title: A statistical framework for revealing signaling pathways perturbed by DNA variants.
abstract: Much of the inter-individual variation in gene expression is triggered via perturbations of signaling networks by DNA variants. We present a novel probabilistic approach for identifying the particular pathways by which DNA variants perturb the signaling network. Our procedure, called PINE, relies on a systematic integration of established biological knowledge of signaling networks with data on transcriptional responses to various experimental conditions. Unlike previous approaches, PINE provides statistical aspects that are critical for prioritizing hypotheses for followup experiments. Using simulated data, we show that higher accuracy is attained with PINE than with existing methods. We used PINE to analyze transcriptional responses of immune dendritic cells to several pathogenic stimulations. PINE identified statistically significant genetic perturbations in the pathogen-sensing signaling network, suggesting previously uncharacterized regulatory mechanisms for functional DNA variants.
authors.affiliation: Department of Cell Research and Immunology, The George S. Wise Faculty of Life Sciences, Tel Aviv University, 6997801 Tel Aviv, Israel.
authors.forename: Roni
authors.initials: R
authors.lastname: Wilentzik
authors.affiliation: Department of Cell Research and Immunology, The George S. Wise Faculty of Life Sciences, Tel Aviv University, 6997801 Tel Aviv, Israel iritgv@post.tau.ac.il.
authors.forename: Irit
authors.initials: I
authors.lastname: Gat-Viks
mesh_terms: D000465:Algorithms; D000818:Animals; D004247:DNA / Q000737:chemistry; D003713:Dendritic Cells / Q000378:metabolism; D014644:Genetic Variation; D005838:Genotype; D051379:Mice; D015233:Models, Statistical; D015398:Signal Transduction / Q000235:genetics*; D051193:Toll-Like Receptors / Q000819:agonists; D014158:Transcription, Genetic
chemical_list: D051193:Toll-Like Receptors; D004247:DNA