DE_Seurat: Function to perform differential expression analysis for all...
In FloWuenne/scFunctions: Functions for single cell data analysis

This function will take a precomputed Seurat object and perform differential expression analysis using one of the differential expression tests included in Seurat (default= wilcox). If you want to perform DE analysis using edgeR, please check the function DE_edgeR_Seurat()! All the results will be saved in a folder above the current folder location named DE_Seurat (../DE_Seurat). The output folder can easily be modified using the parameter 'output_dir'.

DE_Seurat(
  seurat_object,
  de_function = "wilcox",
  output_dir = "../DE_Seurat",
  grouping_var = "Genotype",
  de_groups = c("WT", "KO"),
  min_pct = 0.1,
  man.logfc.threshold = 0.25,
  clusters_to_exclude = c(),
  max_cells = Inf
)

`seurat_object`	The S4 Seurat object which contains filtered and normalized cells in the data slot.
`de_function`	The function that will be used to perform differential expression analysis. See ?FindMarkers in the Seurat package for all options.
`output_dir`	The relative directory that will be used to save results.
`de_groups`	The two group labels to use for differential expression, supplied as a vector.
`min_pct`	The minimum percentage of cells in either group to express a gene for it to be tested. (Changes Seurats FindMarker min.pct variable)
`man.logfc.threshold`	The minimum log-fold change a change has to have to be tested. (changes Seurats FindMarker logfc.threshold variable)
`clusters_to_exclude`	Define a vector of clusters for which you don't want to perform DE analysis.