the initial estimation of the gamma parameters returned by .initialGammaEstimation function
fix.k
the k parameter of the gamma function which is fixed during estimation
weighted
determine whether to down-weight the long tails of two component densities beyond their modes
maxIteration
maximum iterations allowed before converging
tol
the difference threshold used to determine convergence
plotMode
determine whether plot the histogram and density plot estimation
truncate
determine whether to truncate the tails beyond the modes during parameter estimation
verbose
determine whether plot intermediate messages during iterations
Details
The assumption of this function is that the M-value distribution is composed of the mixture of two shifted gamma distributions, which are defined as:
dgamma(x-s[1], shape=k[1], scale=theta[1]) and dgamma(s[2]-x, shape=k[2], scale=theta[2]). Here s represents the shift.
NOTE: the methylation status modeling algorithm was developed based on 27K methylation array. It has not been tested for 450K array. Considering 450K array covers both promoter and gene body, the two component Gamma mixture model assumption may not be valid any more.
Value
The return is a list with "gammaFit" class attribute, which includes the following items:
logLikelihood
the log-likelihood of the fitting model
k
parameter k of gamma distribution
theta
parameter theta of gamma distribution
shift
parameter shift of gamma distribution
proportion
the proportion of two components (gamma distributions)
mode
the mode positions of the gamma distributions
probability
the estimated methylation status posterior probability of each CpG site
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
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Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(lumi)
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from 'package:stats':
IQR, mad, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
rbind, rownames, sapply, setdiff, sort, table, tapply, union,
unique, unsplit
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Setting options('download.file.method.GEOquery'='auto')
Setting options('GEOquery.inmemory.gpl'=FALSE)
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/lumi/gammaFitEM.Rd_%03d_medium.png", width=480, height=480)
> ### Name: gammaFitEM
> ### Title: Estimate the methylation status by fitting a Gamma mixture model
> ### using EM algorithm
> ### Aliases: gammaFitEM
> ### Keywords: methods
>
> ### ** Examples
>
>
> data(example.lumiMethy)
> M <- exprs(example.lumiMethy)
> fittedGamma <- gammaFitEM(M[,1], initialFit=NULL, maxIteration=50, tol=0.0001, plotMode=TRUE, verbose=FALSE)
>
>
>
>
>
>
> dev.off()
null device
1
>