deSet-class: The differential expression class (deSet)
In edge: Extraction of Differential Gene Expression

Description Slots Methods Note Author(s)

The deSet class extends the ExpressionSet class. While the ExpressionSet class contains information about the experiment, the deSet class contains both experimental information and additional information relevant for differential expression analysis, explained below in Slots.

null.model: formula: contains the adjustment variables in the experiment. The null model is used for comparison when fitting the full model.
full.model: formula: contains the adjustment variables and the biological variables of interest.
null.matrix: matrix: the null model as a matrix.
full.matrix: matrix: the full model as a matrix.
individual: factor: contains information on which sample is from which individual in the experiment.
qvalueObj: S3 object: containing qvalue object. See qvalue for additional details.

as(ExpressionSet, "deSet"): Coerce objects of ExpressionSet to deSet.
lrt(deSet, ...): Performs a generalized likelihood ratio test using the full and null models.
odp(deSet, ...): Performs the optimal discovery procedure, which is a new approach for optimally performing many hypothesis tests in a high-dimensional study.
kl_clust(deSet, ...): An implementation of mODP that assigns genes to modules based off of the Kullback-Leibler distance.
fit_models(deSet, ...): Fits a linear model to each gene by method of least squares.
apply_qvalue(deSet, ...): Applies qvalue function.
apply_snm(deSet, ...): Applies surpervised normalization of microarrays (snm) on gene expression data.
apply_sva(deSet, ...): Applies surrogate variable analysis (sva).
fullMatrix(deSet): Access and set full matrix.
nullMatrix(deSet): Access and set null matrix.
fullModel(deSet): Access and set full model.
nullModel(deSet): Access and set null model.
individual(deSet): Access and set individual slot.
qvalueObj(deSet): Access qvalue object. See qvalue.
validObject(deSet): Check validity of deSet object.