calculateThreshold {RUVcorr} | R Documentation |
calculateThreshold
returns the proportion of prioritised genes from a random selection
for supplied threshold. Furthermore, this function also fits a loess curve to the estimated points.
This allows the calculation of a threshold for priortisation of genes.
calculateThreshold( X, exclude, index.ref, set.size = length(index.ref), Weights = NULL, thresholds = seq(0.05, 1, 0.05), anno = NULL, Factor = NULL, cpus = 1, parallel = FALSE )
X |
A matrix of gene expression values. |
exclude |
A vector of indices of genes to exclude. |
index.ref |
A vector of indices of reference genes used for prioritisation. |
set.size |
An integer giving the size of the set of genes that are to be prioritised. |
Weights |
A object of class |
thresholds |
A vector of thresholds; values should be in the range [0,1]. |
anno |
A dataframe or a matrix containing the annotation of arrays in |
Factor |
A character string corresponding to a column name of |
cpus |
An integer giving the number of cores that are supposed to be used. |
parallel |
A logical value indicating whether parallel comuting should be used. |
The proportion of prioritized random genes is estimated by drawing 1000 random sets of genes and calculating how many would be prioritised at every given threshold. A gene is is prioritised if at least one correlation with a known reference gene is above the given threshold.
calculateThreshold
returns an object of class Threshold
.
An object of class Threshold
is a list
with the following components:
Prop.values
A vector of the proportion of prioritized genes.
Thresholds
A vector containing the values in threshold
.
loess.estimate
An object of class loess
.
Saskia Freytag
Y<-simulateGEdata(500, 500, 10, 2, 5, g=NULL, Sigma.eps=0.1, 250, 100, intercept=FALSE, check.input=FALSE) anno<-as.matrix(sample(1:4, dim(Y$Y)[1], replace=TRUE)) colnames(anno)<-"Factor" weights<-findWeights(Y$Y, anno, "Factor") calculateThreshold(Y$Y, exclude=seq(251,500,1), index.ref=seq_len(10), Weights=weights, anno=anno, Factor="Factor")