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.
See ExpressionSet
for additional slot information.
John Storey, Jeffrey Leek, Andrew Bass
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