Usage
find.a0(data, cl, method = z.find, B = 100, delta = 0.9, quan.a0 = (0:5)/5, include.zero = TRUE, control = find.a0Control(), gene.names = dimnames(data)[[1]], rand = NA, ...)
Arguments
data
a matrix, data frame or an ExpressionSet object.
Each row of data (or exprs(data), respectively) must
correspond to a variable (e.g., a gene), and each column to a sample (i.e.\ an observation).
cl
a numeric vector of length ncol(data) containing the class
labels of the samples. In the two class paired case, cl can also
be a matrix with ncol(data) rows and 2 columns. If data is
an ExpressionSet object, cl can also be a character string naming
the column of pData(data) that contains the class labels of the samples.
In the one-class case, cl should be a vector of 1's.
In the two class unpaired case, cl should be a vector containing 0's
(specifying the samples of, e.g., the control group) and 1's (specifying,
e.g., the case group).
In the two class paired case, cl can be either a numeric vector or
a numeric matrix. If it is a vector, then cl has to consist of the
integers between -1 and $-n/2$ (e.g., before treatment group) and between
1 and $n/2$ (e.g., after treatment group), where $n$ is the length of
cl and $k$ is paired with $-k$, $k=1,\dots,n/2$. If cl
is a matrix, one column should contain -1's and 1's specifying, e.g., the before
and the after treatment samples, respectively, and the other column should
contain integer between 1 and $n/2$ specifying the $n/2$ pairs of
observations.
In the multiclass case and if method = cat.stat, cl should be a
vector containing integers between 1 and $g$, where $g$ is the number
of groups.
For examples of how cl can be specified, see the manual of siggenes.
method
the name of a function for computing the numerator and the denominator
of the test statistic of interest, and for specifying other objects required
for the identification of the fudge factor. The default function z.find
provides these objects for t- and F-statistics. It is, however, also possible
to employ an user-written function. For how to write such a function, see the
vignette of siggenes.
B
the number of permutations used in the estimation of the null distribution.
delta
a probability. All genes showing a posterior probability that is
larger than or equal to delta are called differentially expressed.
quan.a0
a numeric vector indicating over which quantiles of the
standard deviations of the genes the fudge factor $a0$ should be
optimized.
include.zero
should $a0 = 0$, i.e. the not-modified test statistic
also be a possible choice for the fudge factor?
control
further arguments for controlling the EBAM analysis with find.a0.
For these arguments, see find.a0Control. gene.names
a character vector of length nrow(data) containing the
names of the genes. By default, the row names of data are used.
rand
integer. If specified, i.e. not NA, the random number generator
will be set into a reproducible state.
...
further arguments for the function specified by fun. For
further arguments of fun = z.find, see z.find.