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#
# Author: JonathanRosenblatt
###############################################################################
pval2qval<- function(pValues, cutoff){
requireLibrary('fdrtool')
fdrtool <- get("fdrtool", envir=asNamespace("fdrtool"))
qvals<-fdrtool(
pValues,
statistic= 'pvalue',
plot=FALSE,verbose=FALSE)$qval
if (missing(cutoff)) {
return(list(qValues=qvals))
}
return(list(qValues=qvals, rejected= qvals<=cutoff ))
}
pval2locfdr<- function(pValues, cutoff){
requireLibrary('fdrtool')
fdrtool <- get("fdrtool", envir=asNamespace("fdrtool"))
locfdr<-fdrtool(
pValues,
statistic= 'pvalue',
plot=FALSE,verbose=FALSE)$lfdr
if (missing(cutoff)) {
return(list(locFDR=locfdr))
}
return(list(locFDR=locfdr, rejected= locfdr<=cutoff ))
}
mutoss.locfdr <- function() {
return(new(Class="MutossMethod",
label="Local FDR (fdr)",
callFunction="pval2locfdr",
output=c("locFDR", "rejected"),
info=
"<h2> Name: </h2> Local fdr.\n
<h3> Also known as: </h3> fdr, empirical posterior probability of the null. \n
<h3> Error Type: </h3> Motivated by Bayesian considerations. Does not guarantee control of frequentist error types like FWER or FDR.\n
<h3> Recommended Usage: </h3> Typically used when a massive amount of hypotheses is being tested as in microarray analyses.\n
<h3> Related procedures: </h3> See FDR methods for similar procedures for frequentist error control.\n
<h3> References: </h3> \n
<ul>
<li> Efron B., Tibshirani R., Storey J. D. and Tusher, V. (2001).<i> Empirical Bayes Analysis of a Microarray Experiment. </i>\n
Journal of the American Statistical Association 96(456):1151-1160. </li>
</ul>",
parameters=list(
pValues=list(type="numeric"),
cutoff=list(type="numeric", label="Local fdr cutoff for rejection", optional=TRUE))))
}
mutoss.qvalues <- function() {
return(new(Class="MutossMethod",
label="q Values (Fdr)",
callFunction="pval2qval",
output=c("qValues", "rejected"),
info=
"<h2> Name: </h2> q-Values.\n
<h3> Also known as: </h3> \n
<ul>
<li> Estimated pFDR</li>\n
<li> Estimated Positive FDR </li>\n
<li> Empirical tail-area posterior probability of the null</li> \n
<h3> Error Type: </h3> Motivated by Bayesian considerations. Guarantees FDR control only when masses of hypotheses are being tested.\n
<h3> Recommended Usage: </h3> Typically used when a massive amount of hypotheses is being tested as in microarray analyses.\n
<h3> Related procedures: </h3> See FDR methods for similar procedures with frequentist error control.\n
<h3> References: </h3> \n
<ul>
<li> Storey, J. D. (2003)<i>The Positive False Discovery Rate: A Bayesian Interpretation and the q-Value.</i>
The Annals of Statistics 31(6): 2013-2035. </li>
</ul>",
parameters=list(
pValues=list(type="numeric"),
cutoff=list(type="numeric", label="q-value (pFDR) cutoff for rejection", optional=TRUE))))
}
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