get1DCutoff: get1DCutoff

In greenelab/miQC: Flexible, probabilistic metrics for quality control of scRNA-seq data

get1DCutoff

Description

When the model is generated based only on mitochondrial percentage, e.g. run_model(sce, model_type = "one_dimensional"), there will be a discrete cutoff point at which to remove cells with at least that mitochondrial percentage. This function identifies this cutoff based on a given posterior probability threshold. This number can then be passed as a cutoff to other modalities.

Usage

get1DCutoff(
  sce,
  model = NULL,
  posterior_cutoff = 0.75,
  subsets_mito_percent = "subsets_mito_percent"
)

Arguments

sce	(SingleCellExperiment) Input data object.
model	(flexmix) Output of mixtureModel function, which should be explicitly called first to ensure stability of model parameters. Default = NULL.
posterior_cutoff	(numeric) The posterior probability of a cell being part of the compromised distribution, a number between 0 and 1. Any cells below the appointed cutoff will be marked to keep. Default = 0.75
subsets_mito_percent	(character) Column name in sce giving the percent of reads mapping to mitochondrial genes. This name is inherited from scater's addPerCellQC() function, provided the subset "mito" with names of all mitochondrial genes is passed in. See examples for details.

Value

Returns a single numeric value, the percent mitochondrial cutoff at which to filter cells.

Examples

library(scRNAseq)
library(scater)
sce <- ZeiselBrainData()
mt_genes <- grepl("^mt-",  rownames(sce))
feature_ctrls <- list(mito = rownames(sce)[mt_genes])
sce <- addPerCellQC(sce, subsets = feature_ctrls)
model <- mixtureModel(sce, model_type = "one_dimensional")
get1DCutoff(sce, model)

greenelab/miQC documentation built on Jan. 6, 2023, 12:16 a.m.