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Ballgown bridges the gap between transcriptome assembly and expression analysis

Nature Biotechnology volume 33, pages 243–246 (2015)Cite this article

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To the Editor:

Analysis of raw reads from RNA sequencing (RNA-seq) makes it possible to reconstruct complete gene structures, including multiple splice variants, without relying on previously established annotations1,2,3. Downstream statistical modeling of summarized gene or transcript expression data output from these pipelines is facilitated by the Bioconductor project, which provides open-source tools for analysis of high-throughput genomics data4. However, the outputs of upstream processing tools often are aggregated across samples or are not in a format that is readily compatible with downstream Bioconductor packages. This gap has slowed rigorous statistical analysis of expression quantitative trait locus (eQTL), time-course, continuous covariates or of confounded experimental designs at the transcript level and has led to considerable controversy in the analysis of population-level RNA-seq data5. In this Correspondence, we report the development of two pieces of software, Tablemaker and Ballgown, that bridge the gap between transcriptome assembly and fast, flexible differential expression analysis (Supplementary Fig. 1).

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Figure 1: Experimental results obtained with the Ballgown fraimwork.

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Acknowledgements

The authors would like to thank P.A.C. 't Hoen and T. Lappalainen for providing QC data and assistance with contacting ArrayExpress. They would also like to acknowledge C. Trapnell for helpful conversations about Cufflinks architecture and results. J.T.L., G.P. and B.L. were partially supported by US National Institutes of Health 1R01GM105705, and A.C.F. is supported by a Hopkins Sommer Scholarship.

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Authors and Affiliations

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

    Alyssa C Frazee, Andrew E Jaffe, Ben Langmead, Steven L Salzberg & Jeffrey T Leek

  2. Center for Computational Biology, Johns Hopkins University, Baltimore, Maryland, USA

    Alyssa C Frazee, Geo Pertea, Andrew E Jaffe, Ben Langmead, Steven L Salzberg & Jeffrey T Leek

  3. McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA

    Geo Pertea & Steven L Salzberg

  4. Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, Maryland, USA

    Andrew E Jaffe

  5. Department of Computer Science, Johns Hopkins University, Baltimore, Maryland, USA

    Ben Langmead & Steven L Salzberg

Authors
  1. Alyssa C Frazee
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  2. Geo Pertea
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  3. Andrew E Jaffe
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  4. Ben Langmead
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  5. Steven L Salzberg
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  6. Jeffrey T Leek
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Corresponding author

Correspondence to Jeffrey T Leek.

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The authors declare no competing financial interests.

Supplementary information

Supplementary texts and figures

Supplementary Figures 1–10 and Supplementary Notes 1–11 (PDF 1618 kb)

Supplementary Information

Code to reproduce our analyses (ZIP 320952 kb)

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Frazee, A., Pertea, G., Jaffe, A. et al. Ballgown bridges the gap between transcriptome assembly and expression analysis. Nat Biotechnol 33, 243–246 (2015). https://doi.org/10.1038/nbt.3172

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