minfi (version 1.18.2)

MethylSet-class: MethylSet instances

Description

This class holds preprocessed data for Illumina methylation microarrays.

Usage

## Constructor
MethylSet(Meth, Unmeth, phenoData, annotation = NULL)
## Data extraction / Accessors
## S3 method for class 'MethylSet':
getMeth(object)
## S3 method for class 'MethylSet':
getUnmeth(object)
## S3 method for class 'MethylSet':
getBeta(object, type = "", offset = 0, betaThreshold = 0)
## S3 method for class 'MethylSet':
getM(object, type = "", \dots)
## S3 method for class 'MethylSet':
getCN(object, \dots)
## S3 method for class 'MethylSet':
getManifest(object)
## S3 method for class 'MethylSet':
preprocessMethod(object)
## Utilities
dropMethylationLoci(object, dropRS = TRUE, dropCH = TRUE)

Arguments

object

A MethylSet.

Meth

A matrix of methylation values (between zero and infinity) with each row being a methylation loci and each column a sample.

Unmeth

See the Meth argument.

phenoData

a phenoData object.

annotation

An annotation string, optional.

type

How are the values calculated? For getBeta setting type="Illumina" sets offset=100 as per Genome Studio. For getM setting type="" computes M-values as the logarithm of Meth/Unmeth, otherwise it is computed as the logit of getBeta(object).

offset

Offset in the beta ratio, see detail.

betaThreshold

Constrains the beta values to be in the inverval betwen betaThreshold and 1-betaThreshold.

dropRS

Should SNP probes be dropped?

dropCH

Should CH probes be dropped

...

For the constructor: additional objects passes to the eSet constructor, particular a phenoData slot. For getM these values gets passed onto getBeta.

Constructor

Instances are constructed using the MethylSet function with the arguments outlined above.

Details

This class inherits from eSet. Essentially the class is a representation of a Meth matrix and a Unmeth matrix linked to a pData data frame.

In addition, an annotation and a preprocessMethod slot is present. The annotation slot describes the type of array and also which annotation package to use. The preprocessMethod slot describes the kind of preprocessing that resulted in this dataset.

A MethylSet stores meth and Unmeth. From these it is easy to compute Beta values, defined as $$\beta = \frac{\textrm{Meth}}{\textrm{Meth} + \textrm{Unmeth} + \textrm{offset}}$$ The offset is chosen to avoid dividing with small values. Illumina uses a default of 100. M-values (an unfortunate bad name) are defined as $$M = \textrm{logit}(\beta) = \log(\textrm{Meth} / \textrm{Unmeth})$$ This formula has problems if either Meth or Unmeth is zero. For this reason, we can use betaThreshold to make sure Beta is neither 0 nor 1, before taken the logit. What makes sense for the offset and betaThreshold depends crucially on how the data was preprocessed. Do not expect the default values to be particular good.

See Also

eSet for the basic class structure. Objects of this class are typically created from an RGChannelSet using preprocessRaw or another preprocessing function.

Examples

showClass("MethylSet")