getQualityScore: Computes a quality score for a CNV fit
In CNVassoc: Association Analysis of CNV Data and Imputed SNPs

Description Usage Arguments Details Value Note Examples

This function provides different types of measurements of uncertainty after CNV calling

getQualityScore(x, ...)
## Default S3 method:
getQualityScore(x, sds, w, type, iter = 10000, threshold = 0.1, ...)
## S3 method for class 'cnv'
getQualityScore(x, type = "class", iter = 10000, threshold = 0.1, ...)

`x`	and object of class `cnv` or means vector of intensity signal for each copy number status
`...`	further arguments passed to or from `getQualityScore` methods
`type`	the type of quality score measurement computed. Possible values are "class", "CNVtools" or "CANARY" (see Details)
`iter`	number of iterations when `type=''class''` or `type=''CANARY''` is specified
`threshold`	a value to compute the proportion of sample individuals with confidence score bigger than it (see Details)
`sds`	standard deviations vector of intensity signal for each copy number status
`w`	copy number status proportions vector

The quality scores measures how well the clusters are separated. If compares the locations of the means with the standard error for each pair of adjacent cluster. Obviously, except for probability of good classification (type="class"), the lower quality score the highest uncertainty. There are 3 possible types of quality score measurements: "class": probability of good classification), "CNVtools": the score defined in 'CNVtools' package) and "CANARY": proportions of sample individuals with confidence score bigger than threshold. The confidence score is defined as the ratio between the second biggest copy number call probability divided by the biggest one.

An object of class getQualityScore with a single number of quality score.

For cnv objects created directly from probabilities and not from fitting a univariate intensity signal, only "class" quality score type can be calculated.

data(dataMLPA)
CNV<-cnv(x = dataMLPA$Gene2, threshold.0 = 0.01, mix.method = "mixdist")
getQualityScore(CNV,type="class")
getQualityScore(CNV,type="CNVtools")
getQualityScore(CNV,type="CANARY")