ORdensity: ORdensity

In jmartinezot/findDE: Differentially Expressed Genes Discovery using ORdensity Method

Description

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.

Object of class ORdensity includes all potential diffentially expressed genes given miroarray data measured in two experimental conditions.

Slots

positive

Matrix including microarray data measured under experimental condition 1.

negative

matrix including microarray data measured under experimental condition 2.

labels

Vector of characters identifying the genes, by default rownames(positive) is inherited. If NULL, the genes are named ‘Gene1’, ..., ‘Genen' according to the order given in positive.

B

Numeric value indicating the number of bootstrap iteration. By default, B=100.

scale

Logical value to indicate whether the scaling of the difference of quatiles should be done.

alpha

Numeric value to control the bootstrap threshold. 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).

K

Numeric value to set the number of nearest neighbours. By default K=10.

out

List containing the potential DE genes and their characteristics. ...

Author(s)

Jose Maria Martinez Otzeta [e-mail]

Jose Maria Martinez-Otzeta, Itziar Irigoien, Concepcion Arenas

References

Irigoien and Arenas (2018) Identification of differentially expressed genes by means of outlier detection. BMC Bioinformatics, 19:317

See Also

summary.ORdensity, preclusteredData, plot.ORdensity, silhouetteAnalysis, clusplotk, compute.ORdensity, findbestK, findDEgenes, ORdensity

Examples

# To create an instance of a class ORdensity given data from 2 experimental conditions
x <- simexpr[, 3:32]
y <- simexpr[, 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)

jmartinezot/findDE documentation built on May 24, 2019, 8:54 a.m.