seabi: Calculate a performance metric based on male-female...
In wateRmelon: Illumina 450 methylation array normalization and metrics

Description Usage Arguments Value Author(s) References Examples

Calculates an area under ROC curve - based metric for Illumina 450K data using a t-test for male-female difference as the predictor for X-chromosome location of probes. The metric is 1-area so that small values indicate good performance, to match our other, standard error based metrics gcose and dmrse. Note that this requires both male and female samples of known sex and can be slow to compute due to running a t-test on every probe.

1	seabi(bn, stop = 1, sex, X)

`bn`	a matrix of betas (default method) or an object containing betas i.e. a `MethyLumiSet` object (`methylumi` package), a `MethylSet` or `RGChannelSet` object (`minfi` package) or a `exprmethy450` object (`IMA` package).
`stop`	partial area under curve is calculated if stop value <1 is provided
`sex`	a factor giving the sex of each sample (column)
`X`	a logical vector of length equal to the number of probes, true for features mapped to X-chromosome

a value between 0 and 1. values close to zero indicate high data quality as judged by the ability to discriminate male from female X-chromosome DNA methylation.

leonard.schalkwyk@kcl.ac.uk

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

   library(methylumi)
   data(melon)
   sex  <- pData(melon)$sex
   X    <- melon@featureData@data$CHR=='X'
   seabi(betas(melon), sex=sex, X=X)

# methylumi method
   seabi(melon, sex=sex, X=X)