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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