SNR2p: Translate p-values to Signal-to-Noise Ratios

In PANR: Posterior association networks and functional modules inferred from rich phenotypes of gene perturbations

Description

The function translate Signal-to-Noise Ratios to p-values based on the fitted mixture model.

Usage

SNR2p(object, SNR, ...)

Arguments

object	an object of S4 class BetaMixture.
SNR	a numeric or integer specifying the SNR to translate
...	not in use, only for further extension.

Value

The function will return a data frame including SNRs, lower and upper quantiles and corresponding p-values.

Author(s)

Xin Wang [e-mail]

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

SNR2p

Examples

## Not run: 
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)
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)
SNR2p(bm1, SNR=10)

## End(Not run)

PANR documentation built on Nov. 8, 2020, 8:15 p.m.