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  • Protocol
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Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown

Nature Protocols volume 11, pages 1650–1667 (2016)Cite this article

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Abstract

High-throughput sequencing of mRNA (RNA-seq) has become the standard method for measuring and comparing the levels of gene expression in a wide variety of species and conditions. RNA-seq experiments generate very large, complex data sets that demand fast, accurate and flexible software to reduce the raw read data to comprehensible results. HISAT (hierarchical indexing for spliced alignment of transcripts), StringTie and Ballgown are free, open-source software tools for comprehensive analysis of RNA-seq experiments. Together, they allow scientists to align reads to a genome, assemble transcripts including novel splice variants, compute the abundance of these transcripts in each sample and compare experiments to identify differentially expressed genes and transcripts. This protocol describes all the steps necessary to process a large set of raw sequencing reads and create lists of gene transcripts, expression levels, and differentially expressed genes and transcripts. The protocol's execution time depends on the computing resources, but it typically takes under 45 min of computer time. HISAT, StringTie and Ballgown are available from http://ccb.jhu.edu/software.shtml.

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Figure 1: An overview of the 'new Tuxedo' protocol.
Figure 2: Merging transcript assemblies using StringTie's merge function.
Figure 3: Distribution of FPKM values across the 12 samples.
Figure 4
Figure 5: Structure and expression levels of five distinct isoforms of the XIST gene in sample ERR188234.
Figure 6: Overall distribution of differential expression P values in females and males.

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Acknowledgements

This work was supported in part by the National Institutes of Health under grants R01-HG006677 (to S.L.S.), R01-GM083873 (to S.L.S.) and R01-GM105705 (to J.T.L.), and the National Science Foundation under grant DBI-1458178 (to M.P.).

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Authors and Affiliations

  1. Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA

    Mihaela Pertea, Daehwan Kim, Geo M Pertea & Steven L Salzberg

  2. Department of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, Maryland, USA

    Mihaela Pertea & Steven L Salzberg

  3. Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA

    Jeffrey T Leek & Steven L Salzberg

  4. Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA

    Steven L Salzberg

Authors
  1. Mihaela Pertea
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  2. Daehwan Kim
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  4. Jeffrey T Leek
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  5. Steven L Salzberg
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Contributions

M.P. led the development of the protocol, with help from all the authors. D.K. is the main developer of HISAT, M.P. led the development of StringTie and J.T.L. is the senior author of Ballgown. G.M.P. developed gffcompare and contributed to StringTie. All authors contributed to the writing of the manuscript. S.L.S. supervised the entire project.

Corresponding author

Correspondence to Steven L Salzberg.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Software

Unix shell script, configuration file, R file and README file (ZIP 4 kb)

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Pertea, M., Kim, D., Pertea, G. et al. Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown. Nat Protoc 11, 1650–1667 (2016). https://doi.org/10.1038/nprot.2016.095

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