champ.refbase {ChAMP} | R Documentation

## Applying References-Base Methold to beta valued methylation data.

### Description

Applying References-Based Methold to correct cell-proportion in a methylation dataset. Reference-based method use purified whole blood cell-type specific methylation value to correct beta value dataset. Cell Proportions for each cell-type will be detected, and lm function will be used to correct beta value for 5 largest cell types. Cell type with smallest cell proportion will not be corrected.

### Usage

        champ.refbase(beta=myNorm,
                      arraytype="450K")

### Arguments

`beta` | whole blood beta methylation dataset user want to correct. (default = myNorm)
`arraytype` | There are two types of purified cell-type specific references can be chosen, "450K" and "27K". By default, 450K value will be used, but user may choose 27K as well. (default = myNorm)

### Value

`CorrectedBea` | A beta valued matrix, with all value get corrected with RefBaseEWAS method. Be aware, champ.refbase will only correct top 5 cell types with largest mean cell proportions, and leave the cell with smallest mean cell proportion. User may check CellFraction result to find out which cell types are get corrected.
`CellFraction` | Proportion for each cell type.

### Author(s)

Houseman EA, Yuan Tian, Andrew Teschendorff

### References

Houseman EA, Accomando WP, Koestler DC, Christensen BC, Marsit CJ, et al. (2012) DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics 13: 86. doi: 10.1186/1471-2105-13-86. pmid:22568884

### Examples

        ## Not run:
            myLoad <- champ.load(directory=system.file("extdata",package="ChAMPdata"))
            myNorm <- champ.norm()
            myRefbase <- champ.refbase()

    ## End(Not run)

[Package ChAMP version 2.22.0 Index]