Choose the features to use when integrating multiple datasets. This function ranks features by the number of datasets they are deemed variable in, breaking ties by the median variable feature rank across datasets. It returns the top scoring features by this ranking.

SelectIntegrationFeatures(
  object.list,
  nfeatures = 2000,
  assay = NULL,
  verbose = TRUE,
  fvf.nfeatures = 2000,
  ...
)

Arguments

object.list

List of seurat objects

nfeatures

Number of features to return

assay

Name or vector of assay names (one for each object) from which to pull the variable features.

verbose

Print messages

fvf.nfeatures

nfeatures for FindVariableFeatures. Used if VariableFeatures have not been set for any object in object.list.

...

Additional parameters to FindVariableFeatures

Value

A vector of selected features

Details

If for any assay in the list, FindVariableFeatures hasn't been run, this method will try to run it using the fvf.nfeatures parameter and any additional ones specified through the ....

Examples

if (FALSE) { # to install the SeuratData package see https://github.com/satijalab/seurat-data library(SeuratData) data("panc8") # panc8 is a merged Seurat object containing 8 separate pancreas datasets # split the object by dataset and take the first 2 pancreas.list <- SplitObject(panc8, split.by = "tech")[1:2] # perform SCTransform normalization pancreas.list <- lapply(X = pancreas.list, FUN = SCTransform) # select integration features features <- SelectIntegrationFeatures(pancreas.list) }