remove_variables: Remove variables based on expression profiles across samples.

In okadalabipr/ASURAT: Functional annotation-driven unsupervised clustering for single-cell data

Remove variables based on expression profiles across samples.

Description

This function removes low expressed variable data.

Usage

remove_variables(sce = NULL, min_nsamples = 0)

Arguments

sce	A SingleCellExperiment object.
min_nsamples	An integer. This function removes variables for which the numbers of non-zero expressing samples are less than this value.

Value

A SingleCellExperiment object.

Examples

data(pbmc_eg)
pbmc <- add_metadata(sce = pbmc_eg, mitochondria_symbol = "^MT-")
pbmc <- remove_variables(sce = pbmc, min_nsamples = 10)

okadalabipr/ASURAT documentation built on Nov. 25, 2022, 5:40 p.m.