Protocol | Published:

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

Nature Protocols volume 11, pages 16501667 (2016) | Download Citation

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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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.).

Author information

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

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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.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Steven L Salzberg.

Supplementary information

Zip files

  1. 1.

    Supplementary Software

    Unix shell script, configuration file, R file and README file

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DOI

https://doi.org/10.1038/nprot.2016.095

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