EstimatePi0: Proportion of the variables under the null hypothesis

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

View source: R/EstimatePi0.R

Description

Estimate of the proportion of the variables under the null hypothesis using tail posterior probabilities

Usage

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EstimatePi0(tpp, pp0, plot = T)

Arguments

tpp

observed tail posterior probability

pp0

a vector of tail posterior probability under H0

plot

if True, estimated pi0 at different locations and the median estimate is plotted

Details

Use Storey (2002) approach to estimate pi0

Value

estimate of pi0 = proportion of non-differentially expressed genes

Author(s)

Natalia Bochkina

References

Bochkina N., Richardson S. (2007) Tail posterior probability for inference in pairwise and multiclass gene expression data. Biometrics (in press).

See Also

TailPP, FDRplotTailPP,histTailPP

Examples

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 data(ybar, ss)
 nreps <- c(8,8)

## Note this is a very short MCMC run!
## For good analysis need proper burn-in period.
 outdir <- BGmix(ybar, ss, nreps, jstar=-1, nburn=0, niter=100, nthin=1)

 params <- ccParams(outdir)  
 res <-  ccTrace(outdir)
  
 tpp.res <- TailPP(res, nreps, params, plots  = FALSE)
 pi0 <- EstimatePi0(tpp.res$tpp, tpp.res$pp0)

BGmix documentation built on May 2, 2018, 3:11 a.m.