# Introduction to cellxgenedp The cellxgene data portal <https://cellxgene.cziscience.com/> provides a graphical user interface to collections of single-cell sequence data processed in standard ways to 'count matrix' summaries. The cellxgenedp package provides an alternative, R-based inteface, allowind data discovery, viewing, and downloading. ## Installation This package is available in *Bioconductor* version 3.15 and later. The following code installs [cellxgenedp](https://bioconductor.org/packages/cellxgenedp) ``` r if (!"BiocManager" %in% rownames(installed.packages())) install.packages("BiocManager", repos = "https://CRAN.R-project.org") BiocManager::install("cellxgenedp") ``` Alternatively, install the 'development' version from GitHub ``` r if (!"remotes" %in% rownames(installed.packages())) install.packages("remotes", repos = "https://CRAN.R-project.org") remotes::install_github("mtmorgan/cellxgenedp") ``` To also install additional packages required for this vignette, use ``` r pkgs <- c("tidyr", "zellkonverter", "SingleCellExperiment", "HDF5Array") required_pkgs <- pkgs[!pkgs %in% rownames(installed.packages())] BiocManager::install(required_pkgs) ``` ## Use Load the package into your current *R* session. We make extensive use of the dplyr packages, and at the end of the vignette use SingleCellExperiment and zellkonverter, so load those as well. ``` r suppressPackageStartupMessages({ library(dplyr) library(cellxgenedp) }) ``` ## Shiny `cxg()` provides a ‘shiny’ interface allowing discovery of collections and datasets, visualization of selected datasets in the cellxgene data portal, and download of datasets for use in R. ## Next steps View the artcle [Discover and download datasets and files from the cellxgene data portal][article]. [article]: https://mtmorgan.github.io/cellxgenedp/articles/using_cellxgenedp.html