title: Genes Caught In Flagranti: Integrating Renal Transcriptional Profiles With Genotypes and Phenotypes.
abstract: In the past decade, population genetics has gained tremendous success in identifying genetic variations that are statistically relevant to renal diseases and kidney function. However, it is challenging to interpret the functional relevance of the genetic variations found by population genetics studies. In this review, we discuss studies that integrate multiple levels of data, especially transcriptome profiles and phenotype data, to assign functional roles of genetic variations involved in kidney function. Furthermore, we introduce state-of-the-art machine learning algorithms, Bayesian networks, support vector machines, and Gaussian process regression, which have been applied successfully to integrating genetic, regulatory, and clinical information to predict clinical outcomes. These methods are likely to be deployed successfully in the nephrology field in the near future.
authors.affiliation: Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI; Department of Internal Medicine, University of Michigan, Ann Arbor, MI; Department of Computer Science and Engineering, University of Michigan, Ann Arbor, MI.
authors.forename: Yuanfang
authors.initials: Y
authors.lastname: Guan
authors.affiliation: Department of Internal Medicine, University of Michigan, Ann Arbor, MI; Nephrologisches Zentrum, Medizinische Klinik und Poliklinik IV, Klinikum der Universität München, Ludwig-Maximilians-University Munich, Munich, Germany.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Martini
authors.affiliation: Department of Internal Medicine, University of Michigan, Ann Arbor, MI.
authors.forename: Laura H
authors.initials: LH
authors.lastname: Mariani
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D020869:Gene Expression Profiling / Q000379:methods*; D053263:Gene Regulatory Networks / Q000235:genetics*; D005838:Genotype; D006801:Humans; D007674:Kidney Diseases / Q000235:genetics* / Q000378:metabolism; D010641:Phenotype; D011379:Prognosis
keywords: Gene regulation; SNP; clinical outcomes; predictions