Imputing gene expression from optimally reduced probe sets

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Imputing gene expression from optimally reduced probe sets

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Title: Imputing gene expression from optimally reduced probe sets
Author: Donner, Yoni; Feng, Ting; Benoist, Christophe O.; Koller, Daphne

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Citation: Donner, Yoni, Ting Feng, Christophe Benoist, and Daphne Koller. 2012. Imputing gene expression from optimally reduced probe sets. Nature methods 9(11): 1120-1125.
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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 develop several algorithms to simultaneously select probes and impute missing values, and 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.
Published Version: doi:10.1038/nmeth.2207
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3505039/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:11177919
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