Transforms the output of an analysis with limma into a SAM
or EBAM
object, such that a SAM or EBAM analysis, respectively,
can be performed using the test statistics provided by limma.
1 2 3 4  limma2sam(fit, coef, moderate = TRUE, sam.control = samControl())
limma2ebam(fit, coef, moderate = TRUE, delta = 0.9,
ebam.control = ebamControl())

fit 
an object of class 
coef 
column number or name corresponding to the coefficient or contrast of
interest. For details, see the argument 
moderate 
should the limma tstatistic be considered? If 
sam.control 
further arguments for the SAM analysis. See 
delta 
the minimum posterior probability for a gene to be called differentially
expressed (or more generally, for a variable to be called significant) in an EBAM
analysis. For details, see 
ebam.control 
further arguments for an EBAM analysis. See 
An object of class SAM
or EBAM
.
Holger Schwender, holger.schwender@udo.edu
Efron, B., Tibshirani, R., Storey, J.D. and Tusher, V. (2001). Empirical Bayes Analysis of a Microarray Experiment. JASA, 96, 11511160.
Smyth, G.K. (2004). Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments. Statistical Applications in Genetics and Molecular Biology, 3(1), Article 3.
Tusher, V.G., Tibshirani, R., and Chu, G. (2001). Significance Analysis of Microarrays Applied to the Ionizing Radiation Response. PNAS, 98, 51165121.
sam
, ebam
, SAMclass
, EBAMclass
,
samControl
, ebamControl
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