title: Correcting for link loss in causal network inference caused by regulator interference.
abstract: BACKGROUND
  There are a number of algorithms to infer causal regulatory networks from time series (gene expression) data. Here we analyse the phenomena of regulator interference, where regulators with similar dynamics mutually suppress both the probability of regulating a target and the associated link strength; for instance, interference between two identical strong regulators reduces link probabilities by ∼50%.
  
  
  RESULTS
  We construct a robust method to define an interference-corrected causal network based on an analysis of the conditional link probabilities that recovers links lost through interference. On a large real network (Streptomyces coelicolor, phosphate depletion), we demonstrate that significant interference can occur between regulators with a correlation as low as 0.865, losing an estimated 34% of links by interference. However, levels of interference cannot be predicted from the correlation between regulators alone and are data specific. Validating against known networks, we show that high numbers of functional links are lost by regulator interference. Performance against other methods on DREAM4 data is excellent.
  
  
  METHODS
  The method is implemented in R and is publicly available as the NIACS package at http://www2.warwick.ac.uk/fac/sci/systemsbiology/research/software.
authors.affiliation: Warwick Systems Biology Centre and School of Life Sciences, University of Warwick, Coventry CV4 7AL, UK.
authors.forename: Ying
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Warwick Systems Biology Centre and School of Life Sciences, University of Warwick, Coventry CV4 7AL, UK.
authors.forename: Christopher A
authors.initials: CA
authors.lastname: Penfold
authors.affiliation: Warwick Systems Biology Centre and School of Life Sciences, University of Warwick, Coventry CV4 7AL, UK.
authors.forename: David A
authors.initials: DA
authors.lastname: Hodgson
authors.affiliation: Warwick Systems Biology Centre and School of Life Sciences, University of Warwick, Coventry CV4 7AL, UK.
authors.forename: Miriam L
authors.initials: ML
authors.lastname: Gifford
authors.affiliation: Warwick Systems Biology Centre and School of Life Sciences, University of Warwick, Coventry CV4 7AL, UK.
authors.forename: Nigel J
authors.initials: NJ
authors.lastname: Burroughs
mesh_terms: D000465:Algorithms; D017360:Arabidopsis / Q000378:metabolism; D002940:Circadian Rhythm; D019295:Computational Biology / Q000379:methods; D015870:Gene Expression; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D015233:Models, Statistical; D011336:Probability; D011381:Programming Languages; D048372:Streptomyces coelicolor / Q000378:metabolism