An object of class ORdensity includes all potential differentially expressed genes given microarray data measured in two experimental conditions.
Matrix including microarray data measured under experimental condition 1.
matrix including microarray data measured under experimental condition 2.
Vector 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
Numeric value indicating the number of permutations. By default,
Logical value to indicate whether the scaling of the difference of quantiles should be done.
Numeric value used by the method to calculate the percentile (1-α)100 of all the elements of the matrix with the permuted samples. By default 0.05.
Numeric value, by default
fold=10. It controls the number of partitions.
Vector of numerics. It sets the quantiles to be considered. By default
probs = c(0.25, 0.5, 0.75).
Vector of numerics. It controls the weights given to the quantiles set in
weights = c(1/4, 1/2, 1/4).
Numeric value to set the number of nearest neighbours. By default
Numeric value to set the number of maximum clusters to consider. By default
List containing the potential DE genes and their characteristics.
Outlyingness index (See Martínez-Otzeta, J. M. et al. 2020; Irigoien, I., and Arenas, C. 2018).
Average number of false positive permuted cases in the neighbourhood (See Martínez-Otzeta, J. M. et al. 2020; Irigoien, I., and Arenas, C. 2018).
Average density of false positive permuted cases in the neighbourhood (See Martínez-Otzeta, J. M. et al. 2020; Irigoien, I., and Arenas, C. 2018).
Matrix holding internal computations. Non-developers should left this parameter as default.
Number of clusters for partitioning the data. It is advisable to let the object to automatically estimate the best partition.
Boolean indicating if log messages are going to be printed.
Boolean indicating if parallel process is used.
Integer indicating the number of processors to be used. If nprocs is 0 or negative, the number of processors detected in the machine is used.
Boolean indicating if the same seed is used for the pseudorandom number generation.
Integer used as seed by the pseudorandom number generator.
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# To create an instance of a class ORdensity given data from 2 experimental conditions simexpr_reduced <- simexpr[c(1:15,101:235),] x <- simexpr_reduced[, 3:32] y <- simexpr_reduced[, 33:62] EXC.1 <- as.matrix(x) EXC.2 <- as.matrix(y) myORdensity <- new("ORdensity", Exp_cond_1 = EXC.1, Exp_cond_2 = EXC.2, B = 20)
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