Greenawalt, D.M., Sieberts, S.K., Cornelis, M.C., Girman, C.J., Zhong, H., Integrating genetic association, genetics of gene expression, and single nucleotide polymorphism set analysis to identify susceptibility Loci for type 2 diabetes mellitus (2012) Am J Epidemiol, 176, pp. 423-430
Li, Q., Seo, J.H., Stranger, B., McKenna, A., Pe’er, I., Integrative eQTLbased analyses reveal the biology of breast cancer risk loci (2013) Cell, 152, pp. 633-641
Serizawa, R.R., Ralfkiaer, U., Steven, K., Lam, G.W., Schmiedel, S., Integrated genetic and epigenetic analysis of bladder cancer reveals an additive diagnostic value of FGFR3 mutations and hypermethylation events (2011) Int J Cancer, 129, pp. 78-87
Hamid, J.S., Hu, P., Roslin, N.M., Ling, V., Greenwood, C.M., Data integration in genetics and genomics: methods and challenges (2009) Hum Genomics Proteomics
Chadeau-Hyam, M., Campanella, G., Jombart, T., Bottolo, L., Portengen, L., Deciphering the complex: methodological overview of statistical models to derive OMICS-based biomarkers (2013) Env Mol Mutagen, 54, pp. 542-557
Kristensen, V.N., Lingjaerde, O.C., Russnes, H.G., Vollan, H.K., Frigessi, A., Principles and methods of integrative genomic analyses in cancer (2014) Nat Rev Cancer, 14, pp. 299-313
Ritchie, M.D., Holzinger, E.R., Li, R., Pendergrass, S.A., Kim, D., Methods of integrating data to uncover genotype–phenotype interactions (2015) Nat Rev Genet, 16, pp. 85-97
Shpak, M., Hall, A.W., Goldberg, M.M., Derryberry, D.Z., Ni, Y., An eQTL analysis of the human glioblastoma multiforme genome (2014) Genomics, 103, pp. 252-263
Bryois, J., Buil, A., Evans, D.M., Kemp, J.P., Montgomery, S.B., Cis and trans effects of human genomic variants on gene expression (2014) PLoS Genet, 10, p. e1004461
Drong, A.W., Nicholson, G., Hedman, A.K., Meduri, E., Grundberg, E., The presence of methylation quantitative trait loci indicates a direct genetic influence on the level of DNA methylation in adipose tissue (2013) PLoS One, 8, p. e55923
Heyn, H., Sayols, S., Moutinho, C., Vidal, E., Sanchez-Mut J, V., Linkage of DNA methylation quantitative trait Loci to human cancer risk (2014) Cell Rep, 7, pp. 331-338
Pineda, S., Gomez-Rubio, P., Picornell, A., Bessonov, K., Márquez, M., Framework for the Integration of Genomics, Epigenomics and Transcriptomics in Complex Diseases (2015) Hum Hered, 79, pp. 124-136
Parkhomenko, E., Tritchler, D., Beyene, J., Sparse canonical correlation analysis with application to genomic data integration (2009) Stat Appl Genet Mol Biol, 8
De Tayrac, M., Le, S., Aubry, M., Mosser, J., Husson, F., Simultaneous analysis of distinct Omics data sets with integration of biological knowledge: Multiple Factor Analysis approach (2009) BMC Genomics, 10, p. 32
Palermo, G., Piraino, P., Zucht, H.D., Performance of PLS regression coefficients in selecting variables for each response of a multivariate PLS for omics-type data (2009) Adv Appl Bioinform Chem, 2, pp. 57-70
Tibshirani, R., Regression Shrinkage and Selection via the Lasso (1996) J R Stat Soc Ser b, 58, pp. 267-288
Hui, Z.T.H., Regularization and variable selection via the Elastic Net (2005) J R Stat Soc Ser B, 67, pp. 301-320
Pineda, S., Milne, R.L., Calle, M.L., Rothman, N., López de Maturana, E., Genetic variation in the TP53 pathway and bladder cancer risk. a comprehensive analysis (2014) PLoS One, 9, p. e89952
Cho, S., Kim, K., Kim, Y.J., Lee, J.-K., Cho, Y.S., Joint identification of multiple genetic variants via elastic-net variable selection in a genome-wide association analysis (2010) Ann Hum Genet, 74, pp. 416-428
Zhou, H., Sehl, M.E., Sinsheimer, J.S., Lange, K., Association screening of common and rare genetic variants by penalized regression (2010) Bioinformatics, 26, pp. 2375-2382
Mankoo, P.K., Shen, R., Schultz, N., Levine, D.A., Sander, C., Time to recurrence and survival in serous ovarian tumors predicted from integrated genomic profiles (2011) PLoS One, 6, p. e24709
Westfall, P.H., Young, S.S., (1993)
Hoerl, A.E., Kennard, R.W., Ridge Regression: Biased Estimation for Nonorthogonal Problems (1970) Technometrics, 12, pp. 55-67
