1,195
Views
13
CrossRef citations to date
0
Altmetric
Theory and Methods

Multiple Testing of Submatrices of a Precision Matrix With Applications to Identification of Between Pathway Interactions

, &
Pages 328-339 | Received 01 Aug 2015, Accepted 01 Oct 2016, Published online: 26 Sep 2017

References

  • Anderson, T. W. (2003), An Introduction To Multivariate Statistical Analysis (3rd ed.), New York: Wiley-Intersceince.
  • Benjamini, Y., and Hochberg, Y. (1995), “Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing,” Journal of the Royal Statistical Society, Series B, 57, 289–300.
  • Beran, R., Bilodeau, M., and de Micheaux, P. L. (2007), “Nonparametric Tests of Independence Between Random Vectors,” Journal of Multivariate Analysis, 98, 1805–1824.
  • Cai, T. T., and Liu, W. (2015), “Large-Scale Multiple Testing of Correlations,” Journal of the American Statistical Association, 110, 229–240.
  • Cai, T. T., Liu, W., and Xia, Y. (2013), “Two-Sample Covariance Matrix Testing and Support Recovery in High-Dimensional and Sparse Settings,” Journal of the American Statistical Association, 108, 265–277.
  • Cai, T. T., and Zhang, A. (2014), “Inference on High-Dimensional Differential Correlation Matrix,” arXiv:1408.5907.
  • Carracedo, A., Ma, L., Teruya-Feldstein, J., Rojo, F., Salmena, L., Alimonti, A., Egia, A., Sasaki, A. T., Thomas, G., Kozma, S. C., Papa, A., Nardella, C., Cantley, L. C., Baselga, J., and Pandolfi, P. P. (2008), “Inhibition of mTORC1 Leads to MAPK Pathway Activation Through a pi3k-Dependent Feedback Loop in Human Cancer,” The Journal of Clinical Investigation, 118, 3065.
  • Chatterjee, N., Kalaylioglu, Z., Moslehi, R., Peters, U., and Wacholder, S. (2006), “Powerful Multilocus Tests of Genetic Association in the Presence of Gene–Gene and Gene–Environment Interactions,” The American Journal of Human Genetics, 79, 1002–1016.
  • Craven, M., and Kumlien, J. (1999), “Constructing Biological Knowledge Bases by Extracting Information From Text Sources,” in Proceedings of the International Conference on Intelligent Systems for Molecular Biology (Vol. 1999), Palo Alto, CA: AAAI Press, pp. 77–86.
  • Fan, J., and Lv, J. (2008), “Sure Independence Screening for Ultra-High Dimensional Feature Space” (with discussion), Journal of the Royal Statistical Society, Series B, 70, 849–911.
  • Gieser, P. W., and Randles, R. H. (1997), “A Nonparametric Test of Independence Between Two Vectors,” Journal of the American Statistical Association, 92, 561–567.
  • Glazko, G. V., and Emmert-Streib, F. (2009), “Unite and Conquer: Univariate and Multivariate Approaches for Finding Differentially Expressed Gene Sets,” Bioinformatics, 25, 2348–2354.
  • Guo, X., and Wang, X.-F. (2008), “Signaling Cross-Talk Between tgf-β/bmp and Other Pathways,” Cell Research, 19, 71–88.
  • Huang, T.-M., et al. (2010), “Testing Conditional Independence Using Maximal Nonlinear Conditional Correlation,” The Annals of Statistics, 38, 2047–2091.
  • Jia, P., Kao, C.-F., Kuo, P.-H., and Zhao, Z. (2011), “A Comprehensive Network and Pathway Analysis of Candidate Genes in Major Depressive Disorder,” BMC Systems Biology, 5, S12.
  • Kelley, R., and Ideker, T. (2005), “Systematic Interpretation of Genetic Interactions Using Protein Networks,” Nature Biotechnology, 23, 561–566.
  • Khatri, P., Sirota, M., and Butte, A. J. (2012), “Ten Years of Pathway Analysis: Current Approaches and Outstanding Challenges,” PLoS Computational Biology, 8, e1002375.
  • Kooperberg, C., and LeBlanc, M. (2008), “Increasing the Power of Identifying Gene × Gene Interactions in Genome-Wide Association Studies,” Genetic Epidemiology, 32, 255–263.
  • Kooperberg, C., and Ruczinski, I. (2005), “Identifying Interacting snps Using Monte Carlo Logic Regression,” Genetic Epidemiology, 28, 157–170.
  • Kouzmenko, A. P., Takeyama, K.-i., Ito, S., Furutani, T., Sawatsubashi, S., Maki, A., Suzuki, E., Kawasaki, Y., Akiyama, T., Tabata, T., et al. (2004), “Wnt/β-Catenin and Estrogen Signaling Converge in vivo,” Journal of Biological Chemistry, 279, 40255–40258.
  • Lauritzen, S. L. (1996), Graphical Models (Vol. 17), Oxford, UK: Oxford University Press.
  • Li, Y., Agarwal, P., and Rajagopalan, D. (2008), “A Global Pathway Crosstalk Network,” Bioinformatics, 24, 1442–1447.
  • Liu, H., Han, F., Yuan, M., Lafferty, J., Wasserman, L., et al. (2012), “High-Dimensional Semiparametric Gaussian Copula Graphical Models,” Annals of Statistics, 40, 2293–2326.
