"highTtest"Value object returned by call to highTtest().
This object should not be created by users.
CK:Object of class matrix or NULL.
A matrix of logical values. The
rows correspond to features, ordered as
provided in input dataSet1. The columns correspond to
levels of significance. Matrix elements are TRUE if
feature was determined to be significant
by the Cao-Kosorok method.
The significance value associated with each column is
dictated by the input gammas.
pi1:Object of class numeric or NULL.
The estimated proportion of alternative hypotheses
calculated using the Cao-Kosorok method.
pvalue:Object of class numeric.
The vector of p-values calculated using the
two-sample t-statistic.
ST:Object of class matrix or NULL.
If requested, a matrix of logical values. The
rows correspond to features, ordered as
provided in input dataSet1. The columns correspond to
levels of significance. Matrix elements are TRUE if
feature was determined to be significant
by the Storey-Tibshirani (2003) method.
The significance value associated with each column is
dictated by the input gammas.
BH:Object of class matrix or NULL
If requested, A matrix of logical values. The
rows correspond to features, ordered as
provided in input dataSet1. The columns correspond to
levels of significance. Matrix elements are TRUE if
feature was determined to be significant
by the Benjamini-Hochberg (1995) method.
The significance value associated with each column is
dictated by the input gammas.
gammas:Object of class numeric.
Vector of significant values provided as
input for the calculation.
signature(x = "highTtest"):
Retrieves a matrix of logical values. The
rows correspond to features, the columns to levels
of significance. Matrix elements are TRUE if feature
was determined to be significant by the Benjamini-Hochberg
(1995) method.
signature(x = "highTtest"):
Retrieves a matrix of logical values. The
rows correspond to features, the columns to levels
of significance. Matrix elements are TRUE if feature
was determined to be significant by the Cao-Kosorok
(2011) method.
signature(x = "highTtest"): Retrieves the
estimated proportion of alternative hypotheses
obtained by the Cao-Kosorok (2011) method.
signature(x = "highTtest"): Generates a plot
of the number of significant features as a function of the
level of significance as calculated for each method (CK,BH, and/or
ST)
signature(x = "highTtest"): Retrieves the
vector of p-values calculated using the
two-sample t-statistic.
signature(x = "highTtest"):
Retrieves a matrix of logical values. The
rows correspond to features, the columns to levels
of significance. Matrix elements are TRUE if feature
was determined to be significant by the Storey-Tibshirani
(2003) method.
signature(x = "highTtest"): Generates
two- and three-dimensional Venn diagrams comparing the
features selected by each method. Implements methods of
package colorfulVennPlot. In addition to the highTtest
object, the level of significance, gamma, must
also be provided.
Cao, H. and Kosorok, M. R. (2011). Simultaneous critical values for t-tests in very high dimensions. Bernoulli, 17, 347--394. PMCID: PMC3092179.
Benjamini, Y. and Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B, 57, 289--300.
Storey, J. and Tibshirani, R. (2003). Statistical significance for genomewide studies. Proceedings of the National Academy of Sciences, USA, 100, 9440--9445.
# NOT RUN {
showClass("highTtest")
# }
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