fitNULL: Fit the NULL component of a three-beta mixture model for...
In PANR: Posterior association networks and functional modules inferred from rich phenotypes of gene perturbations

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

The function performs permutations to the input rich phenotyping screens, and subsequently fit a beta distribution to the densities.

1 2	fitNULL(object, nPerm=20, thetaNULL=c(alphaNULL=4, betaNULL=4), sumMethod="median", permMethod="keepRep", verbose=TRUE, ...)

`object`	an object of S4 class `BetaMixture`.
`nPerm`	a positive numeric or integer value specifying the number of permutations.
`thetaNULL`	a list of numeric values giving the initial values for estimating the two shape parameters (see `dbeta` for more details).
`sumMethod`	a character value specifying how to summarize estimated parameters from multiple permutations. The current version only supports 'median' and 'mean'.
`permMethod`	a character value of the method to permute, either 'keepRep' (keep the order of replicates) or 'all' (regardless of replicates).
`verbose`	a logical value to switch on (if `TRUE`) or off if `FALSE` detailed run-time message.
`...`	other arguments for function `fitdistr`.

This function is a step prior to the three-beta mixture model fitting to functional gene association scores. The fitted parameters are then used as a fixed parameters in the three-beta mixture model for further fitting to the real screens. The NULL fitting is performed using the function fitdistr, so other arguments for the function fitdistr are also allowed by the argument ....

This function will return an updated object of class BetaMixture.

Xin Wang xw264@cam.ac.uk

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.

fitBM

data(Bakal2007)
bm1<-new("BetaMixture", pheno=Bakal2007, model="global", order=1)
bm1<-fitNULL(bm1, nPerm=10, thetaNULL=c(alphaNULL=4, betaNULL=4),
sumMethod="median", permMethod="all", verbose=TRUE)