wilc.stat {siggenes} | R Documentation

## SAM Analysis Using Wilcoxon Rank Statistics

### Description

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).

### Usage

       wilc.stat(data, cl, gene.names = NULL, R.fold = 1, use.dm = FALSE,
           R.unlog = TRUE, na.replace = TRUE, na.method = "mean",
           approx50 = TRUE, ties.method=c("min","random","max"),
           use.row = FALSE, rand = NA)

### Arguments

`data` | a matrix or a data frame. Each row of `data` 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. 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 unpaired case.
`use.dm` | if `TRUE`, the fold change is computed by 2 to the power of the difference between the mean log2 intensities of the two groups, i.e.\ 2 to the power of the numerator of the test statistic. If `FALSE`, the fold change is determined by computing 2 to the power of `data` (if `R.unlog = TRUE`) and then calculating the ratio of the mean intensity in the group coded by 1 to the mean intensity in the group coded by 0. The latter is the default, as this definition of the fold change is used in Tusher et al.\ (2001).
`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.) Ignored if `use.dm = TRUE`.
`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 details, see the help of `rank`. If `use.row = TRUE`, `ties.method = "max"` will be used. For the handling of Zeros, see Details.
`use.row` | if `TRUE`, `rowWilcoxon` is used to compute the Wilcoxon rank statistics.
`rand` | numeric value. If specified, i.e. not `NA`, the random number generator will be set into a reproducible state.

### Details

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`.

### Value

A list containing statistics required by `sam`.

### Author(s)

Holger Schwender, holger.schw@gmx.de

### References

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.

### See Also

`SAM-class`,`sam`, `wilc.ebam`

[Package siggenes version 1.64.0 Index]