinic Conflict of Interest Review Board and were conducted in compliance with Mayo Clinic Conflict of Interest policies.

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Brusic, V., Gottardo, R., Kleinstein, S. et al. Computational resources for high-dimensional immune analysis from the Human Immunology Project Consortium. Nat Biotechnol 32, 146–148 (2014). https://doi.org/10.1038/nbt.2777

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