TY - JOUR T1 - Granatum: a graphical single-cell RNA-seq analysis pipeline for genomics scientists JF - bioRxiv DO - 10.1101/110759 SP - 110759 AU - Xun Zhu AU - Thomas Wolfgruber AU - Austin Tasato AU - Lana X Garmire Y1 - 2017/01/01 UR - http://biorxiv.org/content/early/2017/02/27/110759.abstract N2 - 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 code is freely available for research use at: http://garmiregroup.org/granatum/codescRNA-seqSingle-cell high-throughput RNA sequencingDEdifferential expressionGSEAGene-set enrichment analysisKEGGKyoto Encyclopedia of Genes and GenomesGOGene ontologyPCAPrincipal component analysist-SNEt-Distributed Stochastic Neighbor EmbeddingNMFNon-negative matrix factorizationHclustHierarchical clusteringPPIProtein-protein interaction ER -