Estimate the q-values for a given set of p-values
qvalue.RdEstimate the q-values for a given set of p-values. The q-value of a test measures the proportion of false positives incurred (called the false discovery rate) when that particular test is called significant.
Arguments
- p
A vector of p-values (only necessary input).
- fdr.level
A level at which to control the FDR. Must be in (0,1]. Optional; if this is selected, a vector of TRUE and FALSE is returned that specifies whether each q-value is less than fdr.level or not.
- pfdr
An indicator of whether it is desired to make the estimate more robust for small p-values and a direct finite sample estimate of pFDR -- optional.
- lfdr.out
If TRUE then local false discovery rates are returned. Default is TRUE.
- pi0
It is recommended to not input an estimate of pi0. Experienced users can use their own methodology to estimate the proportion of true nulls or set it equal to 1 for the BH procedure.
- ...
Details
The function pi0est is called internally and calculates
the estimate of \(\pi_0\),
the proportion of true null hypotheses. The function lfdr
is also called internally and
calculates the estimated local FDR values. Arguments for these
functions can be included via ... and
will be utilized in the internal calls made in qvalue.
See http://genomine.org/papers/Storey_FDR_2011.pdf
for a brief introduction to FDRs and q-values.
References
Storey JD. (2011) False discovery rates. In International
Encyclopedia of Statistical Science.
http://genomine.org/papers/Storey_FDR_2011.pdf
http://www.springer.com/statistics/book/978-3-642-04897-5