Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

pLogo: a probabilistic approach to visualizing sequence motifs

Nature Methods volume 10, pages 1211–1212 (2013)Cite this article

Subjects

Abstract

Methods for visualizing protein or nucleic acid motifs have traditionally relied upon residue frequencies to graphically scale character heights. We describe the pLogo, a motif visualization in which residue heights are scaled relative to their statistical significance. A pLogo generation tool is publicly available at http://plogo.uconn.edu/ and supports real-time conditional probability calculations and visualizations.

Your institute does not have access to this article

Relevant articles

Open Access articles citing this article.

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

Buy

All prices are NET prices.

Figure 1: Comparison of sequence logo visualizations for the pLogo, iceLogo and WebLogo tools.
Figure 2: Demonstration of the use of pLogo conditional probabilities through fixed positions.

References

  1. Portales-Casamar, E. et al. Nucleic Acids Res. 38, D105–D110 (2010).

    CAS  Article  Google Scholar 

  2. Catterall, J.F. et al. Nature 275, 510–513 (1978).

    CAS  Article  Google Scholar 

  3. Munro, S. & Pelham, H.R. Cell 48, 899–907 (1987).

    CAS  Article  Google Scholar 

  4. Miller, M.L. et al. Sci. Signal. 1, ra2 (2008).

    Article  Google Scholar 

  5. Dahiya, A., Gavin, M.R., Luo, R.X. & Dean, D.C. Mol. Cell Biol. 20, 6799–6805 (2000).

    CAS  Article  Google Scholar 

  6. Saraste, M., Sibbald, P.R. & Wittinghofer, A. Trends Biochem. Sci. 15, 430–434 (1990).

    Article  Google Scholar 

  7. Schneider, T.D. & Stephens, R.M. Nucleic Acids Res. 18, 6097–6100 (1990).

    CAS  Article  Google Scholar 

  8. Vacic, V., Iakoucheva, L.M. & Radivojac, P. Bioinformatics 22, 1536–1537 (2006).

    CAS  Article  Google Scholar 

  9. Colaert, N., Helsens, K., Martens, L., Vandekerckhove, J. & Gevaert, K. Nat. Methods 6, 786–787 (2009).

    CAS  Article  Google Scholar 

  10. Workman, C.T. et al. Nucleic Acids Res. 33, W389–W392 (2005).

    CAS  Article  Google Scholar 

  11. Schwartz, D. & Gygi, S.P. Nat. Biotechnol. 23, 1391–1398 (2005).

    CAS  Article  Google Scholar 

  12. Prisic, S. et al. Proc. Natl. Acad. Sci. USA 107, 7521–7526 (2010).

    CAS  Article  Google Scholar 

  13. Chiang, C.W. et al. Genetics 180, 2277–2293 (2008).

    Article  Google Scholar 

  14. Chou, M.F. et al. PLoS ONE 7, e52747 (2012).

    CAS  Article  Google Scholar 

  15. Crooks, G.E., Hon, G., Chandonia, J.M. & Brenner, S.E. Genome Res. 14, 1188–1190 (2004).

    CAS  Article  Google Scholar 

  16. Hornbeck, P.V. et al. Nucleic Acids Res. 40, D261–D270 (2012).

    CAS  Article  Google Scholar 

  17. Feinmesser, R.L., Wicks, S.J., Taverner, C.J. & Chantry, A. J. Biol. Chem. 274, 16168–16173 (1999).

    CAS  Article  Google Scholar 

  18. Press, W.H., Teukolsky, S.A., Vetterling, W.T. & Flannery, B.P. Numerical Recipes: The Art of Scientific Computing 3rd edn. (Cambridge University Press, 2007).

  19. The UniProt Consortium. Nucleic Acids Res. 41, D43–D47 (2013).

  20. Forrester, M.T. et al. Nat. Biotechnol. 27, 557–559 (2009).

    CAS  Article  Google Scholar 

  21. Doulias, P.T. et al. Proc. Natl. Acad. Sci. USA 107, 16958–16963 (2010).

    CAS  Article  Google Scholar 

  22. Chen, Y.J., Ku, W.C., Lin, P.Y., Chou, H.C. & Khoo, K.H. J. Proteome Res. 9, 6417–6439 (2010).

    CAS  Article  Google Scholar 

  23. Lu, C.T. et al. Nucleic Acids Res. 41, D295–D305 (2013).

    CAS  Article  Google Scholar 

  24. Mahrus, S. et al. Cell 134, 866–876 (2008).

    CAS  Article  Google Scholar 

  25. Lüthi, A.U. & Martin, S.J. Cell Death Differ. 14, 641–650 (2007).

    Article  Google Scholar 

  26. Igarashi, Y. et al. Nucleic Acids Res. 35, D546–D549 (2007).

    CAS  Article  Google Scholar 

  27. Linheiro, R.S. & Bergman, C.M. Nucleic Acids Res. 36, 6199–6208 (2008).

    CAS  Article  Google Scholar 

Download references

Acknowledgements

The authors wish to thank J. Lubner for his assistance in beta-testing the pLogo Web tool. Additionally, we thank the University of Connecticut Bioinformatics Facility for hosting the pLogo website and maintaining the server on which it runs. This study was funded in part by grants from the University of Connecticut Research Foundation (D.S.) and a Genomes to Life grant from the US Department of Energy (G.M.C.).

Author information

Author notes

  1. Joseph P O'Shea and Michael F Chou: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Physiology and Neurobiology, University of Connecticut, Storrs, Connecticut, USA

    Joseph P O'Shea, Saad A Quader, James K Ryan & Daniel Schwartz

  2. Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA

    Michael F Chou & George M Church

Authors
  1. Joseph P O'Shea
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Michael F Chou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Saad A Quader
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. James K Ryan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. George M Church
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Daniel Schwartz
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

M.F.C. and D.S. conceived of and designed the study. J.P.O., M.F.C. and D.S. gathered and analyzed the data. J.P.O. and D.S. designed the website. J.P.O., S.A.Q. and J.K.R. coded the website. G.M.C. provided materials and experimental insights. D.S. wrote the initial manuscript. All authors helped edit the final manuscript.

Corresponding author

Correspondence to Daniel Schwartz.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figure 1–5 (PDF 8007 kb)

Supplementary Table 1

Source data for Supplementary Figure 1 (XLSX 64 kb)

Supplementary Table 2

Source data for Supplementary Figure 2 (XLSX 9 kb)

Supplementary Table 3

Source data for Supplementary Figure 3 (XLSX 89 kb)

Supplementary Table 4

Source data for Supplementary Figure 4 (XLSX 63 kb)

Supplementary Table 5

Source data for Supplementary Figure 5 (XLSX 126 kb)

Source data

Rights and permissions

Reprints and Permissions

About this article

Cite this article

O'Shea, J., Chou, M., Quader, S. et al. pLogo: a probabilistic approach to visualizing sequence motifs. Nat Methods 10, 1211–1212 (2013). https://doi.org/10.1038/nmeth.2646

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nmeth.2646

Further reading

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing