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Determining sequencing depth in a single-cell RNA-seq experiment.

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? Here we present a mathematical framework which reveals that, for estimating many important gene properties, the optimal allocation is to sequence at a depth of around 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.

SUBMITTER: Zhang MJ 

PROVIDER: S-EPMC7005864 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Determining sequencing depth in a single-cell RNA-seq experiment.

Zhang Martin Jinye MJ   Ntranos Vasilis V   Tse David D  

Nature communications 20200207 1

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? Here we present a mathematical framework which reveals that, for estimating many important gene properties, the optimal allocation is to sequence at a depth of around one read per cell per gene. Interestingly, the corresponding optimal estimator is not the widely-used plug-in estimator, but one develo  ...[more]

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