| 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 large 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, 2^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. |
... |
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.
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