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bioRxiv · 10.1101/110759

Granatum: a graphical single-cell RNA-seq analysis pipeline for genomics scientists

Zhu, X.·Wolfgruber, T.·Tasato, A.·Garmire, L.
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Abstract

BackgroundSingle-cell RNA sequencing (scRNA-Seq) is an increasingly popular platform to study heterogeneity at the single-cell level.\n\nComputational methods to process scRNA-Seq have limited accessibility to bench scientists as they require significant amounts of bioinformatics skills.\n\nResultsWe 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.\n\nConclusionsGranatum 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

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Zhu, X., Wolfgruber, T., Tasato, A., Garmire, L.. 2017-02-22. Granatum: a graphical single-cell RNA-seq analysis pipeline for genomics scientists. https://doi.org/10.1101/110759

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