trigger-net: Network-Trigger analysis
In igbucur/trigger: Transcriptional Regulatory Inference from Genetics of Gene ExpRession

Description Usage Arguments Details Value Author(s) References See Also Examples

Network-Trigger analysis estimates the joint posterior probability of causal regulation for each pair of genes in the genome. These probabilities can further be used to construct a gene regulatory network.

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  	## S4 method for signature 'trigger'
trigger.net(triggerobj, gender = NULL, idx = NULL, 
	Bsec = 100, prob.cut = 0.7, include.loc = TRUE, seed = 123, inputfile = NULL)

`triggerobj`	An object of class `trigger` containing slot `loc.obj` with local-linkage probabilities and marker indices of the best local-linkage markers for genes in the genome. See `trigger` and `trigger.loclink` for details.
`gender`	Optional. When computing statistics involving markers on sex chromosome, `gender` of each sample should be specified.
`idx`	Optional. One can specify the indices of selected genes as putative regulators. By default, all the genes will be selected as putative regulators.
`Bsec`	Number of iterations to perform when estimating null statistics for secondary-linkage and conditional independence.
`prob.cut`	Probability threshold. The joint regulatory probabilities of a regulator to all the other genes will be set to zero if the local-linkage probability of the regulator is below the threshold; default `prob.cut = 0.7`.
`include.loc`	Logical. If `TRUE`, the estimated posterior probability of regulation is more conservative.
`seed`	Optional. A numeric seed for reproducible results.
`inputfile`	Optional. If provided, reads in the probability matrix from working directory.

The option idx contains the indices of putative regulator genes. When the data set is large, one can use this option by selecting a subset of genes as putative regulators in one computation and parallel-computes the genome-wide regulatory probability. If idx=NULL, all the genes will be computed for probability of regulation to other genes in the data.

If include.loc = TRUE, the joint posterior probability of regulation is the product of local-linkage, secondary-linkage and conditional independence. Otherwise, it is the product of secondary-linkage and conditional independence. The local-linkage is not a necessary condition for calculating regulation probability. If the probability of local-linkage is considered, the joint probability of regulation is more conservative. See references for details.

A matrix of genome-wide regulatory probabilities with putative regulators in rows and regulated genes in columns. Note that the matrix is not symmetric. If gene i is estimated to be causal for gene j with high probability, the reverse is not true.

Lin S. Chen lschen.stat@gmail.com, Dipen P. Sangurdekar dps@genomics.princeton.edu and John D. Storey jstorey@princeton.edu

Chen L.S., Emmert-Streib F., and Storey J.D. (2007) Harnessing naturally randomized transcription to infer regulatory relationships among genes. Genome Biology, 8: R219.

trigger.loclink, trigger.netPlot2ps and trigger.trait

 ## Not run: 
  data(yeast)
  attach(yeast)
  triggerobj <- trigger.build(marker = marker, exp = exp, 
            marker.pos = marker.pos, exp.pos = exp.pos)
  triggerobj <- nettrig.loc(triggerobj, window.size = 30000)
  trig.prob <- trigger.net(triggerobj, Bsec = 100)
  netPlot2ps(trig.prob)
  detach(yeast)

## End(Not run)