| filterCells {miQC} | R Documentation |
Find those cells probabilistically determined to be compromised by the mixture model and remove them from the dataset.
filterCells(sce, model = NULL, posterior_cutoff = 0.75, verbose = TRUE)
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 |
verbose |
(boolean) Whether to report how many cells (columns) are being removed from the SingleCellExperiment object. Default = TRUE |
Returns a SingleCellExperiment object, the same as the input except with a new column in colData, prob_compromised, and all cells with greater than the set posterior probability removed from the dataset.
library(scRNAseq)
library(scater)
library(BiocParallel)
sce <- ZeiselBrainData()
mt_genes <- grepl("^mt-", rownames(sce))
feature_ctrls <- list(mito = rownames(sce)[mt_genes])
sce <- addPerCellQC(sce, subsets = feature_ctrls, BPPARAM = MulticoreParam())
model <- mixtureModel(sce)
sce <- filterCells(sce, model)