summary {siggenes}R Documentation

EBAM specific summary method


Summarizes an EBAM analysis for a given value of delta. Computes both general statistics such as the number of differentially expressed genes and the estimated FDR, and gene-specific statistics such as the expression scores and the local FDRs for the differentially expressed genes.


summary(object, delta = NULL, n.digits = 4, what = "both", entrez = FALSE, chip = "",
	file = "", sep = "\t", quote = FALSE, dec=".")


object a SAM object
delta a numeric value between 0 and 1 specifying the minimum posterior probability for a gene to be called differentially expressed
n.digits an integer specifying the number of decimal places in the output
what either "both", "stats" or "genes". If "stats" general information is shown. If "genes" gene-specific information is given. If "both" both general and gene-specific information is shown
entrez logical. If TRUE both the Entrez links and the symbols of the genes will be added to the output
chip character string naming the chip type used in this analysis. Only needed if entrez = TRUE. If the input of either find.a0 or ebam is an ExpressionSet object, chip needs not to be specified
file character string naming the file in which the information should be stored. By default the information is not stored, but shown in the R window
sep the field separator string used when output is stored in file
quote logical indicating if character strings and factors should be surrounded by double quotes. For details, see the help page of write.table
dec the string to use for decimal points


The output of summary is a sumEBAM object consisting of the following slots:
row.sig.genes a numeric vector specifying the rows of the data matrix containing the differentially expressed genes
mat.fdr a matrix containing general information as the estimated FDR and the number of differentially expressed genes
mat.sig a data frame containing gene-specific information on the differentially expressed genes
list.args a list containing the arguments of summary needed for internal use


Holger Schwender,


Efron, B., Tibshirani, R., Storey, J.D. and Tusher, V. (2001). Empirical Bayes Analysis of a Microarray Experiment, JASA, 96, 1151-1160.

Schwender, H., Krause, A. and Ickstadt, K. (2003). Comparison of the Empirical Bayes and the Significance Analysis of Microarrays. Technical Report, SFB 475, University of Dortmund, Germany.