aCGH (version 1.50.0)

impute.HMM: Imputing log2 ratios using HMM

Description

Imputing log2 ratios using the output of the HMM segmenttation

Usage

impute.HMM(aCGH.obj, chrominfo = human.chrom.info.Jul03, maxChrom = 23, use.BIC = TRUE)

Arguments

aCGH.obj
Object of class aCGH.
chrominfo
a chromosomal information associated with the mapping of the data
maxChrom
Highest chromosome to impute.
use.BIC
logical parameter; if true impute missing values based on the Hidden Markov Model selected using Bayesian Information Criterion impute missing data, otherwise use AIC.

Value

Computes and returns the imputed log2 ratio matrix of the aCGH object using the output of the Hidden Markov Model segmentation done by invoking find.hmm.states function.

Details

See details in aCGH discussion.

See Also

aCGH, find.hmm.states, impute.lowess.

Examples


datadir <- system.file(package = "aCGH")
datadir <- paste(datadir, "/examples", sep="")

clones.info <-
      read.table(file = file.path(datadir, "clones.info.ex.txt"),
                 header = TRUE, sep = "\t", quote="", comment.char="")
log2.ratios <-
      read.table(file = file.path(datadir, "log2.ratios.ex.txt"),
                 header = TRUE, sep = "\t", quote="", comment.char="")
ex.acgh <- create.aCGH(log2.ratios, clones.info)

## Imputing the log2 ratios 

hmm(ex.acgh) <- find.hmm.states(ex.acgh, aic = TRUE, delta = 1.5)
log2.ratios.imputed(ex.acgh) <- impute.HMM(ex.acgh)