easyshiny
is a R package to quickly create an interactive web application to visualise and explore single-cell data.
Installation
Run the following code to check if the dependency packages are installed, else install them if required:
pkgs = c("bslib", "data.table", "DT", "ggdendro", "ggplot2", "ggplotify", "ggrepel", "glue", "grid", "hdf5r", "magrittr", "Matrix", "patchwork", "RColorBrewer", "readr", "remotes", "reticulate", "Seurat", "shiny", "shinycssloaders", "shinyhelper")
pkg = pkgs[!(pkgs %in% installed.packages()[,"Package"])]
if(length(pkg)){install.packages(pkg)}
# optional if you want to use custom fonts
install.packages("showtext")
# If you are using h5ad file as input, run the code below as well
# reticulate::py_install("anndata")
easyshiny
can then be installed from GitHub as follows:
remotes::install_github("NBISweden/easyshiny")
For usage and deploy guide, see here.
Screenshots
Single dataset
Multiple datasets
Cell information vs gene expression.
Cell information vs cell information.
Gene expression vs gene expression.
Gene co-expression.
Proportion plot.
Heatmap/Dotplot/Bubble plot.
Violin plot.
Acknowledgements
easyshiny is built on ShinyCell.
Ouyang, J. F., Kamaraj, U. S., Cao, E. Y., & Rackham, O. J. (2021). ShinyCell: simple and sharable visualization of single-cell gene expression data. Bioinformatics, 37(19), 3374-3376.
easyshiny was developed in collaboration with Makinen Lab. Thanks to Taija Mäkinen and Marle Kraft for their valuable contribution.
Issues
Report issues here.
2023 • NBIS