Description Usage Arguments Value Author(s) References

View source: R/HiCblockModel.R

The main function to compute the generalized linear model.

1 2 | ```
HiCblockModel(hrpd, model, facBlock, regressionMode = "NB", scale = F, includeBias = T,
sampleSize = NULL, distInter = NULL)
``` |

`hrpd` |
Preprocessed data. It includes Hi-C interaction pairs that have been annotated with genomic feature information. To compute this object, you should use the function HiCglmiProcData. |

`model` |
A formula object (stats R package). See Section HiCglmi-package, for examples. If regressionMode="PoissonLasso", then the variable model should be set to NULL (i.e. model=NULL). |

`facBlock` |
A vector of character describing the genomic features. For instance, facModel="BEAF32". |

`regressionMode` |
If regressionMode="Poisson", a Poisson regression. If regressionMode="QP", a quasi Poisson regression. If regressionMode="NB", a negative binomial regression. If regressionMode="PoissonLasso", a Poisson lasso regression. |

`scale` |
If scale=TRUE, blocking variables are standardized. |

`includeBias` |
If includeBias=True, then GC, mappability and fragment length biases are included in the regression (default mode). If includeBias=False, biases are not included in the regression. You can used this option if you are using Hi-C matrix that had been previously corrected for biases (not recommended). |

`sampleSize` |
Optional. A numerical value for subsampling Hi-C data. |

`distInter` |
Optional. A vector of two numerical values to set a distance range for Hi-C analysis. |

If regressionMode is "Poisson", "QP" or "NB", then a summary(glm) object is returned.

Raphael Mourad

Submitted.

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