Description Usage Arguments Details Value Author(s) References See Also Examples

This function models the methylation level within a beta regression. The
first independent variable in `formula`

is tested to be
unequal to zero.

1 | ```
betaRegression(formula, link, object, mc.cores, ...)
``` |

`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, |

`object` |
A |

`mc.cores` |
Passed to |

`...` |
Other parameters passed to the |

See `betareg`

function for details.

`mclapply`

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.

Katja Hebestreit

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`

.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
# 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")
``` |

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