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One read per cell per gene is optimal for single-cell RNA-Seq

M. J. Zhang, V. Ntranos, D. Tse
doi: https://doi.org/10.1101/389296
M. J. Zhang
1Department of Electrical Engineering, Stanford University, Stanford, CA
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V. Ntranos
1Department of Electrical Engineering, Stanford University, Stanford, CA
2Division of Biology and Biological Engineering, Caltech, Pasadena, CA
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D. Tse
1Department of Electrical Engineering, Stanford University, Stanford, CA
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  • For correspondence: dntse@stanford.edu
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Abstract

An underlying question for virtually all single-cell RNA sequencing experiments is how to allocate the limited sequencing budget: deep sequencing of a few cells or shallow sequencing of many cells? A mathematical framework reveals that, for estimating many important gene properties, the optimal allocation is to sequence at the depth of one read per cell per gene. Interestingly, the corresponding optimal estimator is not the widely-used plug-in estimator but one developed via empirical Bayes.

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Posted August 09, 2018.
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One read per cell per gene is optimal for single-cell RNA-Seq
M. J. Zhang, V. Ntranos, D. Tse
bioRxiv 389296; doi: https://doi.org/10.1101/389296
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One read per cell per gene is optimal for single-cell RNA-Seq
M. J. Zhang, V. Ntranos, D. Tse
bioRxiv 389296; doi: https://doi.org/10.1101/389296

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