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
- data
An expression matrix with genes in the rows, samples in the columns
- k
Number of neighbors to be used in the
imputation (default=10)
- rowmax
The 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.
- colmax
The 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.
- maxp
The 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.seed
The seed used for the random number generator (default
362436069) for reproducibility.
|
Value
MultiAssayExperiment with imputed assays values
Examples
library(curatedTCGAData)
gbm <- curatedTCGAData("GBM", "RPPA*", FALSE)
## replace DataFrame with "matrix"
gbm[[1L]] <- as.matrix(assay(gbm[[1L]]))
gbm <- imputeAssay(gbm, i = 1L)
[Package
TCGAutils version 1.2.2
Index]