title: Harnessing naturally randomized transcription to infer regulatory relationships among genes.
abstract: We develop an approach utilizing randomized genotypes to rigorously infer causal regulatory relationships among genes at the transcriptional level, based on experiments in which genotyping and expression profiling are performed. This approach can be used to build transcriptional regulatory networks and to identify putative regulators of genes. We apply the method to an experiment in yeast, in which genes known to be in the same processes and functions are recovered in the resulting transcriptional regulatory network.
authors.affiliation: Department of Biostatistics, University of Washington, 1705 NE Pacific St, Seattle, WA 98195, USA. chenlin@u.washington.edu
authors.forename: Lin S
authors.initials: LS
authors.lastname: Chen
authors.forename: Frank
authors.initials: F
authors.lastname: Emmert-Streib
authors.forename: John D
authors.initials: JD
authors.lastname: Storey
mesh_terms: D000465:Algorithms; D020869:Gene Expression Profiling / Q000379:methods*; D005786:Gene Expression Regulation / Q000235:genetics*; D053263:Gene Regulatory Networks / Q000235:genetics*; D005838:Genotype; D008957:Models, Genetic; D015003:Yeasts / Q000235:genetics / Q000378:metabolism