The Community for Technology Leaders
RSS Icon
Issue No.05 - Sept.-Oct. (2012 vol.9)
pp: 1442-1450
Pablo H. Hennings-Yeomans , Dept. of Biomed. Inf., Univ. of Pittsburgh, Pittsburgh, PA, USA
Gregory F. Cooper , Dept. of Biomed. Inf., Univ. of Pittsburgh, Pittsburgh, PA, USA
The prediction of patient's future clinical outcome, such as Alzheimer's and cardiac disease, using only genomic information is an open problem. In cases when genome-wide association studies (GWASs) are able to find strong associations between genomic predictors (e.g., SNPs) and disease, pattern recognition methods may be able to predict the disease well. Furthermore, by using signal processing methods, we can capitalize on latent multivariate interactions of genomic predictors. Such an approach to genomic pattern recognition for prediction of clinical outcomes is investigated in this work. In particular, we show how multiresolution transforms can be applied to genomic data to extract cues of multivariate interactions and, in some cases, improve on the predictive performance of clinical outcomes of standard classification methods. Our results show, for example, that an improvement of about 6 percent increase of the area under the ROC curve can be achieved using multiresolution spaces to train logistic regression to predict late-onset Alzheimer's disease (LOAD) compared to logistic regression applied directly on SNP data.
signal resolution, diseases, genomics, medical signal processing, pattern classification, polymorphism, regression analysis, sensitivity analysis, signal classification, ROC curve, genomic data, multiresolution analysis, patient future clinical outcome, Alzheimer's disease, cardiac disease, genomic information, genome-wide association study, GWAS, signal processing methods, latent multivariate interactions, genomic predictors, genomic pattern recognition, multiresolution transforms, multivariate interactions, standard classification methods, logistic regression, SNP data, single nucleotide polymorphisms, Bioinformatics, Genomics, Signal resolution, Discrete wavelet transforms, Training, Diseases, SNPs., Human genome, single nucleotide polymorphisms, multiresolution, pattern recognition, wavelets, prediction, clinical outcomes, genomics
Pablo H. Hennings-Yeomans, Gregory F. Cooper, "Improving the Prediction of Clinical Outcomes from Genomic Data Using Multiresolution Analysis", IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol.9, no. 5, pp. 1442-1450, Sept.-Oct. 2012, doi:10.1109/TCBB.2012.80
[1] M. Stephens and D.J. Balding, "Bayesian Statistical Methods for Genetic Association Studies," Nature Rev. Genetics, vol. 10, no. 10, pp. 681-690, Oct. 2009.
[2] J. Couzin-Frankel, "Major Heart Disease Genes Prove Elusive," Science, vol. 328, no. 5983, pp. 1220-1221, June 2010.
[3] H.J. Cordell, "Detecting Gene-Gene Interactions that Underlie Human Diseases," Nature Rev. Genetics, vol. 10, no. 6, pp. 392-404, June 2009.
[4] C.J. Hoggart, J.C. Whittaker, M. De Iorio, and D.J. Balding, "Simultaneous Analysis of All SNPs in Genome-Wide and Re-Sequencing Association Studies," PLoS Genetics, vol. 4, no. 7, p. e1000130, July 2008.
[5] Y. Zhang and J.S. Liu, "Bayesian Inference of Epistatic Interactions in Case-Control Studies," Nature Genetics, vol. 39, no. 9, pp. 1167-1173, Aug. 2007.
[6] A. Chebira, "Adaptive Multiresolution Frame Classification of Biomedical Images," PhD dissertation, Carnegie Mellon Univ., 2008.
[7] P. Hennings, J. Thornton, J. Kovačević, and B.V. Kumar, "Wavelet Packet Correlation Methods in Biometrics," Applied Optics, vol. 44, no. 5, pp. 637-646, 2005.
[8] P. Phillips, "Matching Pursuit Filters Applied to Face Identification," IEEE Trans. Image Processing, vol. 7, no. 8, pp. 1150-1164, Aug. 1998.
[9] S. Hutter, A.J. Vilella, and J. Rozas, "Genome-Wide DNA Polymorphism Analyses Using VariScan," BMC Bioinformatics, vol. 7, article 409, Sept. 2006.
[10] D. Botstein, R.L. White, M. Skolnick, and R.W. Davis, "Construction of a Genetic Linkage Map in Man Using Restriction Fragment Length Polymorphisms," Am. J. Human Genetics, vol. 32, no. 3, pp. 314-331, May 1980.
[11] R. Gibbs, "The International HapMap Project," Nature, vol. 426, no. 6968, pp. 789-796, Dec. 2003.
[12] J. Ragoussis, "Genotyping Technologies for Genetic Research," Ann. Rev. Genomics and Human Genetics, vol. 10, no. 1, pp. 117-133, Sept. 2009.
[13] C.M. Bishop, Pattern Recognition and Machine Learning. Springer, 2006.
[14] M. Vetterli, J. Kovačević, and V. Goyal, The World of Fourier and Wavelets: Theory, Algorithms and Applications, http:/, 2011.
[15] S. Mallat, A Wavelet Tour of Signal Processing. Academic Press, 1999.
[16] R.L. Plackett, "Karl Pearson and the Chi-Squared Test," Int'l Statistical Rev., vol. 51, no. 1, pp. 59-72, Apr. 1983.
[17] E.M. Reiman et al., "GAB2 Alleles Modify Alzheimer's Risk in APOE E4 Carriers," Neuron, 54, no. 5, pp. 713-720, June 2007.
[18] P. Scheet and M. Stephens, "A Fast and Flexible Statistical Model for Large-Scale Population Genotype Data: Applications to Inferring Missing Genotypes and Haplotypic Phase," The Am. J. Human Genetics, vol. 78, no. 4, pp. 629-644, Apr. 2006.
[19] S. Purcell, B. Neale, K. Todd-Brown, L. Thomas, M.A.R. Ferreira, D. Bender, J. Maller, P. Sklar, P.I.W. de Bakker, M.J. Daly, and P.C. Sham, "PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses," The Am. J. Human Genetics, vol. 81, no. 3, pp. 559-575, Sept. 2007.
[20] R.R. Coifman and D. Donoho, Translation-Invariant De-Noising, pp. 125-150, Springer-Verlag, 1995.
[21] C.M. Lewis, "Genetic Association Studies: Design, Analysis and Interpretation," Briefings in Bioinformatics, vol. 3, no. 2, pp. 146-153, 2002.
[22] D.M.D. Elizabeth, R. DeLong, and D.L. Clarke-Pearson, "Comparing the Areas under Two or More Correlated Receiver Operating Characteristic Curves: A Nonparametric Approach," Biometrics, vol. 44, no. 3, pp. 837-845, Sept. 1988.
[23] J.H. Lee et al., "Analyses of the National Institute on Aging Late-Onset Alzheimer's Disease Family Study: Implication of Additional Loci," Archives of Neurology, vol. 65, no. 11, pp. 1518-1526, Nov. 2008.
[24] M.L. Metzker, "Sequencing Technologies - The Next Generation," Nature Rev. Genetics, vol. 11, no. 1, pp. 31-46, Jan. 2010.
10 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool