--- title: "CITEseq Cord Blood" author: "Dario Righelli" date: "`r format(Sys.time(), '%d %B, %Y')`" output: BiocStyle::html_document: toc_float: true vignette: > %\VignetteIndexEntry{CITEseq Cord Blood} %\VignetteEncoding{UTF-8} %\VignetteEngine{knitr::rmarkdown} Package: SingleCellMultiModal bibliography: ../inst/REFERENCES.bib editor_options: chunk_output_type: console --- # Installation ```{r,eval=FALSE} if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("SingleCellMultiModal") ``` # Load libraries ```{r, include=TRUE, results="hide", message=FALSE, warning=FALSE} library(MultiAssayExperiment) library(SingleCellMultiModal) ``` # CITE-seq dataset 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. ## Downloading datasets The user can see the available dataset by using the default options ```{r} 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`: ```{r,message=FALSE} mse <- CITEseq( DataType="cord_blood", modes="*", dry.run=FALSE, version="1.0.0" ) mse ``` Example with actual data: ```{r} experiments(mse) ``` ## Exploring the data structure Check row annotations: ```{r} rownames(mse) ``` Take a peek at the `sampleMap`: ```{r} sampleMap(mse) ``` ## scRNA-seq data The scRNA-seq data are accessible with the name `scRNAseq`, which returns a *matrix* object. ```{r} head(experiments(mse)$scRNAseq)[, 1:4] ``` ## scADT data The scADT data are accessible with the name `scADT`, which returns a **matrix** object. ```{r} head(experiments(mse)$scADT)[, 1:4] ``` # SingleCellExperiment object conversion Because of already large use of some methodologies (such as in the [SingleCellExperiment vignette][1] or [CiteFuse Vignette][2] 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. [1]: https://www.bioconductor.org/packages/release/bioc/vignettes/SingleCellExperiment/inst/doc/intro.html#5_adding_alternative_feature_sets [2]: http://www.bioconductor.org/packages/release/bioc/vignettes/CiteFuse/inst/doc/CiteFuse.html ```{r message=FALSE} sce <- CITEseq(DataType="cord_blood", modes="*", dry.run=FALSE, version="1.0.0", DataClass="SingleCellExperiment") sce ``` # Session Info ```{r, tidy=TRUE} sessionInfo() ``` # References