| imputeAssay {TCGAutils} | R Documentation |
This function imputes assays values inside a
MultiAssayExperiment
Description
These function allow the user to enter a
MultiAssayExperiment and impute all the NA values inside assays.
Usage
imputeAssay(multiassayexperiment, i = 1, ...)
Arguments
multiassayexperiment |
A MultiAssayExperiment with genes in the
rows, samples in the columns
|
i |
A numeric, logical, or character vector indicating the
assays to perform imputation on (default 1L)
|
... |
Arguments passed on to impute::impute.knn
dataAn expression matrix with genes in the rows, samples in the columns
kNumber of neighbors to be used in the
imputation (default=10)
rowmaxThe maximum percent missing data allowed in any row
(default 50%). For any rows with more than rowmax% missing
are imputed using the overall mean per sample.
colmaxThe maximum percent missing data allowed in any column
(default 80%). If any column has more than colmax% missing data,
the program halts and reports an error.
maxpThe largest block of genes imputed using the knn
algorithm inside impute.knn (default
1500); larger blocks are divided by two-means clustering
(recursively) prior to imputation. If maxp=p, only knn
imputation is done.
rng.seedThe seed used for the random number generator (default
362436069) for reproducibility.
|
Value
MultiAssayExperiment with imputed assays values
Examples
example(getSubtypeMap)
## convert data to matrix and add as experiment
gbm <-
c(gbm, RPPA_matrix = data.matrix(assay(gbm[["GBM_RPPAArray-20160128"]])))
imputeAssay(gbm, i = "RPPA_matrix")
[Package
TCGAutils version 1.6.2
Index]