FDRforTailPP {BGmix}R Documentation

FDR for tail posterior probability

Description

Calculate the false discovery rate (FDR) for the tail posterior probability

Usage

FDRforTailPP(tpp, a1, a2 = NULL, n.rep1, n.rep2 = NULL, prec = 0.05, p.cut = 0.7, N = 10000, pp0=NULL, plot = T)

Arguments

tpp vector of tail posterior probabilities
a1 posterior mean of the shape parameter of the inverse gamma distribution - prior for the variance in condition 1
a2 posterior mean of the shape parameter of the inverse gamma distribution - prior for the variance in condition 2
n.rep1 number of replicates in condition 1
n.rep2 number of replicates in condition 2
prec precision of the estimate of the cumulative distribution function of tail posterior probability under H0 (at points 1 - k*prec, k =1,2,..)
p.cut to save time, calculate FDR only for cutoffs on tail posterior probability > p.cut
N simulation size for tail posterior probability under H0
pp0 a vector of simulated tail posterior probabilities under H0
plot if True, the estimated pi0 at different locations and the median estimate is plotted

Value

pi0 estimate of pi0 - proportion of non-differentially expressed genes
FDR estimate of FDR for all (distinct) cutoffs > p.cut

Author(s)

Natalia Bochkina

References

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

See Also

TailPP, FDRplotTailPP,histTailPP,EstimatePi0

Examples


 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)
 FDR.res = FDRforTailPP(tpp.res$tpp, a1 = params$maa[1],
a2 = params$maa[2], n.rep1=nreps[1], n.rep2=nreps[2], p.cut = 0.8)


[Package BGmix version 1.2.0 Index]