Description Slots Author(s) References See Also Examples
ORdensity is a package for the automated discovery of differentially expressed genes. It makes use of the ORdensity method and the associated FP and dFP values to detect the most likely true positives.
An object of class ORdensity includes all potential differentially expressed genes given microarray data measured in two experimental conditions.
Exp_cond_1Matrix including microarray data measured under experimental condition 1.
Exp_cond_2matrix including microarray data measured under experimental condition 2.
labelsVector of characters identifying the genes, by default
rownames(Exp_cond_1) is inherited. If NULL,
the genes are named ‘Gene1’, ..., ‘Genen' according to the order given in Exp_cond_1.
BNumeric value indicating the number of bootstrap iterations. By default, B=100.
scaleLogical value to indicate whether the scaling of the difference of quantiles should be done.
alphaNumeric value to control the bootstrap threshold. By default 0.05.
foldNumeric value, by default fold=10. It controls the number of partitions.
probsVector of numerics. It sets the quantiles to be considered. By default
probs = c(0.25, 0.5, 0.75).
weightsVector of numerics. It controls the weights given to the quantiles set in probs.
By default weights = c(1/4, 1/2, 1/4).
numneighboursNumeric value to set the number of nearest neighbours. By default numneighbours=10.
numclustoseekNumeric value to set the number of maximum clusters to consider. By default numclustoseek=10.
outList containing the potential DE genes and their characteristics.
Jose Maria Martinez Otzeta josemaria.martinezo@ehu.eus
Jose Maria Martinez-Otzeta, Itziar Irigoien, Concepcion Arenas
Irigoien and Arenas (2018) Identification of differentially expressed genes by means of outlier detection. BMC Bioinformatics, 19:317
summary.ORdensity, preclusteredData,
plot.ORdensity, silhouetteAnalysis,
findDEgenes, ORdensity
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