ORdensity-class: S4 class for representing potential differentially expressed...
In ORdensity: Identification of Differentially Expressed Genes

An object of class ORdensity includes all potential differentially expressed genes given microarray data measured in two experimental conditions.

Exp_cond_1: Matrix including microarray data measured under experimental condition 1.
Exp_cond_2: matrix including microarray data measured under experimental condition 2.
labels: 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 Exp_cond_1.
B: Numeric value indicating the number of permutations. By default, B=100.
scale: Logical value to indicate whether the scaling of the difference of quantiles should be done.
alpha: 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.
fold: Numeric value, by default fold=10. It controls the number of partitions.
probs: Vector of numerics. It sets the quantiles to be considered. By default probs = c(0.25, 0.5, 0.75).
weights: Vector of numerics. It controls the weights given to the quantiles set in probs. By default weights = c(1/4, 1/2, 1/4).
numneighbours: Numeric value to set the number of nearest neighbours. By default numneighbours=10.
numclustoseek: Numeric value to set the number of maximum clusters to consider. By default numclustoseek=10.
out: List containing the potential DE genes and their characteristics.
OR: Outlyingness index (See Martínez-Otzeta, J. M. et al. 2020; Irigoien, I., and Arenas, C. 2018).
FP: Average number of false positive permuted cases in the neighbourhood (See Martínez-Otzeta, J. M. et al. 2020; Irigoien, I., and Arenas, C. 2018).
dFP: Average density of false positive permuted cases in the neighbourhood (See Martínez-Otzeta, J. M. et al. 2020; Irigoien, I., and Arenas, C. 2018).
char: Matrix holding internal computations. Non-developers should left this parameter as default.
bestKclustering: Number of clusters for partitioning the data. It is advisable to let the object to automatically estimate the best partition.
verbose: Boolean indicating if log messages are going to be printed.
parallel: Boolean indicating if parallel process is used.
nprocs: 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.
replicable: Boolean indicating if the same seed is used for the pseudorandom number generation.
seed: Integer used as seed by the pseudorandom number generator.

# 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)