Trevor, H., Rob, T., Jerome, F., (2001)
Jerome, F., Trevor, H., Rob, T., (2010) Regularization Paths for Generalized Linear Models via Coordinate Descent J Stat Softw, 33
Ge, Y., Dudoit, S., Speed, T.P., Resampling-based multiple testing for microarray data analysis (2003) Test, 12, pp. 1-77
Browning, S.R., Browning, B.L., Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering (2007) Am J Hum Genet, 81, pp. 1084-1097
Zhu, Y., Qiu, P., Ji, Y., TCGA-assembler: open-source software for retrieving and processing TCGA data (2014) Nat Methods, 11, pp. 599-600
Dennis, G., Sherman, B.T., Hosack, D.A., Yang, J., Gao, W., DAVID: Database for Annotation, Visualization, and Integrated Discovery (2003) Genome Biol, 4, p. P3
Huang, D.W., Sherman, B.T., Lempicki, R.A., Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources (2009) Nat Protoc, 4, pp. 44-57
Benjamini, Y., Hochberg, Y., Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing (1995) J R Stat Soc Ser b, 57, p. 11
Choi, W., Czerniak, B., Ochoa, A., Su, X., Siefker-Radtke, A., Intrinsic basal and luminal subtypes of muscle-invasive bladder cancer (2014) Nat Rev Urol, 11, pp. 400-410
Knowles, M.A., Hurst, C.D., Molecular biology of bladder cancer: new insights into pathogenesis and clinical diversity (2014) Nat Rev Cancer, 15, pp. 25-41
Leung, D., Jung, I., Rajagopal, N., Schmitt, A., Selvaraj, S., Integrative analysis of haplotype-resolved epigenomes across human tissues (2015) Nature, 518, pp. 350-354
Waldmann, P., Mészáros, G., Gredler, B., Fuerst, C., Sölkner, J., Evaluation of the lasso and the elastic net in genome-wide association studies (2013) Front Genet, 4, p. 270
Wagner, J.R., Busche, S., Ge, B., Kwan, T., Pastinen, T., The relationship between DNA methylation, genetic and expression inter-individual variation in untransformed human fibroblasts (2014) Genome Biol, 15, p. R37
Bell, J.T., Pai, A.A., Pickrell, J.K., Gaffney, D.J., Pique-Regi, R., DNA methylation patterns associate with genetic and gene expression variation in HapMap cell lines (2011) Genome Biol, 12, p. R10
Mengual, L., Burset, M., Ribal, M.J., Ars, E., Marín-Aguilera, M., Gene expression signature in urine for diagnosing and assessing aggressiveness of bladder urothelial carcinoma (2010) Clin Cancer Res, 16, pp. 2624-2633
Van Oers, J.M.M., Wild, P.J., Burger, M., Denzinger, S., Stoehr, R., FGFR3 mutations and a normal CK20 staining pattern define low-grade noninvasive urothelial bladder tumours (2007) Eur Urol, 52, pp. 760-768
Byun, H.-M., Wong, H.-L., Birnstein, E.A., Wolff, E.M., Liang, G., Examination of IGF2 and H19 loss of imprinting in bladder cancer (2007) Cancer Res, 67, pp. 10753-10758
Wild, P.J., Herr, A., Wissmann, C., Stoehr, R., Rosenthal, A., Gene expression profiling of progressive papillary noninvasive carcinomas of the urinary bladder (2005) Clin Cancer Res, 11, pp. 4415-4429
Karagiannis, G.S., Pavlou, M.P., Diamandis, E.P., Cancer secretomics reveal pathophysiological pathways in cancer molecular oncology (2010) Mol Oncol, 4, pp. 496-510
Yao, R., Davidson, D.D., Lopez-Beltran, A., MacLennan, G.T., Montironi, R., The S100 proteins for screening and prognostic grading of bladder cancer (2007) Histol Histopathol, 22, pp. 1025-1032
Dokun, O.Y., Florl, A.R., Seifert, H.-H., Wolff, I., Schulz, W.A., Relationship of SNCG, S100A4, S100A9 and LCN2 gene expression and DNA methylation in bladder cancer (2008) Int J Cancer, 123, pp. 2798-2807
Minami, S., Sato, Y., Matsumoto, T., Kageyama, T., Kawashima, Y., Proteomic study of sera from patients with bladder cancer: usefulness of S100A8 and S100A9 proteins (2010) Cancer Genomics Proteomics, 7, pp. 181-189
Earl, J., Rico, D., Carrillo-de-Santa-Pau, E., Rodríguez-Santiago, B., Méndez-Pertuz, M., The UBC-40 Urothelial Bladder Cancer cell line index: a genomic resource for functional studies (2015) BMC Genomics, 16, p. 403
Meinshausen, N., Maathuis, M.H., Bühlmann, P., Asymptotic optimality of the Westfall–Young permutation procedure for multiple testing under dependence (2011) Ann Stat, 39, pp. 3369-3391
