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

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)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> library(aCGH)
Loading required package: cluster
Loading required package: survival
Loading required package: multtest
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

Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.


Attaching package: 'aCGH'

The following object is masked from 'package:stats':

    heatmap

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/aCGH/impute.HMM.Rd_%03d_medium.png", width=480, height=480)
> ### Name: impute.HMM
> ### Title: Imputing log2 ratios using HMM
> ### Aliases: impute.HMM
> ### Keywords: models
> 
> ### ** 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)
sample is  1 	Chromosomes: 1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  
sample is  2 	Chromosomes: 1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  
> log2.ratios.imputed(ex.acgh) <- impute.HMM(ex.acgh)
Processing sample  1 
Processing sample  2 
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>