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Last data update: 2014.03.03

R: Impute missing copy number values

imputeMissing

R Documentation

Impute missing copy number values

Description

Missing copy number values are imputed by a constant value or pcf-estimates.

Usage

imputeMissing(data, method, c = 0, pcf.est = NULL,...)

Arguments

`data`	a data frame with numeric or character chromosome numbers in the first column, numeric local probe positions in the second, and numeric copy number data for one or more samples in subsequent columns.
`method`	the imputation method to be used. Must be one of "constant" and "pcf".
`c`	a numerical value to be imputed if method is "constant". Default is 0.
`pcf.est`	a data frame of same size as `data`, with chromosome numbers and positions in the first two columns, and copy number estimates obtained from `pcf` in the subsequent columns. Only applicable if `method="pcf"`. If unspecified and `method="pcf"`, `pcf` is run internally to find estimates.
`...`	other relevant parameters to be passed on to `pcf`

Details

The available imputation methods are:

constant:: all missing values in data are replaced by the specified value c.
pcf:: the estimates from pcf-segmentation (see pcf) are used to impute missing values. If pcf has already been run, these estimates may be specified in pcf.est. If pcf.est is unspecified, pcf is run on the input data. In pcf the analysis is done on the observed values, and estimates for missing observations are set to be the estimate of the nearest observed probe.

Value

A data frame of the same size and format as data with all missing values imputed.

Author(s)

Gro Nilsen

Examples

#Load lymphoma data
data(lymphoma)
chrom <- lymphoma[,1]
pos <- lymphoma[,2]
#pick out data for the first six samples:
cn.data <- lymphoma[,3:8]

#Create missing values in cn.data at random positions:
n <- nrow(cn.data)*ncol(cn.data)
r <- matrix(rbinom(n=n,size=1,prob=0.95),nrow=nrow(cn.data),ncol=ncol(cn.data))
cn.data[r==0] <- NA    #matrix with approximately 5% missing values
mis.data <- data.frame(chrom,pos,cn.data)

#Impute missing values by constant, c=0:
imp.data <- imputeMissing(data=mis.data,method="constant")

#Impute missing values by obtained pcf-values:
pcf.est <- pcf(data=mis.data,return.est=TRUE)
imp.data <- imputeMissing(data=mis.data,method="pcf",pcf.est=pcf.est)

#Or run pcf within imputeMissing:
imp.data <- imputeMissing(data=mis.data,method="pcf")

Results


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)

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> library(copynumber)
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

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/copynumber/imputeMissing.Rd_%03d_medium.png", width=480, height=480)
> ### Name: imputeMissing
> ### Title: Impute missing copy number values
> ### Aliases: imputeMissing
> 
> ### ** Examples
> 
> #Load lymphoma data
> data(lymphoma)
> chrom <- lymphoma[,1]
> pos <- lymphoma[,2]
> #pick out data for the first six samples:
> cn.data <- lymphoma[,3:8]
> 
> #Create missing values in cn.data at random positions:
> n <- nrow(cn.data)*ncol(cn.data)
> r <- matrix(rbinom(n=n,size=1,prob=0.95),nrow=nrow(cn.data),ncol=ncol(cn.data))
> cn.data[r==0] <- NA    #matrix with approximately 5% missing values
> mis.data <- data.frame(chrom,pos,cn.data)
> 
> #Impute missing values by constant, c=0:
> imp.data <- imputeMissing(data=mis.data,method="constant")
> 
> #Impute missing values by obtained pcf-values:
> pcf.est <- pcf(data=mis.data,return.est=TRUE)
pcf finished for chromosome arm 1p 
pcf finished for chromosome arm 1q 
pcf finished for chromosome arm 2p 
pcf finished for chromosome arm 2q 
pcf finished for chromosome arm 3p 
pcf finished for chromosome arm 3q 
pcf finished for chromosome arm 4p 
pcf finished for chromosome arm 4q 
pcf finished for chromosome arm 5p 
pcf finished for chromosome arm 5q 
pcf finished for chromosome arm 6p 
pcf finished for chromosome arm 6q 
pcf finished for chromosome arm 7p 
pcf finished for chromosome arm 7q 
pcf finished for chromosome arm 8p 
pcf finished for chromosome arm 8q 
pcf finished for chromosome arm 9p 
pcf finished for chromosome arm 9q 
pcf finished for chromosome arm 10p 
pcf finished for chromosome arm 10q 
pcf finished for chromosome arm 11p 
pcf finished for chromosome arm 11q 
pcf finished for chromosome arm 12p 
pcf finished for chromosome arm 12q 
pcf finished for chromosome arm 13q 
pcf finished for chromosome arm 14q 
pcf finished for chromosome arm 15q 
pcf finished for chromosome arm 16p 
pcf finished for chromosome arm 16q 
pcf finished for chromosome arm 17p 
pcf finished for chromosome arm 17q 
pcf finished for chromosome arm 18p 
pcf finished for chromosome arm 18q 
pcf finished for chromosome arm 19p 
pcf finished for chromosome arm 19q 
pcf finished for chromosome arm 20p 
pcf finished for chromosome arm 20q 
pcf finished for chromosome arm 21q 
pcf finished for chromosome arm 22q 
pcf finished for chromosome arm 23p 
pcf finished for chromosome arm 23q 
> imp.data <- imputeMissing(data=mis.data,method="pcf",pcf.est=pcf.est)
> 
> #Or run pcf within imputeMissing:
> imp.data <- imputeMissing(data=mis.data,method="pcf")
pcf finished for chromosome arm 1p 
pcf finished for chromosome arm 1q 
pcf finished for chromosome arm 2p 
pcf finished for chromosome arm 2q 
pcf finished for chromosome arm 3p 
pcf finished for chromosome arm 3q 
pcf finished for chromosome arm 4p 
pcf finished for chromosome arm 4q 
pcf finished for chromosome arm 5p 
pcf finished for chromosome arm 5q 
pcf finished for chromosome arm 6p 
pcf finished for chromosome arm 6q 
pcf finished for chromosome arm 7p 
pcf finished for chromosome arm 7q 
pcf finished for chromosome arm 8p 
pcf finished for chromosome arm 8q 
pcf finished for chromosome arm 9p 
pcf finished for chromosome arm 9q 
pcf finished for chromosome arm 10p 
pcf finished for chromosome arm 10q 
pcf finished for chromosome arm 11p 
pcf finished for chromosome arm 11q 
pcf finished for chromosome arm 12p 
pcf finished for chromosome arm 12q 
pcf finished for chromosome arm 13q 
pcf finished for chromosome arm 14q 
pcf finished for chromosome arm 15q 
pcf finished for chromosome arm 16p 
pcf finished for chromosome arm 16q 
pcf finished for chromosome arm 17p 
pcf finished for chromosome arm 17q 
pcf finished for chromosome arm 18p 
pcf finished for chromosome arm 18q 
pcf finished for chromosome arm 19p 
pcf finished for chromosome arm 19q 
pcf finished for chromosome arm 20p 
pcf finished for chromosome arm 20q 
pcf finished for chromosome arm 21q 
pcf finished for chromosome arm 22q 
pcf finished for chromosome arm 23p 
pcf finished for chromosome arm 23q 
> 
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> 
> 
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> 
> dev.off()
null device 
          1 
>