ShinyCellPlus

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ShinyCellPlus is a modular version of ShinyCell developed at the Monash Genomics and Bioinformatics Platform (MGBP). Each module consists on a tab in the app. Each module is created individually and is it selfcontained. ShinyCellPlus supports large scRNAseq and multimodal datasets with fast on-demand HDF5 access, extended visualisations, improved filtering, and publication-ready plots. Its modular structure makes it flexible, scalable, and easy to customise.

Features

• Modular UI and server structure
• Supports scRNAseq, ATAC, and multimodal datasets
• Fast HDF5 on-demand loading
• Publication‑ready plots (PNG/PDF export)
• Extended visualisation tabs (UMAP, 3D UMAP, violin, bubble, heatmap, coexpression, AUC marker genes)
• Cell subsetting and conditional plotting
• Easy integration with new modules via a registry system

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Fast usage just needs 3 steps

1. Setup

Clone this repository

git clone https://github.com/MonashBioinformaticsPlatform/ShinyCellPlus.git

Open the .Rproj file

Load RENV - all require library

install.packages("renv")
renv::restore()

Run the 2 helper functions prepShinyCellPlus() and useShinyCellPlus()

2. prepShinyCellPlus()

library(ShinyCell) #devtools::install_github("SGDDNB/ShinyCell")
library(Seurat)
library(Signac)
library(dplyr)


# Prepare seurat object, checks Key names, creates sc1counts.h5, adds a 3D reduction UMAP
cnts<-LoadSeuratRds("seurat_object.Rds")

source("functions/prepShinyCellPlus.R")

prepShinyCellPlus(seurat_rds = "seurat_obj.rds", # or seurat_obj = cnts
                  out_dir = "testing_data", 
                  do_umap3d = TRUE,  
                  do_markers= TRUE,   
                  markers_res_pattern = "RNA_snn_res")

3.useShinyCellPlus()

# Create a new app.R with the modified ShinyCell tabs

source("functions/useShinyCellPlus.R")

useShinyCellPlus(
    shiny.dir="testing_data/",
    shinycellplus.dir.src="~/ShinyCellPlus/",
    rsconnect.deploy = FALSE,
    data_type = "",
    enabled_tabs = c("cellinfo_cellinfo",
                    "cellinfo_geneexpr",
                    "cellinfo3D_cellinfo3D",
                    "cellinfo3D_geneexpr3D",
                    "genecoex",
                    "violin_boxplot",
                    "proportions",
                    "bubble_heatmap",
                    "pseudobulk"),
    overwrite_modules = TRUE,
    app_title='Testing'
)

Review Docs for further information on development instructions