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Prepare SingleCellExperiment object for analysis

Source: R/CoreMethods.R
PrepareData.Rd

This function prepares the SingleCellExperiment object for analysis. The only required input is an object of class SingleCellExperiment with at least data in the logcounts slot.

Usage

PrepareData.SingleCellExperiment(object)

# S4 method for class 'SingleCellExperiment'
PrepareData(object)

Arguments

object

An object of SingleCellExperiment class.

Value

An object of SingleCellExperiment class.

Examples

# Import package
suppressPackageStartupMessages(library("SingleCellExperiment"))

# Create toy SCE data
batches <- c("b1", "b2")
set.seed(239)
batch <- sample(x = batches, size = nrow(iris), replace = TRUE)
sce <- SingleCellExperiment(assays = list(logcounts = t(iris[,1:4])),  
                            colData = DataFrame("Species" = iris$Species, 
                                               "Batch" = batch))
colnames(sce) <- paste0("samp", 1:ncol(sce))
sce <- PrepareData(sce)
#> Converting object of `matrix` class into `dgCMatrix`. Please note that Coralysis has been designed to work with sparse data, i.e. data with a high proportion of zero values! Dense data will likely increase run time and memory usage drastically!
#> 4/4 features remain after filtering features with only zero values.