scGenePanel

scGenePanel creates a multi-panel visualization for various gene expression metrics on user defined gene, sample group and cell types using single-cell RNAseq data.

Features

1. A multi-panel plot that contains:
   1. UMAP : Visualize cluster of cells, split by cell identity of interest and highlighted cell type of interest
   2. Violin plot : Visualize gene expression counts, colored by cell identity of interest and split by cell type of interest
   3. Tabular plot : Quantify cell counts, cell frequency ratio and quantiles of gene expression counts per cell identity of interest
2. Accepts two commonly used input data object (Seurat, SingleCellExperiment) via object parameter
3. "Tableau" or "RColorBrewer" discrete qualitative color palettes options available via col.palette parameter
4. Order of cell identity of interest can be changes via group_order parameter
5. Shiny version to explore gene expression data interactively

Installation

From Github repository (once publicly available)

library(devtools)
install_github("vandydata/scGenePanel")

From local Git clone

install.packages("/path/to/scGenePanel", repos = NULL, type = "source")
# with dependencies
install.packages("/path/to/scGenePanel", repos = NULL, type = "source", dependencies = TRUE)