imputeAssay: This function imputes assays values inside a...

Description Usage Arguments Value Examples

View source: R/imputeAssay.R

Description

These function allow the user to enter a MultiAssayExperiment and impute all the NA values inside assays.

Usage

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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

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library(curatedTCGAData)

gbm <- curatedTCGAData("GBM", "RPPA*", FALSE)

## replace DataFrame with "matrix"
gbm[[1L]] <- as.matrix(assay(gbm[[1L]]))

gbm <- imputeAssay(gbm, i = 1L)

waldronlab/BiocInterfaces documentation built on Oct. 10, 2018, 9:26 p.m.