Seurat Analysis

## [1] "Read in data, generate inital Seurat object"

counts <- read.delim(params$counts, row.names = 1)
seuset <- Seurat::CreateSeuratObject(counts = counts, min.cells = min_cells, min.features = min_genes)

## [1] "Filter and normalize for UMI counts"

seuset <- subset(seuset, subset = `nCount_RNA` > low_thresholds & `nCount_RNA` < high_thresholds)
seuset <- Seurat::NormalizeData(seuset, normalization.method = "LogNormalize", scale.factor = 10000)

## [1] "Variable Genes"

seuset <- Seurat::FindVariableFeatures(object = seuset, selection.method = "mvp")
Seurat::VariableFeaturePlot(seuset, cols = c("black", "red"), selection.method = "disp")

seuset <- Seurat::ScaleData(object = seuset, vars.to.regress = "nCount_RNA")

## Regressing out nCount_RNA

## Centering and scaling data matrix