wilc.stat {siggenes} | R Documentation |
Generates the required statistics for a Significance Analysis of Microarrays analysis using standardized Wilcoxon rank statistics.
Should not be called directly, but via sam(..., method = wilc.stat).
wilc.stat(data, cl, gene.names = NULL, R.fold = 1, R.unlog = TRUE, na.replace = TRUE, na.method = "mean", approx50 = TRUE, ties.method=c("min","random","max"), check.ties = FALSE, rand = NA)
data |
a matrix or a data frame. Each row of data must correspond to a gene,
and each column to a sample |
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. For details
on how cl should be specified, see ?sam |
gene.names |
a character vector of length nrow(data) containing the
names of the genes |
R.fold |
a numeric value. If the fold change of a gene is smaller than or
equal to R.fold , or larger than or equal to 1/R.fold ,respectively,
then this gene will be excluded from the SAM analysis. The expression score
d of excluded genes is set to NA . By default, R.fold
is set to 1 such that all genes are included in the SAM analysis. Setting
R.fold to 0 or a negative value will avoid the computation of the fold
change. The fold change is only computed in the two-class cases |
R.unlog |
if TRUE , the anti-log of data will be used in the computation of the
fold change. Otherwise, data is used. This transformation should be done
if data is log2-tranformed (in a SAM analysis, it is highly recommended
to use log2-transformed expression data) |
na.replace |
if TRUE , missing values will be removed by the genewise/rowwise
statistic specified by na.method . If a gene has less than 2 non-missing
values, this gene will be excluded from further analysis. If na.replace = FALSE ,
all genes with one or more missing values will be excluded from further analysis.
The expression score d of excluded genes is set to NA |
na.method |
a character string naming the statistic with which missing values
will be replaced if na.replace=TRUE . Must be either "mean" (default)
or median |
approx50 |
if TRUE , the null distribution will be approximated by
the standard normal distribution. Otherwise, the exact null distribution is
computed. This argument will automatically be set to FALSE if there
are less than 50 samples in each of the groups |
ties.method |
either "min" (default), "random" , or "max" . If
"random" , the ranks of ties are randomly assigned. If "min" or "max" ,
the ranks of ties are set to the minimum or maximum rank, respectively. For the handling
of Zeros, see Details |
check.ties |
if TRUE , a warning will be generated if there are ties or Zeros.
This warning contains information about how many genes have ties or Zeros. Otherwise,
this warning is not generated. Default is FALSE since checking for ties can
take some time |
rand |
numeric value. If specified, i.e. not NA , the random number generator
will be set into a reproducible state |
Standardized versions of the Wilcoxon rank statistics are computed. This means that W*=(W-mean(W))/sd(W) is used as expression score d, where W is the usual Wilcoxon rank sum statistic or Wilcoxon signed rank statistic, respectively.
In the computation of these statistics, the ranks of ties are by default set to the minimum rank. In the computation of the Wilcoxon signed rank statistic, zeros are randomly set either to a very small positive or negative value.
If there are less than 50 observations in each of the groups, the exact null distribution
will be used. If there are more than 50 observations in at least one group, the null
distribution will by default be approximated by the standard normal distribution. It is,
however, still possible to compute the exact null distribution by setting approx50
to FALSE
.
a list containing statistics required by sam
Holger Schwender, holger.schw@gmx.de
Schwender, H., Krause, A. and Ickstadt, K. (2003). Comparison of the Empirical Bayes and the Significance Analysis of Microarrays. Technical Report, SFB 475, University of Dortmund, Germany.
Tusher, V.G., Tibshirani, R., and Chu, G. (2001). Significance analysis of microarrays applied to the ionizing radiation response. PNAS, 98, 5116-5121.