ebam {siggenes} | R Documentation |

Performs an Empirical Bayes Analysis of Microarrays for a specified value of the
fudge factor *a0*. Modified versions of the t statistics are used.

ebam(a0.out,a0=NA,p0=NA,delta=NA,local.bin=.1,gene.names=NULL,q.values=TRUE, R.fold=TRUE,R.unlog=TRUE,na.rm=FALSE,file.out=NA)

`a0.out` |
the object to which the output of a previous analysis with `find.a0`
was assigned. |

`a0` |
the fudge factor. If `NA` , the value suggested by `find.a0`
will be used. |

`p0` |
prior probability that a gene is differentially expressed. If not specified
(i.e. `NA` ), it will automatically be computed. |

`delta` |
a gene will be called differentially expressed, if its posterior
probability of being differentially expressed is larger than or equal to
`delta` . By default, the same `delta` is used as in `find.a0` . |

`local.bin` |
specifies the interval used in the estimation of the local FDR for the
expression score z. By default, this interval is [z-0.1,z+0.1]. |

`gene.names` |
a vector containing the names of the genes |

`q.values` |
if `TRUE` (default), the q-value for each gene will be computed. |

`R.fold` |
if `TRUE` (default), the fold change for each differentially
expressed gene will be computed. |

`R.unlog` |
if `TRUE` , the anti-log of `data` will be used in the computation of
the R.fold. This is recommend if `data` contains the log2 transformed gene
expression levels. |

`na.rm` |
if `FALSE` (default), the fold change of genes with at least one
missing value will be set to `NA` . If `TRUE` , missing values will be
replaced by the genewise mean. |

`file.out` |
if specified, general information like the number of significant genes and the estimated FDR and gene-specific information like the expression scores, the q-values, the R fold etc. of the differentially expressed genes are stored in this file. |

a plot of the expression scores against their posterior probability of being differentially expressed, and (optional) a file containing general information like the estimated FDR and the number of differentially expressed genes and gene-specific information about the differentially expressed genes like their names, their expression scores, q values and their fold changes.

`FDR` |
vector containing the estimated p0, the number of significant genes,
the number of falsely called genes and the estimated FDR. |

`ebam.out` |
table containing gene-specific information about the differentially expressed genes. |

`row.sig.genes` |
vector consisting of the row numbers that belong to the differentially expressed genes. |

`...` |
further objects containing additional information |

The number of false positives are computed by *p0* times the number of falsely
called genes.

Holger Schwender, holger.schw@gmx.de

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.

## 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) # 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) # Now that we have find the optimal value of a0, an empirical Bayes # analysis can be performed. ebam.out<-ebam(find.out,gene.names=golub.gnames[,3]) # For further analyses the row numbers of the differentially expressed # genes are obtained by ebam.out$row.sig.genes ## End(Not run)

[Package *siggenes* version 1.4.0 Index]