dimar: dimar

In kreutz-lab/DIMAR: Data-driven selection of an imputation algorithm in R

dimar

Description

DIMAR: Data-driven selection of an imputation algorithm in R

Usage

dimar(mtx, pattern = NULL, methods = "fast", npat = NULL, group = "cluster")

Arguments

mtx	Data matrix or MaxQuant input file ('.txt')
pattern	Search pattern for specifying sample names read in as default data, if not specified the user will be asked
methods	List of imputation algorithms ['fast'] uses the nine most selected algorithms
npat	Number of patterns of MVs to be simulated and to test the algorithms on [5/10/20 depending on the size of the data]
group	vector of group indices for ttest (group==1 vs group==2) ['cluster'] as a default, clustering with 2 cluster is performed

Examples

mtx <- matrix(rnorm(1000), nrow=100)
mtx[sample(c(1:1000),100)] <- NA
Imp <- dimar(mtx)

filename <- "Test1.txt"
filepath <- system.file("extdata", filename, package = "DIMAR")
Imp <- dimar(mtx = filepath, pattern = 'Intensity', group = c('PKB','PKC'))

kreutz-lab/DIMAR documentation built on Aug. 19, 2024, 11:07 a.m.