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#------------------------------------------------------------------------------#
# Storey Tibshirani method #
# This code is based on that provided by John Storey obtained from #
# http://genomics.princeton.edu/storeylab/qvalue/results.R #
#------------------------------------------------------------------------------#
# #
# Inputs : #
# #
# alphas : vector of levels at which the FDR is to be 'controlled' #
# #
# p_value : vector of p-values #
# #
# Outputs : #
# #
# logical matrix indicating rejected hypotheses for each level #
#------------------------------------------------------------------------------#
StoreyTibshirani <- function(alphas, p_value){
m <- length(p_value)
lam <- seq(0,0.95,0.01)
pi0_temp <- sapply(X = lam,
FUN = function(x,p){ mean(p>x)/(1-x)},
p = p_value)
pi0 <- smooth.spline(x = lam,
y = pi0_temp,
w = (1-lam),
df = 3)$y[length(lam)]
qvalue <- pi0*m*p_value/rank(p_value)
qvalue[m] <- min(qvalue[m],1)
i <- m-1
while(i >= 1) {
qvalue[i] <- min(qvalue[i],qvalue[i+1],1)
i <- i - 1
}
indicator.st <- sapply(X = alphas,
FUN = function(x,q){q <= x},
q = qvalue)
if(is.matrix(indicator.st)){
colnames(indicator.st) <- round(alphas,3)
} else {
indicator.st <- matrix(indicator.st,nrow=1)
colnames(indicator.st) <- round(alphas,3)
}
return(indicator.st)
}
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