betaRegression {BiSeq} | R Documentation

## A function to estimate and test a group factor within a beta regression

### Description

This function models the methylation level within a beta regression. The first independent variable in `formula` is tested to be unequal to zero.

### Usage

    betaRegression(formula, link, object, mc.cores, ...)

### Arguments

`formula` | Symbolic description of the model. For the first independent variable the P value (Wald test) and the effect on methylation is returned. For details see below.
`link` | A character specifying the link function in the mean model (mu). Currently, `"logit"`, `"probit"`, `"cloglog"`, `"log"`, `"loglog"` are supported.
`object` | A `BSrel` object.
`mc.cores` | Passed to `mclapply`.
`...` | Other parameters passed to the `betareg` function.

### Details

See `betareg` function for details.

`mclapply`

### Value

A `data.frame` containing the position, chromosome, P value, estimated methylation level in group 1 and group 2 and methylation difference of group 1 and group 2.

### Author(s)

Katja Hebestreit

### References

Hebestreit, K., Dugas, M., and Klein HU. Detection of significantly differentially methylated regions in targeted bisulfite sequencing Data. In preparation. Bioinformatics. 2013 Jul 1;29(13):1647-53.

See also reference list in the documentation of `betareg`.

### See Also

`betareg`

### Examples

    # load RRBS data, subset to save time, find CpG clusters and smooth methylation data:
    data(rrbs)
    rrbs.small <- rrbs[1:1000,]
    rrbs.clust.unlim <- clusterSites(object = rrbs.small,
                                     groups = colData(rrbs)$group,
                                     perc.samples = 4/5,
                                     min.sites = 20,
                                     max.dist = 100)

    ind.cov <- totalReads(rrbs.clust.unlim) > 0
    quant <- quantile(totalReads(rrbs.clust.unlim)[ind.cov], 0.9)
    rrbs.clust.lim <- limitCov(rrbs.clust.unlim, maxCov = quant)

    # with a small subset to save calculation time:
    rrbs.part <- rrbs.clust.lim[1:100,]

    predictedMeth <- predictMeth(object=rrbs.part)

    betaResults <- betaRegression(formula = ~group, link = "probit",
                                  object = predictedMeth, type="BR")

[Package BiSeq version 1.30.0 Index]