ebam {siggenes}R Documentation

Empirical Bayes Analysis of Microarrays


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




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.

See Also

find.a0 ebam.wilc


## Not run: 
    # 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.
    # 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.
    # Now that we have find the optimal value of a0, an empirical Bayes
    # analysis can be performed.
    # For further analyses the row numbers of the differentially expressed
    # genes are obtained by
## End(Not run)

[Package siggenes version 1.4.0 Index]