title: Partial correlation analysis indicates causal relationships between GC-content, exon density and recombination rate in the human genome.
abstract: BACKGROUND
  Several features are known to correlate with the GC-content in the human genome, including recombination rate, gene density and distance to telomere. However, by testing for pairwise correlation only, it is impossible to distinguish direct associations from indirect ones and to distinguish between causes and effects.
  
  
  RESULTS
  We use partial correlations to construct partially directed graphs for the following four variables: GC-content, recombination rate, exon density and distance-to-telomere. Recombination rate and exon density are unconditionally uncorrelated, but become inversely correlated by conditioning on GC-content. This pattern indicates a model where recombination rate and exon density are two independent causes of GC-content variation.
  
  
  CONCLUSIONS
  Causal inference and graphical models are useful methods to understand genome evolution and the mechanisms of isochore evolution in the human genome.
authors.affiliation: The Robert S Boas Center for Genomics and Human GeneticsFeinstein Institute for Medical Research, North Shore LIJ Health System, Manhasset, NY 11030, USA. jan.freudenberg@gmail.com
authors.forename: Jan
authors.initials: J
authors.lastname: Freudenberg
authors.forename: Mingyi
authors.initials: M
authors.lastname: Wang
authors.forename: Yaning
authors.initials: Y
authors.lastname: Yang
authors.forename: Wentian
authors.initials: W
authors.lastname: Li
mesh_terms: D001482:Base Composition; D003198:Computer Simulation; D019143:Evolution, Molecular; D005091:Exons; D015894:Genome, Human; D023281:Genomics; D006801:Humans; D011995:Recombination, Genetic / Q000235:genetics*; D016615:Telomere / Q000235:genetics / Q000378:metabolism