remove_samples: Remove samples based on expression profiles across variables.

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

Remove samples based on expression profiles across variables.

Description

This function removes sample data by setting minimum and maximum threshold values for the metadata.

Usage

remove_samples(
  sce = NULL,
  min_nReads = NULL,
  max_nReads = NULL,
  min_nGenes = NULL,
  max_nGenes = NULL,
  min_percMT = NULL,
  max_percMT = NULL
)

Arguments

sce	A SingleCellExperiment object.
min_nReads	A minimum threshold value of the number of reads.
max_nReads	A maximum threshold value of the number of reads.
min_nGenes	A minimum threshold value of the number of non-zero expressed genes.
max_nGenes	A maximum threshold value of the number of non-zero expressed genes.
min_percMT	A minimum threshold value of the percent of reads that map to mitochondrial genes.
max_percMT	A maximum threshold value of the percent of reads that map to mitochondrial genes.

Value

A SingleCellExperiment object.

Examples

data(pbmc_eg)
pbmc <- add_metadata(sce = pbmc_eg, mitochondria_symbol = "^MT-")
pbmc <- remove_samples(sce = pbmc, min_nReads = 0, max_nReads = 1e+10,
                       min_nGenes = 0, max_nGenes = 1e+10,
                       min_percMT = NULL, max_percMT = NULL)

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