BetaMixture-class {PANR} | R Documentation

## An S4 class for beta mixture modelling of functional gene associations

### Description

This S4 class includes methods to do beta-mixture modelling of functional gene associations given rich phenotyping screens.

### Objects from the Class

Objects of class `BetaMixture` can be created from `new("BetaMixture", metric, order, association, model, pheno, partition)` (see the example below for details).

### Slots

`pheno`:

  a numeric matrix of rich phenotypes with rows and columns specifying genes and samples, respectively.

`metric`:

  a character value specifying the metric to compute similarity scores. Currently, 'cosine' and 'correlation' are supported (see `assoScore` for more details).

`order`:

  a numeric value specifying the order of the similarity score to be computed. Only 1 and 2 is supported for the current version. The first order (when `order=1`) similarities are used for quatification of the strength of functional associations between genes, whilst the second order (when `code=2`) ones are employed to compute the strength of modularity between genes.

`association`:

  a numeric vector providing all association scores between genes. This can be useful when `pheno` is not available or the user has a different way to compute functional associations.

`model`:

  a character value specifying whether the original (if `global`) or extended (if `stratified`) model is used.

`partition`:

  a numeric of gene partition labels (e.g. c(rep(1, 100), rep(2, 20), rep(3, 80)) is a valid vector of partition labels for a vector of associations falling into three categories of interaction types 1, 2 and 3).

`result`:

  a list storing results from S4 methods of this class.

`summary`:

  a list of summary information for available results.

### Methods

An overview of methods (More detailed introduction can be found in help for each specific function.):

`permNULL`

  do permutations for input rich phenotyping screens (`'pheno'`).

`fitNULL`

  fit the permuted association scores to a beta distribution.

`fitBM`

  fit the functional association scores computed from input screens to a three-beta mixture model.

`p2SNR`

  Translate p-values to Signal-to-Noise Ratios.

`SNR2p`

  Translate Signal-to-Noise Ratios to p-values.

`view`

  view the fitting results (a histogram of the original data and fitted probability density curves) for NULL and real data.

`summarize`

  summarize results including input data and parameters, NULL fitting and beta mixture fitting.

### Author(s)

Xin Wang xw264@cam.ac.uk

### References

Xin Wang, Mauro Castro, Klaas W. Mulder and Florian Markowetz, Posterior association networks and enriched functional gene modules inferred from rich phenotypic perturbation screens, in preparation.

### See Also

`permNULL` `fitNULL` `fitBM` `view` `summarize`

### Examples

    ## Not run:
    	data(Bakal2007)
    	bm1<-new("BetaMixture", pheno=Bakal2007, metric="cosine",
    		model="global", order=1)
    	bm1<-fitNULL(bm1, nPerm=10, thetaNULL=c(alphaNULL=4, betaNULL=4),
    		sumMethod="median", permMethod="all", verbose=TRUE)
    	bm1<-fitBM(bm1, para=list(zInit=NULL, thetaInit=c(alphaNeg=2, betaNeg=4,
    		alphaNULL=bm1@result$fitNULL$thetaNULL[["alphaNULL"]],
    		betaNULL=bm1@result$fitNULL$thetaNULL[["betaNULL"]],
    		alphaPos=4, betaPos=2), gamma=NULL),
    		ctrl=list(fitNULL=FALSE, tol=1e-1), verbose=TRUE, gradtol=1e-3)
    	view(bm1, "fitNULL")
    	view(bm1, "fitBM")
    	bm1

    ## End(Not run)

[Package PANR version 1.26.0 Index]