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