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On the Role and Potential of High-Dimensional Biologic Data in Cancer Research

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High-Dimensional Data Analysis in Cancer Research

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References

  • Amundadottir, L., Sulem, P., Gudmundsson, J., et al. (2006). A common variant associated with prostate cancer in european and african populations. Nature Genetics, 38(6):652–658.

    Article  PubMed  CAS  Google Scholar 

  • Benjamini, Y. and Hochberg, Y. (1995). Controlling for false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B, 57:289–300.

    Google Scholar 

  • Druker, B. J., Guilhot, F., O’Brien, S. G., et al. (2006). Five-year follow-up of patients receiving imatinib for chronic myeloid leukemia. New England Journal of Medicine, 355(23):2408–2417.

    Article  PubMed  CAS  Google Scholar 

  • Easton, D., Pooley, K., Dunning, A., et al. (2007). Genome-wide association study identifies novel breast cancer susceptibility loci. Nature, 447(7148): 1087–1093.

    Article  PubMed  CAS  Google Scholar 

  • Efron, B. (2004). Large-scale simultaneous hypothesis testing: The choice of a null hypothesis. Journal of the American Statistical Association, 99:96–104.

    Article  Google Scholar 

  • Faca, V., Coram, M., Phanstiel, D., et al. (2006). Quantitative analysis of acrylamide labeled serum proteins by lc-ms/ms. Journal of Proteome Research, 5(8):2009–2018.

    Article  PubMed  CAS  Google Scholar 

  • Felsenstein, J. (2007). Theoretical Evolutionary Genetics. University of Washington/ASUW Publishing, Seattle, WA.

    Google Scholar 

  • Freedman, M. L., Haiman, C. A., Patterson, N., et al. (2006). Admixture mapping identifies 8q24 as a prostate cancer risk locus in african-american men. Proceedings of the National Academy of Sciences, 103(38):14068–14073.

    Article  CAS  Google Scholar 

  • Golub, T. R., Slonim, D. K., Tamayo, P., et al. (1999). Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science, 286(5439):531–537.

    Article  PubMed  CAS  Google Scholar 

  • Hinds, D. A., Stuve, L. L., Nilsen, G. B., et al. (2005). Whole-genome patterns of common DNA variation in three human populations. Science, 307(5712):1072–1079.

    Article  PubMed  CAS  Google Scholar 

  • Hunter, D. J., Kraft, P., Jacobs, K. B., et al. (2007). A genome-wide association study identifies alleles in fgfr2 associated with risk of sporadic postmenopausal breast cancer. Nature Genetics, 39(6):870–874.

    Article  PubMed  CAS  Google Scholar 

  • Khatri, P. and Draghici, S. (2005). Ontological analysis of gene expression data: current tools, limitations, and open problems. Bioinformatics, 18:3587–3595.

    Article  Google Scholar 

  • Ott, J. (1991). Analysis of Human Genetic Linkage. Johns Hopkins University Press, Baltimore, MD.

    Google Scholar 

  • Piccart-Gebhart, M. J., Procter, M., Leyland-Jones, B., et al. (2005). Trastuzumab after adjuvant chemotherapy in her2-positive breast cancer. New England Journal of Medicine, 353(16):1659–1672.

    Article  PubMed  CAS  Google Scholar 

  • Prentice, R. and Qi, L. (2006). Aspects of the design and analysis of high-dimensional snp studies for disease risk estimation. Biostatistics, 7:339–354.

    Article  PubMed  Google Scholar 

  • Rouzier, R., Perou, C. M., Symmans, W. F., et al. (2005). Breast cancer molecular subtypes respond differently to preoperative chemotherapy. Clinical Cancer Research, 11(16):5678–5685.

    Article  PubMed  CAS  Google Scholar 

  • Ruczinski, I., Kooperberg, C., and LeBlanc, M. (2003). Logic regression. Journal of Computational and Graphical Statististics, 12:475–511.

    Article  Google Scholar 

  • Samani, N. J., Erdmann, J., Hall, A. S., et al. (2007). Genomewide association analysis of coronary artery disease. New England Journal of Medicine, 357(5):443–453.

    Article  PubMed  CAS  Google Scholar 

  • Shurubor, Y., Matson, W., Martin, R., et al. (2005). Relative contribution of specific sources of systematic errors and analytic imprecision to metabolite analysis by hplc-ecd. Metabolomics, 1:159–168.

    Article  CAS  Google Scholar 

  • The International HapMap Consortium (2003). The international hapmap project. Nature, 426(6968):789–796.

    Google Scholar 

  • The Women's Health Initiative Steering Committee (2004). Effects of conjugated equine estrogen in postmenopausal women with hysterectomy: The women's health initiative randomized controlled trial. JAMA, 291(14):1701–1712.

    Google Scholar 

  • Thomas, D. (2004). Statistical Methods in Genetic Epidemiology. Oxford University Press, London.

    Google Scholar 

  • Tibshirani, R. (1996). Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society B, 58:267–288.

    Google Scholar 

  • Wang, X., Yu, J., Sreekumar, A., et al. (2005). Autoantibody signatures in prostate cancer. New England Journal of Medicine, 353(12):1224–1235.

    Article  PubMed  CAS  Google Scholar 

  • Writing Group for the Women's Health Initiative Investigators (2002). Risks and benefits of estrogen plus progestin in healthy postmenopausal women: Principal results from the women's health initiative randomized controlled trial. Journal of the American Medical Association, 288(3):321–333.

    Google Scholar 

  • Yeager, M., N., O., Hayes, R. B., et al. (2007). Genome-wide association study of prostate cancer identifies a second risk locus at 8q24. Nature Genetics, 39(5):645–649.

    Article  PubMed  CAS  Google Scholar 

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Author information

Authors and Affiliations

  1. Division of Public Health Sciences, Division of Public Health Sciences, 1100 Fairview Avenue North, Seattle, WA, USA

    Ross L. Prentice

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  1. Ross L. Prentice
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Correspondence to Ross L. Prentice .

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Editors and Affiliations

  1. School of Medicine, Division of Biostatistics, Indiana University, West 10th Street 410 , Indianapolis, 46202, U.S.A.

    Xiaochun Li

  2. Dept. Mathematics, University of California, San Diego, Gilman Dr. 9500, La Jolla, 92093-0112, U.S.A.

    Ronghui Xu

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Prentice, R.L. (2009). On the Role and Potential of High-Dimensional Biologic Data in Cancer Research. In: Li, X., Xu, R. (eds) High-Dimensional Data Analysis in Cancer Research. Applied Bioinformatics and Biostatistics in Cancer Research. Springer, New York, NY. https://doi.org/10.1007/978-0-387-69765-9_1

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