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.

Reply to ‘Inflated performance measures in enhancer–promoter interaction-prediction methods’

Nature Genetics volume 51, pages 1198–1200 (2019)Cite this article

Subjects

First, let us elaborate on how enhancer–promoter interaction data can violate the IID assumption. The unit of measurement here is an enhancer–promoter pair, upon which many genomic features are observed. Dependence arises from (i) promoters interacting with more than one enhancer, (ii) enhancers interacting with more than one promoter and (iii) genomic features, such as broad histone modification peaks, that overlap more than one enhancer–promoter pair, primarily because of proximal clusters of regulatory elements. In the published TargetFinder training data, promiscuous promoters interacting with many enhancers are the major contributor to dependence between pairs. Regarding the identically distributed assumption, we note that genomic loci have different types and levels of genomic features, as do different cell lines. Consequently, enhancer–promoter pairs that are independent (for example, on different chromosomes) may not be identically distributed. Thus, both parts of the IID assumption may be violated, and data more consistent with one part of the assumption may be less consistent with the other.

Your institute does not have access to this article

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

Buy

All prices are NET prices.

Fig. 1: Corrected performance across and within cell types.
Fig. 2: Corrected performance within cell types only.

References

  1. Cao, F. & Fullwood, M. J. Nat. Genet. https://doi.org/10.1038/s41588-019-0434-7 (2019).

  2. Xi, W. & Beer, M. A. PLoS Comput. Biol. 14, e1006625 (2018).

    Article  Google Scholar 

  3. Whalen, S., Truty, R. M. & Pollard, K. S. Nat. Genet. 48, 488–496 (2016).

    CAS  Article  Google Scholar 

  4. Dundar, M., Krishnapuram, B., Bi, J. & Rao, R.B. in Proc. 20th International Joint Conference on Artificial Intelligence 756–761 (IJCAI, 2007).

  5. Kwasnieski, J. C., Fiore, C., Chaudhari, H. G. & Cohen, B. A. Genome Res. 24, 1595–1602 (2014).

    CAS  Article  Google Scholar 

  6. Cao, Q. et al. Nat. Genet. 49, 1428–1436 (2017).

    CAS  Article  Google Scholar 

  7. Kelley, D. R. et al. Genome Res. 28, 739–750 (2018).

    CAS  Article  Google Scholar 

  8. Hait, T. A., Amar, D., Shamir, R. & Elkon, R. Genome Biol. 19, 56 (2018).

    Article  Google Scholar 

  9. Schreiber, J., Libbrecht, M., Bilmes, J. & Noble, W.S. Preprint at bioRxiv https://doi.org/10.1101/103614 (2018).

  10. Chicco, D. BioData Min. 10, 35 (2017).

    Article  Google Scholar 

  11. Arthur, R. K., An, N., Khan, S. & McNerney, M. E. Nucleic Acids Res. 45, 6350–6361 (2017).

    CAS  Article  Google Scholar 

  12. Weintraub, A. S. et al. Cell 171, 1573–1588.e28 (2017).

    CAS  Article  Google Scholar 

  13. Tan, J. Y. et al. Cell Rep. 18, 2280–2288 (2017).

    CAS  Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Gladstone Institutes, San Francisco, CA, USA

    Sean Whalen & Katherine S. Pollard

  2. Department of Epidemiology and Biostatistics, Institute for Human Genetics, Quantitative Biology Institute, and Institute for Computational Health Sciences, University of California, San Francisco, San Francisco, CA, USA

    Katherine S. Pollard

  3. Chan-Zuckerberg Biohub, San Francisco, CA, USA

    Katherine S. Pollard

Authors
  1. Sean Whalen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Katherine S. Pollard
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Katherine S. Pollard.

Ethics declarations

Competing interests

The authors declare no competing interests.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Whalen, S., Pollard, K.S. Reply to ‘Inflated performance measures in enhancer–promoter interaction-prediction methods’. Nat Genet 51, 1198–1200 (2019). https://doi.org/10.1038/s41588-019-0473-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41588-019-0473-0

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