Nothing

```
# This file is part of BGmix, a fully Bayesian model for
# differential expression.
# Copyright 2007 Natalia Bochkina <[email protected]>
#
# BGmix is free software; you can redistribute it and/or modify it
# under the terms of the GNU General Public License, version 2, as
# published by the Free Software Foundation.
#
# BGmix is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
#=================================================
# Auxiliary functions
#=================================================
# -------------------------------------------
# input: pp- tail posterior probability
calcF0tail <- function(pp, A, h=0.02, p.cut=0.6, N=100000, pp0=SimulateFromNull(A, N), correct.zero = F, F0.only=T)
{
if(is.null(dim(pp))) pp = as.matrix(pp)
n = dim(pp)[1]
K = dim(pp)[2]
f0 = array(dim=c(n,K))
F0 = array(dim=c(n,K))
for(k in 1:K)
{
seq1 = (1:n)[pp[,k] > p.cut]
for(i in seq1)
{
if(! F0.only) f0[i,k] = mean(pp0 >= pp[i,k]-h/2 & pp0 <= pp[i,k]+h/2)/h
F0[i,k] = mean(pp0 < pp[i,k])
}
if(correct.zero & ! F0.only)
{
f0.summ = tapply(f0[,k], INDEX = pp[,k], mean)
pp.summ = tapply(pp[,k], INDEX = pp[,k], mean)
# plot(pp.summ, f0.summ)
seq01 = match(pp[pp[,k] < 0.05,k], pp.summ)
f0[pp < 0.05,k] = f0.summ[12 - seq01]
}
}
if(F0.only) return(F0) else return(list(f0=f0, F0=F0))
}
```

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