Single-cell RNA sequencing (scRNA-seq) enables the high-throughput quantification of gene expression profiles of individual cells and discovery of cellular heterogeneity and functional diversity. The increased complexity of scRNA-seq data present significant challenges for the effective analysis and interpretation of results. iS-CellR (Interactive platform for Single-cell RNAseq) is a web-based Shiny application designed to provide a comprehensive analysis of single-cell RNA sequencing data. iS-CellR provides a fast method for filtering and normalization of raw data, dimensionality reductions (linear and non-linear) to identify cell types clusters, differential gene expression analysis to locate markers, and inter-/intra-sample heterogeneity analysis. iS-CellR integrates the Seurat package with Shiny’s reactive programming framework and interactive visualization using plotly library. iS-CellR runs on any modern web browser and provides access to powerful R libraries through a graphical user interface. Each session of iS-CellR allows the user to share, reproduce and archive results without requiring programming skills.

How to Get Started and Load Data

It is important that the input file should follow the same format as descibed below.

To get started, please load in a CSV/TSV separated values file. The file should contain the count data where:

1. Columns are Cells
2. Rows are Genes
3. Optional: Cell names or Cell type in Column header followed by Cell id. eg. Tcell_TC1_fcount_1.

NOTE: An example CSV file can be accessed <a href=‘data/Maligant50.csv’, target=‘blank’, download = ‘Maligant50.csv’>here (right click save as).

Notes on Plots and Processed Data

All plots can be downloaded at a high resolution in PDF. This functionality works best in Chrome and Firefox. Within the Shiny app, user can control the labelling of clusters. User can also provide list of genes to compare their expression levels.

Questions

For any issues or questions that might arise, please email Mitul.Patel@immunocore.com.