Converting to/from SCE objects

Table of Contents

• SCE vs Seurat objects
• Converting from Seurat to SCE
• Converting from SCE to Seurat

This cheatsheet explains how you can convert single-cell experiment data in R between SingleCellExperiment (SCE) and Seurat formats.

SCE vs Seurat objects

When converting between Seurat and SCE objects, it's helpful to know how the different object types store and refer to similar information. The table below shows different aspects of single-cell objects and how to access the associated data, assuming the default names for each type of single-cell object. There are several differences between Seurat and SCE objects that are useful to be aware of when converting them. Importantly, the term "assay" refers to different things in SCE vs. Seurat objects:

• In an SCE object, an assay is a matrix of counts, with default names "counts" for raw counts and "logcounts" for normalized counts.
• In a Seurat object, an assay instead refers to an experiment. The default Seurat assay is called "RNA", and it is analogous to the "main experiment" in an SCE object, which is not given a particular name.
• The Seurat count matrices are stored within a given assay (experiment) and have default names of "counts" for raw counts and "data" for normalized counts.

In addition, by default, SCE reduced dimension names are capitalized (e.g., "PCA"), and Seurat reduced dimension names are in lower case (e.g., "pca").

Always bear in mind that your object(s) may be named differently from the defaults as described here!

Data aspect	SCE	Seurat v5
Raw counts matrix	counts(sce_object)	seurat_obj[["RNA"]]$counts
Normalized counts matrix	logcounts(sce_object)	seurat_obj[["RNA"]]$data
Reduced dimension: PCA matrix	reducedDim(sce_object, "PCA)	seurat_obj$pca@cell.embeddings
Reduced dimension: UMAP matrix	reducedDim(sce_object, "UMAP)	seurat_obj$umap@cell.embeddings
Cell-level metadata	colData(sce_object)	seurat_obj@meta.data
Feature (gene)-level metadata	rowData(sce_object)	seurat_obj[["RNA"]]@meta.data Note that Seurat v3 syntax is: seurat_obj[["RNA"]]@meta.features
Miscellaneous additional metadata	metadata(sce_object)	seurat_obj@misc

We provide some code examples below for these conversions below. For all code examples below, it is assumed that the SingleCellExperiment library has been loaded into your R environment:

library(SingleCellExperiment)

Converting from Seurat to SCE

The following example code assumes you have a Seurat object called seurat_obj.

# Convert Seurat object to SCE object
sce_object <- Seurat::as.SingleCellExperiment(seurat_obj)

By default, all assays (experiments) present in the Seurat object will be ported into the new SCE object. Recall, in Seurat, an assay refers to an experiment which may be associated with multiple count matrices. To only specify that certain assays are retained, you can optionally provide the argument assay with Seurat assay names to retain in the SCE object, for example:

# Convert Seurat object to SCE object, retaining only the 'RNA' experiment (assay)
sce_object <- Seurat::as.SingleCellExperiment(seurat_obj, assay = "RNA")

Specifying assay is mostly useful if there are alternative experiments, for example from CITE-Seq data, present in the Seurat object that you do not want to retain during SCE conversion.

Converting from SCE to Seurat

The following example code assumes you are starting with an SCE object called sce_object.

The function Seurat::as.Seurat() can be used to convert an SCE object into a Seurat object and takes the following arguments:

• The SCE object to convert
• Optional named arguments with the following defaults:
  • counts = "counts" specifies that the SCE object contains a "counts" assay of normalized counts that should be included during conversion.
    • If there is no "counts" assay in the SCE object, set this argument as counts = NULL or rename accordingly, e.g. counts = "whatever_assay_name_you_are_using".
  • data = "logcounts" specifies that the SCE object contains a "logcounts" assay of normalized counts that should be included during conversion.
    • If there is no "logcounts" assay in the SCE object, set this argument as data = NULL or rename accordingly, e.g. data = "whatever_assay_name_you_are_using".
  • assay = NULL specifies that, by default, all assays (experiments) will be converted. If there are multiple assays and you wish to only convert, for example, the "RNA" assay, set this argument as assay = "RNA".
  • project = "SingleCellExperiment" specifies that the Seurat object being created will have this associated project name. You can override this with any string of interest, e.g. project = "sample_XYZ".

# Convert SCE object to Seurat object, assuming both
#  `counts` and  `logcounts` assays are present
seurat_object <- Seurat::as.Seurat(sce_object)

# Convert SCE object to Seurat object, where the SCE object
#  contains a `counts` but not a `logcounts` assay
seurat_object <- Seurat::as.Seurat(sce_object, data = NULL)