Quality Control

# QC -----

# RDS objects before QC are read into memory.

# Define technology.
sample.10v3.snRNAseq$technology <- "10X | v3 | snRNAseq"
sample.multiome$technology <- "10X | multiome | snRNAseq"

# Compute percentage of ribosomal RNA.
sample.multiome[["percent.rb"]] <- Seurat::PercentageFeatureSet(sample.multiome, pattern = "^RB-")
sample.10v3.snRNAseq[["percent.rb"]] <- Seurat::PercentageFeatureSet(sample.10v3.snRNAseq, pattern = "^RB-")

# Merge datasets.
sample <- merge(x = sample.10v3.snRNAseq,
                y = sample.multiome)

# First QC round.
umis <- sample$nCount_RNA >= 1000
genes <- sample$nFeature_RNA >= 500
mito <- c(sample[, sample$technology == "10X | v3 | scRNAseq"]$percent.mt <= 20, sample[, sample$technology != "10X | v3 | scRNAseq"]$percent.mt <= 5) 

mask <- umis & genes & mito

sample <- sample[, mask]

# Second QC round.
umis <- sample$nCount_RNA <= (mean(sample$nCount_RNA) + 3 * stats::sd(sample$nCount_RNA))
genes <- sample$nFeature_RNA <= (mean(sample$nFeature_RNA) + 3 * stats::sd(sample$nFeature_RNA))


mask <- umis & genes
sample <- sample[, mask]