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Remove low variance features from a matrix

Source: R/utils.R
remove_var.Rd

This function removes the p lowest variance features from a matrix. The function expects features in rows and samples in columns (e.g. an expression matrix).

Usage

remove_var(x, ...)

# S3 method for class 'matrix'
remove_var(x, p)

# S3 method for class 'data.frame'
remove_var(x, p)

# S3 method for class 'SummarizedExperiment'
remove_var(x, p, assay = "counts")

# S3 method for class 'DelayedArray'
remove_var(x, p)

Arguments

x

matrix, numeric data.frame, or SummarizedExperiment object

p

proportion of low variance features to remove

assay

if SummarizedExperiment, what assay to use. Default = "counts"

Value

matrix with lowest variance features removed

Examples


# Remove 80% lowest variance features
removed <- remove_var(GSE161650_lc, p = 0.8)
#> Removing 80% lowest variance features...