Description Usage Arguments Value Examples

Comprehensive DMR analysis based on bimodal normal distribution model and weighted cost function for regional methylation analysis optimization. It captures the regional methylation modification by taking the spatial distribution of CpGs into account for the enrichment DNA methylation sequencing data so as to optimize the definition of the empirical regions. Combined with the dependent adjustment for regional p-value combination.

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`myDiff` |
a |

`step` |
a numeric variable for calculating auto-correlation, default: 100. |

`dist` |
distance cutoff to call a gap for DMR, default: "none", which will be automatically determined by the bimodal normal distribution, default: 100. |

`DMC.qvalue` |
qvalue cutoff for DMC definition, default: 0.01 |

`DMC.methdiff` |
methylation difference cutoff for DMC definition, default: 25. |

`num.DMCs` |
cutoff of the number DMCs in each region to call DMR, default: 1. |

`num.CpGs` |
cutoff of the number of CpGs, default: 3. |

`DMR.methdiff` |
cutoff of the DMR mean methylation difference, default=20. |

`plot` |
plot the bimodal normal distribution fitting or not, default=FAlSE. |

`main` |
the title of the plot, if plot=TRUE. Default=FALSE. |

`mode` |
the mode of call DMRs. 1: using all CpGs together. 2: use unidirectional CpGs to call DMRs. default: 1. |

`ACF` |
p-value combination test with (TRUE, default) or without (FALSE) dependency adjustment. |

`fuzzypval` |
p-value cutoff for raw regions definition. |

`GRanges`

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