Qvalue package: I am getting back 1, 000 q values when I only want 1 q value.

Hi Tom,
From a quick scan of the docs, I think you are looking for qobj$pi0.
The vector qobj$qvalue seems to be the local false discovery rate for
each of your randomizations. Note that the manual implies that the p
values are those of multiple comparisons within a data set, not
randomizations of the data, so I'm not sure that your usage is valid
for the function..

Jim


On Fri, Jan 13, 2017 at 4:12 AM, Thomas Ryan <tombernardryan at gmail.com>
wrote:

Hi all, I'm wondering if someone could put me on the right path to using
the "qvalue" package correctly.

I have an original p value from an analysis, and I've done 1,000
randomisations of the data set. So I now have an original P value and

1,000

random p values. I want to work out the false discovery rate (FDR) (Q; as
described by Storey and Tibshriani in 2003) for my original p value,
defined as the number of expected false positives over the number of
significant results for my original P value.

So, for my original P value, I want one Q value, that has been calculated
as described above based on the 1,000 random p values.

I wrote this code:

pvals <- c(list_of_p_values_obtained_from_randomisations)
qobj <-qvalue(p=pvals)
r_output1 <- qobj$pvalue
r_output2 <- qobj$qvalue

r_output1 is the list of 1,000 p values that I put in, and r_output2 is

a q

value for each of those p values (i.e. so there are 1,000 q values).

The problem is I don't want there to be 1,000 Q values (i.e one for each
random p value). The Q value should be the false discovery rate (FDR)

(Q),

defined as the number of expected false positives over the number of
significant results. So I want one Q value for my original P value, and

to

calculate that one Q value using the 1,000 random P values I have

generated.

Could someone please tell me where I'm going wrong.

Thanks
Tom

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