Abstract
Correlations between polymorphic markers and observed phenotypes provide the basis for mapping traits in quantitative genetics. When the phenotype is gene expression, then loci involved in regulatory control can theoretically be implicated. Recent efforts to construct gene regulatory networks from genotype and gene expression data have shown that biologically relevant networks can be achieved from an integrative approach. Inspired by epistatic models of multi-locus QTL mapping, we propose a unified model of expression and genotype representing cis- and trans-acting regulation. We demonstrate the power of the model in contrast to standard interval mapping by automatically discovering specific pairs of regulator-target genes in yeast. Our approach’s generality provides a convenient framework for inducing a regulatory network topology of directed and undirected weighted edges.
Keywords
- Quantitative Trait Locus
- Bayesian Network
- Quantitative Trait Locus Interval
- Conditional Probability Table
- Epistatic Model
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Kulp, D., Jagalur, M. (2007). Causal Inference of Regulator-Target Pairs by Gene Mapping of Expression Phenotypes. In: Eskin, E., Ideker, T., Raphael, B., Workman, C. (eds) Systems Biology and Regulatory Genomics. RSB RRG 2005 2005. Lecture Notes in Computer Science(), vol 4023. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-48540-7_9
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DOI: https://doi.org/10.1007/978-3-540-48540-7_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-48293-2
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