find.a0 {siggenes} R Documentation

## Computation of the Fudge Factor

### Description

Provides the required information for obtaining the optimal choice of the fudge factor in the Empirical Bayes Analysis of Microarrays that uses the modified t statistics.

### Usage

```   find.a0(data,cl,B=100,balanced=FALSE,mat.samp=NULL,delta=0.9,alpha=(0:9)/10,
include.0=TRUE,p0=NA,plot.legend=TRUE,na.rm=FALSE,rand=TRUE)
```

### Arguments

 `data` the data set that should be analyzed. Every row of this data set must correspond to a gene, and each column to a biological sample. `cl` a vector containing the class labels of the samples. In the two class unpaired case, the label of a sample is either 0 (e.g., control group) or 1 (e.g., case group). In the two class paired case, the labels are the integers between 1 and n/2 (e.g., after treatment group) and between -1 and -n/2 (e.g., before treatment group), where n is the length of `cl` and k is paired with -k. For one group data, the label for each sample should be 1. `B` number of permutations used in the calculation of the null density. `balanced` if `TRUE`, only balanced permutations will be used. Default is `FALSE`. `mat.samp` a permutation matrix. If specified, this matrix will be used, even if `rand` and `B` are specified. `delta` a gene will be called differentially expressed, if its posterior probability of being differentially expressed is large than or equal to `delta`. `alpha` a vector of possible values for the fudge factor a0 in terms of quantiles of the standard deviations of the genes. `include.0` if `TRUE` (default), a0=0 will also be a possible choice for the fudge factor. `p0` the prior probability that a gene is differentially expressed. If not specified, it will automatically be computed. `plot.legend` if `TRUE` (default), a legend will be added to the plot of the expression scores vs. their logit-transformed posterior probability. `na.rm` if `FALSE` (default), the expression score of genes with one or more missing values will be set to `NA`. If `TRUE`, the missing values will be replaced by the genewise mean of the non-missing values. `rand` if specified, the random number generator will be put in a reproducible state.

### Value

a list of the numbers of genes called differentially expressed by the EBAM analysis for several choices of a0, and the plot of the expression scores vs. their corresponding logit-transformed posterior probability of being significant.

 `sig.a0` vector containing the number of differentially expressed genes for the specified set of values for a0. `a0` the optimal choice of the fudge factor using the criterion of Efron et al. (2001) that the a0 should be used which leads to the most differentially expressed genes.

### Note

The results of `find.a0` must be assigned to an object for the further analysis with `ebam`.

### Author(s)

Holger Schwender, holger.schw@gmx.de

### References

Efron, B., Tibshirani, R., Storey, J.D., and Tusher, V. (2001). Empirical Bayes Analysis of a Microarray Experiment, JASA, 96, 1151-1160.

Storey, J.D., and Tibshirani, R. (2003). Statistical significance for genome-wide experiments, Technical Report, Department of Statistics, Stanford University.

Schwender, H. (2003). Assessing the false discovery rate in a statistical analysis of gene expression data, Chapter 7, Diploma thesis, Department of Statistics, University of Dortmund, http://de.geocities.com/holgerschw/thesis.pdf.

`ebam` `ebam.wilc`

### Examples

```## Not run:
library(multtest)
# Load the data of Golub et al. (1999). data(golub) contains
# a 3051x38 gene expression matrix called golub, a vector of
# length called golub.cl that consists of the 38 class labels,
# and a matrix called golub.gnames whose third column contains
# the gene names.
data(golub)

# Now the optimal value for the fudge factor a0 is computed,
# where possible values of the a0 are 0 and the 0, 0.05 and
# 0.1 quantile of the standard deviations of the genes.
# Setting rand=123 makes the results reproducible.

find.out<-find.a0(golub,golub.cl,alpha=c(0,0.05,0.1),rand=123)
## End(Not run)```

[Package siggenes version 1.4.0 Index]