Description Usage Arguments Value

View source: R/Inference_merip.R

`Inference_merip`

is a function to infer methylation and differential methylation given merip datasets.

1 2 | ```
Inference_merip(SE_M, MODE = "Meth", DM_METHOD = "DESeq2", PCA = FALSE,
HDER = "Unknown", ROW_FILTER = 0, CQN = FALSE, GC_INDX = NULL)
``` |

`SE_M` |
A |

`MODE` |
Could be either "Meth" or "DM", the later will conduct differential methylation analysis with the design: |

`DM_METHOD` |
A character string indicating the statistical method used in differential methylation analysis, could be one in c("DESeq2","QNB"). |

`PCA` |
Wheather to save the PCA plot after rlog transformation, default is FALSE, the plot will not be generated when |

`HDER` |
What should be the header of the PCA plot, applied when |

`CQN` |
Wheather to normalize GC content dependency of methylation / differential methylation log2FC, default is FALSE. |

`GC_INDX` |
The GC content values for each features (rows) of the count matrix, it is required when CQN = TRUE. log2(Q) = intercept + I(Treated) + I(IP) + I(IP):I(Treated). The result is just the differences in conditioning effect, or the statistics for estimate before the term I(IP):I(Treated). We don't get this by contrast, because the information is already contained in coefficient estimate under the design above, and we don't need to linear combine (or a linear combination by t(c(0,0,0,1))) the estimates to get it. An additional column c("Perturbation") is necessary for this option, the Perturbation column has to include character "C" for control condition. |

A DESeq2 result object for DESeq2 analysis; for other analysis, it will generate a `data.frame`

object.

ZhenWei10/meripQC documentation built on April 18, 2018, 9:37 p.m.

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