FDRforTailPP {BGmix} | R Documentation |
Calculate the false discovery rate (FDR) for the tail posterior probability
FDRforTailPP(tpp, a1, a2 = NULL, n.rep1, n.rep2 = NULL, prec = 0.05, p.cut = 0.7, N = 10000, pp0=NULL, plot = T)
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 |
pi0 |
estimate of pi0 - proportion of non-differentially expressed genes |
FDR |
estimate of FDR for all (distinct) cutoffs > p.cut |
Natalia Bochkina
Bochkina N., Richardson S. (2007) Tail posterior probability for inference in pairwise and multiclass gene expression data. Biometrics.
TailPP
, FDRplotTailPP
,histTailPP
,EstimatePi0
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)