summary {siggenes} | R Documentation |
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, 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.
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.