impute.HMM: Imputing log2 ratios using HMM

In aCGH: Classes and functions for Array Comparative Genomic Hybridization data

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.

Details

See details in aCGH discussion.

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.

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)

aCGH documentation built on Nov. 8, 2020, 6:58 p.m.