genki {wateRmelon} | R Documentation

## SNP derived performance metrics for Illumina 450K DNA methylation arrays.

### Description

A very simple genotype calling by one-dimensional K-means clustering is performed on each SNP, and for those SNPs where there are three genotypes, the squared deviations are summed for each genotype (similar to a standard deviation for each of allele A homozygote, heterozygote and allele B homozygote). By default these are further divided by the square root of the number of samples to get a standard error-like statistic.

### Usage

    genki(bn, g = getsnp(rownames(bn)), se = TRUE)

### Arguments

`bn` | a matrix of beta values(default method), a `MethyLumiSet` object (`methylumi` package), a `MethylSet` or `RGChannelSet` object (`minfi` package) or a `exprmethy450` object (`IMA` package).
`g` | vector of SNP names
`se` | TRUE or FALSE specifies whether to calculate the standard error-like statistic

### Details

There are 65 well-behaved SNP genotyping probes included on the array. These each produce a distribution of betas with tight peaks for the three possible genotypes, which will be broadened by technical variation between samples. The spread of the peaks is thus usable as a performance metric.

### Value

a vector of 3 values for the dispersion of the three genotype peaks (AA, AB, BB : low, medium and high beta values)

### Note

Corrected `RGChannelSet` methods - 12/10/2015

### Author(s)

Leonard.Schalkwyk@kcl.ac.uk

### References

Pidsley R, Wong CCY, Volta M, Lunnon K, Mill J, Schalkwyk LC: A data-driven approach to preprocessing Illumina 450K methylation array data (submitted)

### Examples

      #MethyLumiSet method
         data(melon)
         genki(melon)

      #MethyLumiSet method after normalization
         melon.dasen <- dasen(melon)
         genki(melon.dasen)

[Package wateRmelon version 1.28.0 Index]