impute.HMM
From aCGH v1.50.0
by Peter Dimitrov
Imputing log2 ratios using HMM
Imputing log2 ratios using the output of the HMM segmenttation
- Keywords
- models
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
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)
Community examples
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