methimputeBinomialHMM: methimputeBinomialHMM

In ataudt/methimpute: Imputation-guided re-construction of complete methylomes from WGBS data

Description

The methimputeBinomialHMM is a list() which contains various entries (see Value section). The main entry of this object is $data, which contains the methylation status calls and posterior values. See Details for a description of all columns.

Details

The $data entry in this object contains the following columns:

• context The sequence context of the cytosine.

• counts Counts for methylated and total number of reads at each position.

• distance The distance in base-pairs from the previous to the current cytosine.

• transitionContext Transition context in the form "previous-current".

• posteriorMax Maximum posterior value of the methylation status call, can be interpreted as the confidence in the call.

• posteriorMeth Posterior value of the "methylated" component.

• posteriorUnmeth Posterior value of the "unmethylated" component.

• status Methylation status.

• rc.meth.lvl Recalibrated methylation level, calculated as r$data$rc.meth.lvl = r$data$params$emissionParams$Unmethylated[data$context,] * r$data$posteriorUnmeth + r$params$emissionParams$Methylated[data$context,] * r$data$posteriorMeth, where r is the methimputeBinomialHMM object.

Value

A list() with the following entries:

convergenceInfo	A list() with information about the convergence of the model fitting procedure.
params	A list() with fitted and non-fitted model parameters.
params.initial	A list() with initial values for the model parameters.
data	A GRanges-class with cytosine positions and methylation status calls.
segments	The data entry where coordinates of consecutive cytosines with the same methylation status have been merged.

See Also

methimpute-objects

ataudt/methimpute documentation built on May 10, 2019, 2:07 p.m.