binomRegMethModelPred: A smoothed-EM algorithm to estimate covariate effects and...

In kaiqiong/SOMNiBUS: Smooth modeling of bisulfite sequencing

A smoothed-EM algorithm to estimate covariate effects and test regional association in Bisulfite Sequencing-derived methylation data

Description

This function returns the predicted methylation levels

Usage

binomRegMethModelPred(
  BEM.obj,
  newdata = NULL,
  type = "proportion",
  verbose = TRUE
)

Arguments

BEM.obj	an output from the function binomRegMethModel
newdata	the data set whose predictions are calculated; with columns 'Position', covariate names matching the BEM.obj
type	return the predicted methylation proportion or the predicted response (in logit or other binom.link scale)
verbose	logical indicates if the algorithm should provide progress report information. The default value is TRUE.

Value

This function returns the predicted methylation levels

Author(s)

Kaiqiong Zhao

Examples

#------------------------------------------------------------#
data(RAdat)
RAdat.f <- na.omit(RAdat[RAdat$Total_Counts != 0, ])
out <- binomRegMethModel(
  data=RAdat.f, n.k=rep(5, 3), p0=0.003307034, p1=0.9,
  epsilon=10^(-6), epsilon.lambda=10^(-3), maxStep=200,
  Quasi = FALSE, RanEff = FALSE
)
binomRegMethModelPred(out)

kaiqiong/SOMNiBUS documentation built on Feb. 24, 2023, 5:38 a.m.