title: Evaluation and integration of 49 genome-wide experiments and the prediction of previously unknown obesity-related genes.
abstract: BACKGROUND
  Genome-wide experiments only rarely show resounding success in yielding genes associated with complex polygenic disorders. We evaluate 49 obesity-related genome-wide experiments with publicly available findings including microarray, genetics, proteomics and gene knock-down from human, mouse, rat and worm, in terms of their ability to rediscover a comprehensive set of genes previously found to be causally associated or having variants associated with obesity.
  
  
  RESULTS
  Individual experiments show poor predictive ability for rediscovering known obesity-associated genes. We show that intersecting the results of experiments significantly improves the sensitivity, specificity and precision of the prediction of obesity-associated genes. We create an integrative model that statistically significantly outperforms all 49 individual genome-wide experiments. We find that genes known to be associated with obesity are significantly implicated in more obesity-related experiments and use this to provide a list of genes that we predict to have the highest likelihood of association for obesity. The approach described here can include any number and type of genome-wide experiments and might be useful for other complex polygenic disorders as well.
authors.affiliation: Department of Medicine, Stanford Medical Informatics, Stanford University School of Medicine, Lucile Packard Children's Hospital, Stanford, CA 94305, USA.
authors.forename: Sangeeta B
authors.initials: SB
authors.lastname: English
authors.forename: Atul J
authors.initials: AJ
authors.lastname: Butte
mesh_terms: D000465:Algorithms; D015415:Biomarkers / Q000378:metabolism; D002874:Chromosome Mapping / Q000379:methods*; D030562:Databases, Protein; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods; D009765:Obesity / Q000378:metabolism*; D020543:Proteome / Q000378:metabolism*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D018511:Systems Integration
chemical_list: D015415:Biomarkers; D020543:Proteome