Create a data with missing values
These functions take an instance of class
"MSnSet" and sets randomly selected values to
NA.
makeNaData(object, nNA, pNA, exclude) makeNaData2(object, nRows, nNAs, exclude) whichNA(x)
object |
An instance of class |
nNA |
The absolute number of missing values to be assigned. |
pNA |
The proportion of missing values to be assignmed. |
exclude |
A |
nRows |
The number of rows for each set. |
nNAs |
The number of missing values for each set. |
x |
A |
makeNaData randomly selects a number nNA (or a
proportion pNA) of cells in the expression matrix to be set
to NA.
makeNaData2 will select length(nRows) sets of rows
from object, each with nRows[i] rows respectively.
The first set will be assigned nNAs[1] missing values, the
second nNAs[2], ... As opposed to makeNaData, this
permits to control the number of NAs per rows.
The whichNA can be used to extract the indices
of the missing values, as illustrated in the example.
An instance of class MSnSet, as object, but
with the appropriate number/proportion of missing values. The
returned object has an additional feature meta-data columns,
nNA
Laurent Gatto
## Example 1
library(pRolocdata)
data(dunkley2006)
sum(is.na(dunkley2006))
dunkleyNA <- makeNaData(dunkley2006, nNA = 150)
processingData(dunkleyNA)
sum(is.na(dunkleyNA))
table(fData(dunkleyNA)$nNA)
naIdx <- whichNA(dunkleyNA)
head(naIdx)
## Example 2
dunkleyNA <- makeNaData(dunkley2006, nNA = 150, exclude = 1:10)
processingData(dunkleyNA)
table(fData(dunkleyNA)$nNA[1:10])
table(fData(dunkleyNA)$nNA)
## Example 3
nr <- rep(10, 5)
na <- 1:5
x <- makeNaData2(dunkley2006[1:100, 1:5],
nRows = nr,
nNAs = na)
processingData(x)
(res <- table(fData(x)$nNA))
stopifnot(as.numeric(names(res)[-1]) == na)
stopifnot(res[-1] == nr)
## Example 3
nr2 <- c(5, 12, 11, 8)
na2 <- c(3, 8, 1, 4)
x2 <- makeNaData2(dunkley2006[1:100, 1:10],
nRows = nr2,
nNAs = na2)
processingData(x2)
(res2 <- table(fData(x2)$nNA))
stopifnot(as.numeric(names(res2)[-1]) == sort(na2))
stopifnot(res2[-1] == nr2[order(na2)])
## Example 5
nr3 <- c(5, 12, 11, 8)
na3 <- c(3, 8, 1, 3)
x3 <- makeNaData2(dunkley2006[1:100, 1:10],
nRows = nr3,
nNAs = na3)
processingData(x3)
(res3 <- table(fData(x3)$nNA))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.