Brief Communication | Published:

TACO produces robust multisample transcriptome assemblies from RNA-seq

Nature Methods volume 14, pages 6870 (2017) | Download Citation

Abstract

Accurate transcript structure and abundance inference from RNA sequencing (RNA-seq) data is foundational for molecular discovery. Here we present TACO, a computational method to reconstruct a consensus transcriptome from multiple RNA-seq data sets. TACO employs novel change-point detection to demarcate transcript start and end sites, leading to improved reconstruction accuracy compared with other tools in its class. The tool is available at http://tacorna.github.io and can be readily incorporated into RNA-seq analysis workflows.

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Acknowledgements

This work was supported in part by the NIH Prostate Specialized Program of Research Excellence grant P50CA186786 (A.M.C.), F30 CA 200328 (Y.S.N.), U01CA214170 (A.M.C.), and U24 CA210967 (A.M.C.). A.M.C. is supported by the Prostate Cancer Foundation and the Howard Hughes Medical Institute. A.M.C. is an American Cancer Society Research Professor and a Taubman Scholar of the University of Michigan.

Author information

Affiliations

  1. Michigan Center for Translational Pathology, University of Michigan, Ann Arbor, Michigan, USA.

    • Yashar S Niknafs
    • , Balaji Pandian
    • , Arul M Chinnaiyan
    •  & Matthew K Iyer
  2. Department of Cellular and Molecular Biology, University of Michigan, Ann Arbor, Michigan, USA.

    • Yashar S Niknafs
    •  & Arul M Chinnaiyan
  3. Department of Statistics, Colorado State University, Fort Collins, Colorado, USA.

    • Hariharan K Iyer
  4. Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA.

    • Arul M Chinnaiyan
  5. Howard Hughes Medical Institute, University of Michigan, Ann Arbor, Michigan, USA.

    • Arul M Chinnaiyan
  6. Comprehensive Cancer Center, University of Michigan, Ann Arbor, Michigan, USA.

    • Arul M Chinnaiyan
  7. Department of Urology, University of Michigan, Ann Arbor, Michigan, USA.

    • Arul M Chinnaiyan

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Contributions

M.K.I. designed the core of TACO method with assistance from Y.S.N., B.P., and H.K.I. The change-point detection method was developed by Y.S.N. and M.K.I. Code optimization was performed by M.K.I., B.P., and Y.S.N. Performance benchmarking was performed by Y.S.N. Y.S.N., A.M.C., and M.K.I. wrote the manuscript. A.M.C. supervised development of the tool and guided the project to completion. All authors read and approved the final manuscript.

Competing interests

Oncomine is supported by ThermoFisher, Inc. (previously Life Technologies and Compendia Biosciences). A.M.C. was a cofounder of Compendia Biosciences and served on the scientific advisory board of Life Technologies before it was acquired.

Corresponding author

Correspondence to Arul M Chinnaiyan.

Integrated supplementary information

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–10 and Supplementary Note.

Excel files

  1. 1.

    Supplementary Table 1

    Samples used.

  2. 2.

    Supplementary Table 2

    Batches used.

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    Supplementary Table 3

    Batch size statistics.

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    Supplementary Table 4

    Isoform fraction statistics.

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    Supplementary Table 5

    GTEX Samples used.

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    Supplementary Table 6

    High expression statistics.

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    Supplementary Table 7

    Changepoint parameter statistics.

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DOI

https://doi.org/10.1038/nmeth.4078