| TailRankTest-class | R Documentation |
This is the class representation for the results of a tail-rank test to find biomarkers in a microarray data set. It includes methods for summarizing and plotting the results of the test.
Although objects can be created, as usual, using new, the only
reliable way to create valid objects is to use the
TailRankTest function. See the description of that
function for details on how the tail-rank test works.
statistic:a numeric vector containng the tail-rank statistic for each row (gene) in a microarray data set
direction:a character string representing the direction of the test; can be "up", "down", or "two-sided"
N1:an integer; the numnber of samples in the "base" or "healthy" group
N2:an integer; the number of samples in the "test" or "cancer" group
specificity:a real number between 0 and 1; the desired specificity used in the test to estimate a quantile from the "base" group
tolerance:a real number between 0 and 1; the upper tolerance bound used to estimate the threshold
confidence:a real number between 0 and 1; the confidence level that there are no false positives
cutoff:an integer; the maximum expected value of the statistic under the null hypothesis
model:a character string describing the model (binomial or beta-binomial) used to decide on cutoffs for significance
tau:a numeric vector or NULL; gene-by-gene upper bounds for significance
rho:a numeric vector or NULL; gene-by-gene lower bounds for significance
Display a summary of the TailRankTest object
Plot a histogram of the statistic in
the TailRankTest object x. The optional argument
overlay is a logical flag. If overlay=TRUE, then the
histogram is overlain with a curve representing the null
distribution. The default value of overlay is FALSE.
Convert the TailRankTest object
x into a logical vector, which takes on a TRUE value
whenever the tail-rank statistic exceeds the significance cutoff.
Obtain the vector of tail-rank
statistics contained in object.
Kevin R. Coombes <krc@silicovore.com>
TailRankTest,
tailRankPower,
biomarkerPowerTable,
matrixMean,
toleranceBound
# generate some fake data to use in the example
nr <- 40000
nc <- 110
fake.data <- matrix(rnorm(nr*nc), ncol=nc)
fake.class <- rep(c(TRUE, FALSE), c(40, 70))
# perform the tail-rank test
null.tr <- TailRankTest(fake.data, fake.class)
# get a summary of the results
summary(null.tr)
# plot a histogram of the statistics
hist(null.tr, overlay=TRUE)
# get the actual statistics
stats <- getStatistic(null.tr)
# get a vector that selects the "positive" calls for the test
is.marker <- as.logical(null.tr)
# the following line should evaluate to the number of rows, nr = 40000
sum( is.marker == (stats > null.tr@cutoff) )
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