Description Usage Arguments Value Examples

Run bumphunter to obtain DMRs (parameters stolen straight from bumphunter)

1 2 3 | ```
runbumphunter(methyl.mat, treatment, covariates, pickCutoff = TRUE,
pickCutoffQ = 0.975, maxGap = 300, smooth = FALSE, B = 250,
nullMethod = "bootstrap", n.core = 20)
``` |

`methyl.mat` |
matrix of samples by methylation |

`covariates` |
matrix (samples in rows, covar in column) |

`pickCutoff` |
Should bumphunter attempt to pick a cutoff using the permutation distribution? |

`pickCutoffQ` |
The quantile used for picking the cutoff using the permutation distribution. |

`maxGap` |
If cluster is not provided this maximum location gap will be used to define cluster via the clusterMaker function. |

`smooth` |
A logical value. If TRUE the estimated profile will be smoothed with the smoother defined by smoothFunction |

`B` |
An integer denoting the number of resamples to use when computing
null distributions. This defaults to 0. If permutations is supplied that
defines the number of permutations/bootstraps and B is ignored. |

`nullMethod` |
Method used to generate null candidate regions, must be one of ‘bootstrap’ or ‘permutation’ (defaults to ‘permutation’). However, if covariates in addition to the outcome of interest are included in the design matrix (ncol(design)>2), the ‘permutation’ approach is not recommended. |

`n.core` |
number of cores to run in paralell |

annotated data frame; see bumphunter documentation for further explanation of output

1 | ```
DMS_annotated=annotateGenes(DMS)
``` |

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