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

In waldronlab/TCGAmisc: TCGA utility functions for data management

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

A 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")

waldronlab/TCGAmisc documentation built on Nov. 4, 2024, 7:51 a.m.