HiCblockModel: The model.

In HiCblock: Systematic Analysis of Architectural Proteins and Functional Elements in Blocking Long-Range Contacts Between Loci

Description

The main function to compute the generalized linear model.

Usage

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

Arguments

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.

Value

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

Author(s)

Raphael Mourad

References

Submitted.

HiCblock documentation built on Aug. 20, 2019, 5:25 p.m.