ebam {siggenes}R Documentation

Empirical Bayes Analysis of Microarrays

Description

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

Usage

    ebam(a0.out,data,a0=NA,p0=NA,delta=NA,stable=TRUE,number.int=139,local.bin=.1,
    col.accession=NA,col.gene.name=NA,q.values=TRUE,R.fold=TRUE,R.dataset=data,na.rm=FALSE,
    file.out=NA)

Arguments

a0.out the object to which the output of a previous analysis with find.a0 was assigned.
data the data set that should be analyzed. Each column of this data set must correspond to a gene. It has to be the same data set that was used in find.a0.
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 large than or equal to delta. By default, the same delta is used as in find.a0.
stable if TRUE (default), p0 will be computed by the algorithm of Storey and Tibshirani (2003). If FALSE, the (unstable) estimate will be computed that ensures that the posterior probability of being differentially expressed is always nonnegative.
number.int the number of equally spaced intervals that is used in the logistic regression for the estimation of the ratio of the null density to the mixture density.
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].
col.accession the column of data containing the accession numbers of the genes. If specified, the accession numbers of the significant genes will be added to the output.
col.gene.name the column of data that contains the names of the genes. If specified, the names of the significant genes will be added to the output.
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.dataset the data set used in the computation of the fold change. This data set can be a transformed version of data.
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.

Value

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.
...

Note

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

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.

See Also

find.a0 ebam.wilc


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