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Epigenome-wide association studies without the need for cell-type composition

Nature Methods volume 11, pages 309–311 (2014)Cite this article

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Abstract

In epigenome-wide association studies, cell-type composition often differs between cases and controls, yielding associations that simply tag cell type rather than reveal fundamental biology. Current solutions require actual or estimated cell-type composition—information not easily obtainable for many samples of interest. We propose a method, FaST-LMM-EWASher, that automatically corrects for cell-type composition without the need for explicit knowledge of it, and then validate our method by comparison with the state-of-the-art approach. Corresponding software is available from http://www.microsoft.com/science/.

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Figure 1: RA methylation analysis for 354 cases and 312 controls across 103,638 loci1.
Figure 2: Simulated data with cell-type composition characteristics based on the actual RA data used in Figure 1 (354 cases and 312 controls across 103,638 loci).

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Acknowledgements

We thank Y. Yamanaka for helpful feedback on the manuscript and D. Koestler, M. Kobor, G. Quon for useful discussions.

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Authors and Affiliations

  1. eScience Research Group, Microsoft Research, Los Angeles, California, USA

    James Zou, Christoph Lippert, David Heckerman & Jennifer Listgarten

  2. The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA

    James Zou

  3. School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts, USA

    James Zou

  4. Harvard Medical School, Boston, Massachusetts, USA

    Martin Aryee

  5. Massachusetts General Hospital, Boston, Massachusetts, USA

    Martin Aryee

Authors
  1. James Zou
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  2. Christoph Lippert
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  3. David Heckerman
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  4. Martin Aryee
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  5. Jennifer Listgarten
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Contributions

J.Z. and J.L. designed research, performed research, contributed analytic tools, analyzed data and wrote the paper. C.L. and D.H. contributed analytic tools. M.A. designed research.

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Correspondence to James Zou or Jennifer Listgarten.

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Competing interests

J.Z., C.L., D.H. and J.L. were employees of Microsoft at the time this work was performed.

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Supplementary Figures 1–12, Supplementary Tables 1–3 and Supplementary Notes 1 and 2. (PDF 2262 kb)

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Zou, J., Lippert, C., Heckerman, D. et al. Epigenome-wide association studies without the need for cell-type composition. Nat Methods 11, 309–311 (2014). https://doi.org/10.1038/nmeth.2815

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