Description Usage Arguments Details Value Author(s) See Also Examples
Missing copy number values are imputed by a constant value or pcf-estimates.
1 | imputeMissing(data, method, c = 0, pcf.est = NULL,...)
|
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 |
... |
other relevant parameters to be passed on to |
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.
A data frame of the same size and format as data
with all missing values imputed.
Gro Nilsen
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | #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")
|
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