PT  - JOURNAL ARTICLE
AU  - Xun Zhu
AU  - Thomas Wolfgruber
AU  - Austin Tasato
AU  - David G. Garmire
AU  - Lana X Garmire
TI  - Granatum: a graphical single-cell RNA-Seq analysis pipeline for genomics scientists
AID  - 10.1101/110759
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 110759
4099  - http://biorxiv.org/content/early/2017/08/08/110759.short
4100  - http://biorxiv.org/content/early/2017/08/08/110759.full
AB  - 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/appscRNA-SeqSingle-cell high-throughput RNA sequencingDEdifferential expressionGSEAGene-set enrichment analysisKEGGKyoto Encyclopedia of Genes and GenomesGOGene ontologyPCAPrincipal component analysisSNEt-Distributed Stochastic Neighbor EmbeddingNMFNon-negative matrix factorizationHclustHierarchical clusteringPPIProtein-protein interaction