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Imputing gene expression from selectively reduced probe sets

Nature Methods volume 9, pages 1120–1125 (2012)Cite this article

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Abstract

Measuring complete gene expression profiles for a large number of experiments is costly. We propose an approach in which a small subset of probes is selected based on a preliminary set of full expression profiles. In subsequent experiments, only the subset is measured, and the missing values are imputed. We developed several algorithms to simultaneously select probes and impute missing values, and we demonstrate that these 'probe selection for imputation' (PSI) algorithms can successfully reconstruct missing gene expression values in a wide variety of applications, as evaluated using multiple metrics of biological importance. We analyze the performance of PSI methods under varying conditions, provide guidelines for choosing the optimal method based on the experimental setting, and indicate how to estimate imputation accuracy. Finally, we apply our approach to a large-scale study of immune system variation.

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Figure 1: An integrated approach to probe selection and imputation.
Figure 2: Relative and absolute imputation accuracy.
Figure 3: Additional evaluation metrics of biological relevance.
Figure 4: Cost-benefit analysis to determine the optimal number of selected probes and modular decomposition subsets.
Figure 5: The samples, probe ratio, linearity (SPRL) predictor and ImmVar results.

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Acknowledgements

This work was supported by grant RC2 GM093080 (funded through the American Recovery and Reinvestment Act) from the US National Institutes of Health–National Institute of General Medical Sciences to C.B. and D.K. We thank I. Amit and J. Ye for useful comments on this manuscript.

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Authors and Affiliations

  1. Department of Computer Science, Stanford University, Stanford, California, USA

    Yoni Donner & Daphne Koller

  2. Department of Microbiology and Immunobiology, Division of Immunology, Harvard Medical School, Boston, Massachusetts, USA

    Ting Feng & Christophe Benoist

Authors
  1. Yoni Donner
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  2. Ting Feng
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  3. Christophe Benoist
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  4. Daphne Koller
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Contributions

Y.D. and D.K. designed the methods; Y.D. implemented the methods, wrote the code, performed the experiments and analyzed the data; T.F. and C.B. provided data and gave feedback on the results; Y.D. and D.K. wrote the manuscript; C.B. reviewed and commented on the manuscript.

Corresponding author

Correspondence to Daphne Koller.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–8, Supplementary Table 1, Supplementary Results and Supplementary Note (PDF 1946 kb)

Supplementary Data

The data sets used in the experiments described in the paper, in the file format used by the PSI software. (ZIP 11389 kb)

Supplementary Software

PSI software. (ZIP 16 kb)

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Donner, Y., Feng, T., Benoist, C. et al. Imputing gene expression from selectively reduced probe sets. Nat Methods 9, 1120–1125 (2012). https://doi.org/10.1038/nmeth.2207

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