Find differently expressed genes

This function makes use of Seurat::FindAllMarkers() to compute the differently expressed genes across the groups of the grouping variable denoted in the argument across.

See details for more.

runDEA(
  object,
  across,
  method_de = NULL,
  verbose = NULL,
  base = 2,
  variable.features.n = 3000,
  ...
)

runDeAnalysis(...)

Arguments

object

A valid spata-object.

across

Character value or NULL. Specifies the grouping variable of interest.

Use getGroupingOptions() to obtain all variable names that group the barcode spots of your object in a certain manner.

method_de

Character value. Denotes the method to according to which the de-analysis is performed. Given to argument test.use of the Seurat::FindAllMarkers()-function. Run SPATA::dea_methods to obtain all valid input options.

...

Additional arguments given to Seurat::FindAllMarkers()

fc_name, base

Given to corresponding arguments of Seurat::FindAllMarkers().

Value

The input spata2 object containing the added or computed results.

Details

This function is a wrapper around the DEA pipeline from the Seurat package. It creates a temporary Seurat object via Seurat::CreateSeuratObject(), and Seurat::SCTransform(). Then, Seurat::FindAllMarkers() is run. The output data.frame is stored in the SPATA2 object which is returned at the end.

If across and/or method_de are vectors instead of single values runDEA() iterates over all combinations in a for-loop and stores the results in the respective slots. (e.g.: If across = 'seurat_clusters' and method_de = c('wilcox', 'bimod') the function computes the differently expressed genes across all groups found in the feature variable seurat_clusters according to method wilcox and stores the results in the respective slot. Then it does the same according to method bimod.)

The results are obtainable via getDeaResults(), getDeaResultsDf() and getDeaGenes().