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

Xun Zhu, Thomas Wolfgruber, Austin Tasato, David G. Garmire, Lana X Garmire
doi: https://doi.org/10.1101/110759
Xun Zhu
1Graduate Program in Molecular Biology and Bioengineering, University of Hawaii at Manoa, Honolulu, HI 96816
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Thomas Wolfgruber
1Graduate Program in Molecular Biology and Bioengineering, University of Hawaii at Manoa, Honolulu, HI 96816
2Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI 96813
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Austin Tasato
3Department of Electrical Engineering, University of Hawaii at Manoa, Honolulu, HI 96816
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David G. Garmire
3Department of Electrical Engineering, University of Hawaii at Manoa, Honolulu, HI 96816
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Lana X Garmire
1Graduate Program in Molecular Biology and Bioengineering, University of Hawaii at Manoa, Honolulu, HI 96816
2Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI 96813
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  • For correspondence: LGarmire@cc.hawaii.edu
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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
  • Copyright 
    The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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    Posted August 08, 2017.
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    Granatum: a graphical single-cell RNA-Seq analysis pipeline for genomics scientists
    Xun Zhu, Thomas Wolfgruber, Austin Tasato, David G. Garmire, Lana X Garmire
    bioRxiv 110759; doi: https://doi.org/10.1101/110759
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    Granatum: a graphical single-cell RNA-Seq analysis pipeline for genomics scientists
    Xun Zhu, Thomas Wolfgruber, Austin Tasato, David G. Garmire, Lana X Garmire
    bioRxiv 110759; doi: https://doi.org/10.1101/110759

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