Brief Communication | Published:

Sailfish enables alignment-free isoform quantification from RNA-seq reads using lightweight algorithms

Nature Biotechnology volume 32, pages 462464 (2014) | Download Citation

Abstract

We introduce Sailfish, a computational method for quantifying the abundance of previously annotated RNA isoforms from RNA-seq data. Because Sailfish entirely avoids mapping reads, a time-consuming step in all current methods, it provides quantification estimates much faster than do existing approaches (typically 20 times faster) without loss of accuracy. By facilitating frequent reanalysis of data and reducing the need to optimize parameters, Sailfish exemplifies the potential of lightweight algorithms for efficiently processing sequencing reads.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Accessions

Sequence Read Archive

References

  1. 1.

    & BMC Bioinformatics 14, 91 (2013).

  2. 2.

    et al. Sci. Trans. Med. 111ra121 (2011).

  3. 3.

    , , & Genome Biol. 10, R25 (2009).

  4. 4.

    , , , & Nat. Methods 5, 621–628 (2008).

  5. 5.

    et al. Nat. Biotechnol. 28, 511–515 (2010).

  6. 6.

    & BMC Bioinformatics 12, 323 (2011).

  7. 7.

    & Nat. Methods 10, 71–73 (2012).

  8. 8.

    , , & Genome Biol. 14, R30 (2013).

  9. 9.

    , & Proceedings of the 10th International Workshop on Algorithms and Data Structures Halifax, NS, Canada, August 15–17, 2007 (eds. Dehne, F., Sack, J.-R. & Zeh, N.)139–150 (Springer, 2007).

  10. 10.

    & Bioinformatics 27, 764–770 (2011).

  11. 11.

    & Scand. J. Stat. 35, 335–353 (2008).

  12. 12.

    , , & Algorithms Mol. Biol. 6, 9 (2011).

  13. 13.

    , & Stat. Sci. 26, 62–83 (2011).

  14. 14.

    , & BMC Bioinformatics 12, 290 (2011).

  15. 15.

    et al. Nat. Biotechnol. 24, 1151–1161 (2006).

  16. 16.

    , , & BMC Bioinformatics 11, 94 (2010).

  17. 17.

    et al. Nucleic Acids Res. 40, 10073–10083 (2012).

  18. 18.

    et al. Nat. Biotechnol. 29, 644–652 (2011).

  19. 19.

    et al. BMC Bioinformatics 13 (suppl. 6), S5 (2012).

  20. 20.

    , , & Nucleic Acids Res. 40, D1, D130–D135 (2012).

  21. 21.

    et al. Nucleic Acids Res. 41, D1, D48–D55 (2013).

  22. 22.

    , & Bioinformatics 25, 1105–1111 (2009).

  23. 23.

    J. Comput. Sci. Coll. 23, 298–298 (2008).

Download references

Acknowledgements

This work has been partially funded by the US National Science Foundation (CCF-1256087, CCF-1053918, and EF-0849899) and US National Institutes of Health (R21AI085376, R21HG006913 and R01HG007104). C.K. received support as an Alfred P. Sloan Research Fellow. We would like to thank A. Roberts for helping to diagnose and resolve an artifact in an earlier version of this manuscript pertaining to the synthetic data generated by the Flux Simulator.

Author information

Affiliations

  1. Lane Center for Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.

    • Rob Patro
    •  & Carl Kingsford
  2. Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, Maryland, USA.

    • Stephen M Mount
  3. Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, USA.

    • Stephen M Mount

Authors

  1. Search for Rob Patro in:

  2. Search for Stephen M Mount in:

  3. Search for Carl Kingsford in:

Contributions

R.P., S.M.M. and C.K. designed the method and algorithms, devised the experiments, and wrote the manuscript. R.P. implemented the Sailfish software.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Carl Kingsford.

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–7, Supplementary Table 1 and Supplementary Notes 1–3

Zip files

  1. 1.

    Supplementary Data

    Version 0.6.3 of the Sailfish source code

About this article

Publication history

Received

Accepted

Published

DOI

https://doi.org/10.1038/nbt.2862

Further reading