if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("SingleCellMultiModal")
library(MultiAssayExperiment) library(SingleCellMultiModal) library(SingleCellExperiment)
CITE-seq data are a combination of two data types extracted at the same time from the same cell. First data type is scRNA-seq data, while the second one consists of about a hundread of antibody-derived tags (ADT). In particular this dataset is provided by @stoeckius2017simultaneous.
The user can see the available dataset by using the default options
CITEseq(DataType="cord_blood", modes="*", dry.run=TRUE, version="1.0.0")
Or simply by setting dry.run = FALSE
it downloads the data and creates the
MultiAssayExperiment
object.
In this example, we will use one of the two available datasets scADT_Counts
:
mae <- CITEseq( DataType="cord_blood", modes="*", dry.run=FALSE, version="1.0.0" ) mae
Example with actual data:
experiments(mae)
Check row annotations:
rownames(mae)
Take a peek at the sampleMap
:
sampleMap(mae)
The scRNA-seq data are accessible with the name scRNAseq
, which returns a
matrix object.
head(experiments(mae)$scRNAseq)[, 1:4]
The scADT data are accessible with the name scADT
, which returns a
matrix object.
head(experiments(mae)$scADT)[, 1:4]
Because of already large use of some methodologies (such as
in the SingleCellExperiment vignette or CiteFuse Vignette where the
SingleCellExperiment
object is used for CITE-seq data,
we provide a function for the conversion of our CITE-seq MultiAssayExperiment
object into a SingleCellExperiment
object with scRNA-seq data as counts and
scADT data as altExp
s.
sce <- CITEseq(DataType="cord_blood", modes="*", dry.run=FALSE, version="1.0.0", DataClass="SingleCellExperiment") sce
sessionInfo()
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