SelectIntegrationFeatures: Select integration features

In satijalab/seurat: Tools for Single Cell Genomics

Select integration features

Description

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.

Usage

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

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 ....

Value

A vector of selected features

Examples

## Not run: 
# 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)

## End(Not run)

satijalab/seurat documentation built on May 11, 2024, 4:04 a.m.