Abstract
Background Single-cell RNA sequencing (scRNA-seq) is an increasingly popular platform to study heterogeneity at the single cell level. Computational methods to process scRNA-seq have limited accessibility to bench scientists, as they require significant amount of bioinformatics skills.
Results We have developed Granatum, a web browser based scRNA-seq analysis pipeline to make analysis more broadly accessible to researchers. Without a single line of programming code, a user can click through the pipeline, setting parameters and visualizing results via the interactive graphical interface. The pipeline conveniently walks the users through various steps of scRNA-seq analysis. It has a comprehensive list of modules, including plate merging and batch effect removal, outlier sample removal, gene filtering, gene expression normalization, cell clustering, differential gene expression analysis, pathway/ontology enrichment analysis, protein network interaction visualization, and pseudo-time cell series construction.
Conclusions Granatum enables much widely adoption of scRNA-seq technology by empowering the bench scientists with an easy to use graphical interface for scRNA-seq data analysis. The package is freely available for research use at: http://garmiregroup.org/granatum/app
List of abbreviations
- scRNA-seq
- Single-cell high-throughput RNA sequencing
- DE
- differential expression
- GSEA
- Gene-set enrichment analysis
- KEGG
- Kyoto Encyclopedia of Genes and Genomes
- GO
- Gene ontology
- PCA
- Principal component analysis
- t-SNE
- t-Distributed Stochastic Neighbor Embedding
- NMF
- Non-negative matrix factorization
- Hclust
- Hierarchical clustering
- PPI
- Protein-protein interaction