getPotentialDIMP {MethylIT} | R Documentation |

This function perform a selection of the cytosine sites carrying the potential methylation signal. The potential signals from controls and treatments are used as prior classification in further step of signal detection.

getPotentialDIMP(LR, nlms = NULL, div.col, dist.name = "Weibull2P", absolute = FALSE, alpha = 0.05, pval.col = NULL, tv.col = NULL, tv.cut = NULL, min.coverage = NULL, hdiv.col = NULL, hdiv.cut = NULL, pAdjustMethod = NULL)

`LR` |
An object from 'InfDiv' or "testDMP" class. These objects are
previously obtained with function |

`nlms` |
A list of distribution fitted models (output of 'fitNonlinearWeibullDist' function) or NULL. If NULL, then empirical cumulative distribution function is used to get the potential DMPs. |

`div.col` |
Column number for divergence variable is located in the meta-column. |

`dist.name` |
name of the distribution to fit: Weibull2P (default:
"Weibull2P"), Weibull three-parameters (Weibull3P), gamma with
three-parameter (Gamma3P), gamma with two-parameter (Gamma2P),
generalized gamma with three-parameter ("GGamma3P") or four-parameter
("GGamma4P"), the empirical cumulative distribution function (ECDF) or
"None". If |

`absolute` |
Logic (default, FALSE). Total variation (TV, the difference of methylation levels) is normally an output in the downstream MethylIT analysis. If 'absolute = TRUE', then TV is transformed into |TV|, which is an information divergence that can be fitted to Weibull or to Generalized Gamma distribution. So, if the nonlinear fit was performed for |TV|, then absolute must be set to TRUE. |

`alpha` |
A numerical value (usually alpha < 0.05) used to select cytosine sites k with information divergence (DIV_k) for which Weibull probability P[DIV_k > DIV(alpha)]. |

`pval.col` |
An integer denoting a column from each GRanges object from
LR where p-values are provided when |

`tv.col` |
Column number for the total variation to be used for filtering cytosine positions (if provided). |

`tv.cut` |
If tv.cut and tv.col are provided, then cytosine sites k with abs(TV_k) < tv.cut are removed before to perform the ROC analysis. |

`min.coverage` |
Cytosine sites with coverage less than min.coverage are discarded. Default: 0 |

`hdiv.col` |
Optional. A column number for the Hellinger distance to be used for filtering cytosine positions. Default is NULL. |

`hdiv.cut` |
If hdiv.cut and hdiv.col are provided, then cytosine sites k with hdiv < hdiv.cut are removed. |

`pAdjustMethod` |
method used to adjust the p-values from other
approaches like Fisher's exact test, which involve multiple comparisons
Default is NULL. Do not apply it when a probability distribution model
is used ( |

The potential signals are cytosine sites k with information divergence (DIV_k) values greater than the DIV(alpha = 0.05). The value of alpha can be specified. For example, potential signals with DIV_k > DIV(alpha = 0.01) can be selected. For each sample, cytosine sites are selected based on the corresponding nonlinear fitted distribution model that has been supplied.

A list of GRanges objects, each GRanges object carrying the selected cytosine sites and and the Weibull probability P[DIV_k > DIV(alpha)].

## Get a dataset of Hellinger divergency of methylation levels and their ## corresponding best nonlinear fit distribution models from the package data(HD, nlms) PS <- getPotentialDIMP(LR = HD, nlms = nlms, div.col = 9L, alpha = 0.05)

[Package *MethylIT* version 0.3.1 ]