  • Liu, H., Tang, Y., and Zhang, H. H. (2009), “A New Chi-Square Approximation to the Distribution of Non-Negative Definite Quadratic Forms in Non-Central Normal Variables,” Computational Statistics and Data Analysis, 53, 853–856.
  • Liu, W. (2013), “Gaussian Graphical Model Estimation With False Discovery Rate Control,” Annals of Statistics, 41, 2948–2978.
  • Liu, W., and Shao, Q.-M. (2014), “Phase Transition and Regularized Bootstrap in Large Scale t-Tests With False Discovery Rate Control,” Annals of Statistics, 42, 2003–2025.
  • Liu, Z.-P., Wang, Y., Zhang, X.-S., and Chen, L. (2010), “Identifying Dysfunctional Crosstalk of Pathways in Various Regions of Alzheimer’s Disease Brains,” BMC Systems Biology, 4, S11.
  • Matthews, L., Gopinath, G., Gillespie, M., Caudy, M., Croft, D., de Bono, B., Garapati, P., Hemish, J., Hermjakob, H., Jassal, B., and Kanapin, A. (2009), “Reactome Knowledgebase of Human Biological Pathways and Processes,” Nucleic Acids Research, 37, D619–D622.
  • Osborne, C. K., Shou, J., Massarweh, S., and Schiff, R. (2005), “Crosstalk Between Estrogen Receptor and Growth Factor Receptor Pathways as a Cause for Endocrine Therapy Resistance in Breast Cancer,” Clinical Cancer Research, 11, 865s–870s.
  • Pan, X.-H. (2012), “Pathway Crosstalk Analysis Based on Protein-Protein Network Analysis in Ovarian Cancer,” Asian Pacific Journal of Cancer Prevention, 13, 3905–3909.
  • Puri, N., and Salgia, R. (2008), “Synergism of egfr and c-met Pathways, Cross-Talk and Inhibition, in Non-Small Cell Lung Cancer,” Journal of Carcinogenesis, 7, 9.
  • Ritchie, M., Hahn, L., Roodi, N., Bailey, L., Dupont, W., Parl, F., and Moore, J. (2001), “Multifactor-Dimensionality Reduction Reveals High-Order Interactions Among Estrogen-Metabolism Genes in Sporadic Breast Cancer,” American Journal of Human Genetics, 69, 138–147.
  • Rual, J.-F., Venkatesan, K., Hao, T., Hirozane-Kishikawa, T., Dricot, A., Li, N., Berriz, G. F., Gibbons, F. D., Dreze, M., Ayivi-Guedehoussou, N., and Klitgord, N. (2005), “Towards a Proteome-Scale Map of the Human Protein–Protein Interaction Network,” Nature, 437, 1173–1178.
  • Shou, J., Massarweh, S., Osborne, C. K., Wakeling, A. E., Ali, S., Weiss, H., and Schiff, R. (2004), “Mechanisms of Tamoxifen Resistance: Increased Estrogen Receptor-her2/neu Cross-Talk in er/her2–Positive Breast Cancer,” Journal of the National Cancer Institute, 96, 926–935.
  • Su, L., and White, H. (2007), “A Consistent Characteristic Function-Based Test for Conditional Independence,” Journal of Econometrics, 141, 807–834.
  • Su, L., and White, H. (2008), “A Nonparametric Hellinger Metric Test for Conditional Independence,” Econometric Theory, 24, 829–864.
  • Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., and Mesirov, J. P. (2005), “Gene Set Enrichment Analysis: A Knowledge-Based Approach for Interpreting Genome-Wide Expression Profiles,” Proceedings of the National Academy of Sciences of the United States of America, 102, 15545–15550.
  • Um, Y., and Randles, R. H. (2001), “A Multivariate Nonparametric Test of Independence Among Many Vectors,” Journal of Nonparametric Statistics, 13, 699–708.
  • van’t Veer, L. J., Dai, H., Van De Vijver, M. J., He, Y. D., Hart, A. A., Mao, M., Peterse, H. L., van der Kooy, K., Marton, M. J., Witteveen, A. T., and Schreiber, G. J. (2002), “Gene Expression Profiling Predicts Clinical Outcome of Breast Cancer,” Nature, 415, 530–536.
  • Weirauch, M. T. (2011), “Gene Coexpression Networks for the Analysis of dna Microarray Data,” Applied Statistics for Network Biology: Methods in Systems Biology, 215–250.
  • Xenarios, I., Salwinski, L., Duan, X. J., Higney, P., Kim, S.-M., and Eisenberg, D. (2002), “Dip, the Database of Interacting Proteins: A Research Tool for Studying Cellular Networks of Protein Interactions,” Nucleic Acids Research, 30, 303–305.
  • Xia, Y., Cai, T., and Cai, T. T. (2015), “Testing Differential Networks With Applications to the Detection of Gene–Gene Interactions,” Biometrika, 102, 247–266.
  • ——— (2016), “Supplement to “Multiple Testing of Submatrices of a Precision Matrix with Applications to Identification of Between Pathway Interactions,” Technical report.
  • Xue, L., and Zou, H. (2012), “Regularized Rank-Based Estimation of High-Dimensional Nonparanormal Graphical Models,” Annals of Statistics, 40, 2541–2571.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.