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 amounts of bioinformatics skills.
Results We have developed Granatum, a web-based scRNA-Seq analysis pipeline to make analysis more broadly accessible to researchers. Without a single line of programming code, users can click through the pipeline, setting parameters and visualizing results via the interactive graphical interface Granatum conveniently walks 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, geneexpression normalization, cell clustering, differential gene expression analysis, pathway/ontology enrichment analysis, protein-networ interaction visualization, and pseudo-time cell series construction.
Conclusions Granatum enables broad 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
- SNE
- t-Distributed Stochastic Neighbor Embedding
- NMF
- Non-negative matrix factorization
- Hclust
- Hierarchical clustering
- PPI
- Protein-protein interaction
