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Gene expression deconvolution in linear space

Nature Methods volume 9, page 9 (2012)Cite this article

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Shen-Orr et al. reply:

We appreciate the comments made by Zhong and Liu and their hard work on the proof1. Indeed, removing unneeded normalization methods, including log transformation, can yield even better linearity results, optimizing the use of deconvolution methods.

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References

  1. Zhong, Y. & Liu, Z. Nat. Methods 9, 8–9 (2011).

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  2. Shen-Orr, S.S. et al. Nat. Methods 7, 287–289 (2010).

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Authors and Affiliations

  1. Department of Immunology, Rappaport Faculty of Medicine, Technion, Haifa, Israel

    Shai S Shen-Orr

  2. Health Research and Policy and Department of Statistics, Stanford University School of Medicine, Stanford, California, USA

    Robert Tibshirani

  3. Division of Systems Medicine, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA

    Atul J Butte

Authors
  1. Shai S Shen-Orr
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  2. Robert Tibshirani
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  3. Atul J Butte
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Corresponding author

Correspondence to Shai S Shen-Orr.

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Shen-Orr, S., Tibshirani, R. & Butte, A. Gene expression deconvolution in linear space. Nat Methods 9, 9 (2012). https://doi.org/10.1038/nmeth.1831

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