## S3 method for class 'qvalue':
summary(object, cuts = c(1e-04, 0.001, 0.01, 0.025, 0.05,
0.1, 1), digits = getOption("digits"), ...)summary shows the original call, estimated proportion of
true null hypotheses, and a table comparing the number of significant calls
for the p-values, estimated q-values, and estimated local FDR values using a set of
cutoffs given by cuts.Storey JD and Tibshirani R. (2003) Statistical significance for
genome-wide experiments. Proceedings of the National Academy of Sciences,
100: 9440-9445.
Storey JD. (2003) The positive false discovery rate: A Bayesian
interpretation and the q-value. Annals of Statistics, 31: 2013-2035.
Storey JD, Taylor JE, and Siegmund D. (2004) Strong control,
conservative point estimation, and simultaneous conservative
consistency of false discovery rates: A unified approach. Journal of
the Royal Statistical Society, Series B, 66: 187-205.
Storey JD. (2011) False discovery rates. In International Encyclopedia of Statistical Science.
qvalue, plot.qvalue, write.qvalue# import data
data(hedenfalk)
p <- hedenfalk$p
# get summary results from q-value object
qobj <- qvalue(p)
summary(qobj, cuts=c(0.01, 0.05))Run the code above in your browser using DataLab